{ "cells": [ { "cell_type": "code", "execution_count": 6, "id": "junior-accounting", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Channels:\n", " - defaults\n", "Platform: linux-64\n", "Collecting package metadata (repodata.json): done\n", "Solving environment: done\n", "\n", "## Package Plan ##\n", "\n", " environment location: /usr/licensed/anaconda3/2024.6\n", "\n", " added / updated specs:\n", " - h5netcdf\n", " - netcdf4\n", "\n", "\n", "The following NEW packages will be INSTALLED:\n", "\n", " cftime pkgs/main/linux-64::cftime-1.6.4-py312h5eee18b_0 \n", " h5netcdf pkgs/main/linux-64::h5netcdf-1.2.0-py312h06a4308_0 \n", " hdf4 pkgs/main/linux-64::hdf4-4.2.13-h3ca952b_2 \n", " libnetcdf pkgs/main/linux-64::libnetcdf-4.8.1-h14805e7_4 \n", " libzip pkgs/main/linux-64::libzip-1.8.0-h6ac8c49_1 \n", " netcdf4 pkgs/main/linux-64::netcdf4-1.6.2-py312h33ae428_0 \n", "\n", "The following packages will be UPDATED:\n", "\n", " ca-certificates 2024.3.11-h06a4308_0 --> 2024.12.31-h06a4308_0 \n", " certifi 2024.6.2-py312h06a4308_0 --> 2025.1.31-py312h06a4308_0 \n", " conda 24.5.0-py312h06a4308_0 --> 24.11.3-py312h06a4308_0 \n", " openssl 3.0.14-h5eee18b_0 --> 3.0.15-h5eee18b_0 \n", "\n", "\n", "\n", "Downloading and Extracting Packages:\n", "\n", "Preparing transaction: done\n", "Verifying transaction: failed\n", "\n", "EnvironmentNotWritableError: The current user does not have write permissions to the target environment.\n", " environment location: /usr/licensed/anaconda3/2024.6\n", " uid: 227132\n", " gid: 30119\n", "\n", "\n", "\n", "Note: you may need to restart the kernel to use updated packages.\n" ] } ], "source": [ "conda install netcdf4 h5netcdf" ] }, { "cell_type": "code", "execution_count": 9, "id": "7bfb4bb2-5a53-4b02-894a-79aa6044cde0", "metadata": { "scrolled": true }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Channels:\n", " - conda-forge\n", " - defaults\n", "Platform: linux-64\n", "Collecting package metadata (repodata.json): done\n", "Solving environment: done\n", "\n", "## Package Plan ##\n", "\n", " environment location: /usr/licensed/anaconda3/2024.6\n", "\n", " added / updated specs:\n", " - bottleneck\n", " - dask\n", " - netcdf4\n", " - xarray\n", "\n", "\n", "The following packages will be downloaded:\n", "\n", " package | build\n", " ---------------------------|-----------------\n", " _libgcc_mutex-0.1 | conda_forge 3 KB conda-forge\n", " _openmp_mutex-4.5 | 2_gnu 23 KB conda-forge\n", " blosc-1.21.5 | hc2324a3_1 48 KB conda-forge\n", " bottleneck-1.4.2 | py312hc0a28a1_0 138 KB conda-forge\n", " ca-certificates-2025.1.31 | hbcca054_0 154 KB conda-forge\n", " cached-property-1.5.2 | hd8ed1ab_1 4 KB conda-forge\n", " cached_property-1.5.2 | pyha770c72_1 11 KB conda-forge\n", " certifi-2025.1.31 | pyhd8ed1ab_0 159 KB conda-forge\n", " cftime-1.6.4 | py312hc0a28a1_1 242 KB conda-forge\n", " cloudpickle-3.1.1 | pyhd8ed1ab_0 25 KB conda-forge\n", " conda-25.1.1 | py312h7900ff3_0 1.1 MB conda-forge\n", " dask-2025.2.0 | pyhd8ed1ab_0 7 KB conda-forge\n", " dask-core-2025.2.0 | pyhd8ed1ab_0 946 KB conda-forge\n", " dask-expr-2.0.0 | pyhd8ed1ab_0 9 KB conda-forge\n", " distributed-2025.2.0 | pyhd8ed1ab_0 782 KB conda-forge\n", " expat-2.6.4 | h5888daf_0 135 KB conda-forge\n", " fontconfig-2.14.2 | h14ed4e7_0 266 KB conda-forge\n", " h5py-3.12.1 |nompi_py312hedeef09_103 1.3 MB conda-forge\n", " hdf4-4.2.15 | h9772cbc_5 951 KB conda-forge\n", " hdf5-1.14.3 |nompi_h4f84152_101 3.7 MB conda-forge\n", " libaec-1.1.3 | h59595ed_0 35 KB conda-forge\n", " libarchive-3.7.4 | hfca40fe_0 851 KB conda-forge\n", " libexpat-2.6.4 | h5888daf_0 72 KB conda-forge\n", " libgcc-14.2.0 | h77fa898_1 829 KB conda-forge\n", " libgcc-ng-14.2.0 | h69a702a_1 53 KB conda-forge\n", " libgfortran-14.2.0 | h69a702a_1 53 KB conda-forge\n", " libgfortran-ng-14.2.0 | h69a702a_1 53 KB conda-forge\n", " libgfortran5-14.2.0 | hd5240d6_1 1.4 MB conda-forge\n", " libgomp-14.2.0 | h77fa898_1 450 KB conda-forge\n", " libmamba-1.5.11 | hfe524e5_0 1.8 MB\n", " libmambapy-1.5.11 | py312haf1ee3a_0 340 KB\n", " libnetcdf-4.9.2 |nompi_h9612171_113 829 KB conda-forge\n", " libnsl-2.0.1 | hd590300_0 33 KB conda-forge\n", " libsqlite-3.46.0 | hde9e2c9_0 845 KB conda-forge\n", " libstdcxx-14.2.0 | hc0a3c3a_1 3.7 MB conda-forge\n", " libstdcxx-ng-14.2.0 | h4852527_1 53 KB conda-forge\n", " libuuid-2.38.1 | h0b41bf4_0 33 KB conda-forge\n", " libxcrypt-4.4.36 | hd590300_1 98 KB conda-forge\n", " libxkbcommon-1.7.0 | h662e7e4_0 580 KB conda-forge\n", " libxml2-2.13.5 | hfdd30dd_0 738 KB\n", " libxslt-1.1.39 | h76b75d6_0 248 KB conda-forge\n", " libzip-1.10.1 | h2629f0a_3 105 KB conda-forge\n", " libzlib-1.2.13 | h4ab18f5_6 60 KB conda-forge\n", " lxml-5.2.2 | py312hb90d8a5_0 1.3 MB conda-forge\n", " netcdf4-1.6.5 |nompi_py312h39d4375_102 542 KB conda-forge\n", " numba-0.59.1 | py312hacefee8_0 5.4 MB conda-forge\n", " openssl-3.4.1 | h7b32b05_0 2.8 MB conda-forge\n", " pytables-3.9.2 | py312h5531bb7_1 1.5 MB conda-forge\n", " python-3.12.2 |hab00c5b_0_cpython 30.8 MB conda-forge\n", " python_abi-3.12 | 5_cp312 6 KB conda-forge\n", " qt-webengine-5.15.9 | he2071f7_8 53.7 MB\n", " snappy-1.2.1 | h8bd8927_1 42 KB conda-forge\n", " xarray-2025.1.2 | pyhd8ed1ab_0 818 KB conda-forge\n", " xkeyboard-config-2.42 | h4ab18f5_0 380 KB conda-forge\n", " xorg-kbproto-1.0.7 | hb9d3cd8_1003 30 KB conda-forge\n", " xorg-libx11-1.8.9 | h8ee46fc_0 809 KB conda-forge\n", " xorg-libxau-1.0.12 | hb9d3cd8_0 14 KB conda-forge\n", " xorg-xextproto-7.3.0 | hb9d3cd8_1004 30 KB conda-forge\n", " xorg-xproto-7.0.31 | hb9d3cd8_1008 72 KB conda-forge\n", " zlib-1.2.13 | h4ab18f5_6 91 KB conda-forge\n", " zstandard-0.23.0 | py312hef9b889_1 410 KB conda-forge\n", " zstd-1.5.6 | ha6fb4c9_0 542 KB conda-forge\n", " ------------------------------------------------------------\n", " Total: 122.3 MB\n", "\n", "The following NEW packages will be INSTALLED:\n", "\n", " cached-property conda-forge/noarch::cached-property-1.5.2-hd8ed1ab_1 \n", " cached_property conda-forge/noarch::cached_property-1.5.2-pyha770c72_1 \n", " cftime conda-forge/linux-64::cftime-1.6.4-py312hc0a28a1_1 \n", " hdf4 conda-forge/linux-64::hdf4-4.2.15-h9772cbc_5 \n", " libexpat conda-forge/linux-64::libexpat-2.6.4-h5888daf_0 \n", " libgcc conda-forge/linux-64::libgcc-14.2.0-h77fa898_1 \n", " libgfortran conda-forge/linux-64::libgfortran-14.2.0-h69a702a_1 \n", " libnetcdf conda-forge/linux-64::libnetcdf-4.9.2-nompi_h9612171_113 \n", " libnsl conda-forge/linux-64::libnsl-2.0.1-hd590300_0 \n", " libsqlite conda-forge/linux-64::libsqlite-3.46.0-hde9e2c9_0 \n", " libstdcxx conda-forge/linux-64::libstdcxx-14.2.0-hc0a3c3a_1 \n", " libxcrypt conda-forge/linux-64::libxcrypt-4.4.36-hd590300_1 \n", " libzip conda-forge/linux-64::libzip-1.10.1-h2629f0a_3 \n", " libzlib conda-forge/linux-64::libzlib-1.2.13-h4ab18f5_6 \n", " netcdf4 conda-forge/linux-64::netcdf4-1.6.5-nompi_py312h39d4375_102 \n", " python_abi conda-forge/linux-64::python_abi-3.12-5_cp312 \n", " xkeyboard-config conda-forge/linux-64::xkeyboard-config-2.42-h4ab18f5_0 \n", " xorg-kbproto conda-forge/linux-64::xorg-kbproto-1.0.7-hb9d3cd8_1003 \n", " xorg-libx11 conda-forge/linux-64::xorg-libx11-1.8.9-h8ee46fc_0 \n", " xorg-libxau conda-forge/linux-64::xorg-libxau-1.0.12-hb9d3cd8_0 \n", " xorg-xextproto conda-forge/linux-64::xorg-xextproto-7.3.0-hb9d3cd8_1004 \n", " xorg-xproto conda-forge/linux-64::xorg-xproto-7.0.31-hb9d3cd8_1008 \n", "\n", "The following packages will be UPDATED:\n", "\n", " blosc pkgs/main::blosc-1.21.3-h6a678d5_0 --> conda-forge::blosc-1.21.5-hc2324a3_1 \n", " bottleneck pkgs/main::bottleneck-1.3.7-py312ha88~ --> conda-forge::bottleneck-1.4.2-py312hc0a28a1_0 \n", " ca-certificates pkgs/main::ca-certificates-2024.3.11-~ --> conda-forge::ca-certificates-2025.1.31-hbcca054_0 \n", " certifi pkgs/main/linux-64::certifi-2024.6.2-~ --> conda-forge/noarch::certifi-2025.1.31-pyhd8ed1ab_0 \n", " cloudpickle pkgs/main/linux-64::cloudpickle-2.2.1~ --> conda-forge/noarch::cloudpickle-3.1.1-pyhd8ed1ab_0 \n", " conda pkgs/main::conda-24.5.0-py312h06a4308~ --> conda-forge::conda-25.1.1-py312h7900ff3_0 \n", " dask pkgs/main/linux-64::dask-2024.5.0-py3~ --> conda-forge/noarch::dask-2025.2.0-pyhd8ed1ab_0 \n", " dask-core pkgs/main/linux-64::dask-core-2024.5.~ --> conda-forge/noarch::dask-core-2025.2.0-pyhd8ed1ab_0 \n", " dask-expr pkgs/main/linux-64::dask-expr-1.1.0-p~ --> conda-forge/noarch::dask-expr-2.0.0-pyhd8ed1ab_0 \n", " distributed pkgs/main/linux-64::distributed-2024.~ --> conda-forge/noarch::distributed-2025.2.0-pyhd8ed1ab_0 \n", " expat pkgs/main::expat-2.6.2-h6a678d5_0 --> conda-forge::expat-2.6.4-h5888daf_0 \n", " fontconfig pkgs/main::fontconfig-2.14.1-h4c34cd2~ --> conda-forge::fontconfig-2.14.2-h14ed4e7_0 \n", " h5py pkgs/main::h5py-3.11.0-py312h34c39bb_0 --> conda-forge::h5py-3.12.1-nompi_py312hedeef09_103 \n", " hdf5 pkgs/main::hdf5-1.12.1-h2b7332f_3 --> conda-forge::hdf5-1.14.3-nompi_h4f84152_101 \n", " libaec pkgs/main::libaec-1.0.4-he6710b0_1 --> conda-forge::libaec-1.1.3-h59595ed_0 \n", " libarchive pkgs/main::libarchive-3.6.2-h6ac8c49_3 --> conda-forge::libarchive-3.7.4-hfca40fe_0 \n", " libgcc-ng pkgs/main::libgcc-ng-11.2.0-h1234567_1 --> conda-forge::libgcc-ng-14.2.0-h69a702a_1 \n", " libgfortran-ng pkgs/main::libgfortran-ng-11.2.0-h003~ --> conda-forge::libgfortran-ng-14.2.0-h69a702a_1 \n", " libgfortran5 pkgs/main::libgfortran5-11.2.0-h12345~ --> conda-forge::libgfortran5-14.2.0-hd5240d6_1 \n", " libgomp pkgs/main::libgomp-11.2.0-h1234567_1 --> conda-forge::libgomp-14.2.0-h77fa898_1 \n", " libmamba 1.5.8-hfe524e5_2 --> 1.5.11-hfe524e5_0 \n", " libmambapy 1.5.8-py312h2dafd23_2 --> 1.5.11-py312haf1ee3a_0 \n", " libstdcxx-ng pkgs/main::libstdcxx-ng-11.2.0-h12345~ --> conda-forge::libstdcxx-ng-14.2.0-h4852527_1 \n", " libuuid pkgs/main::libuuid-1.41.5-h5eee18b_0 --> conda-forge::libuuid-2.38.1-h0b41bf4_0 \n", " libxkbcommon pkgs/main::libxkbcommon-1.0.1-h5eee18~ --> conda-forge::libxkbcommon-1.7.0-h662e7e4_0 \n", " libxml2 2.10.4-hfdd30dd_2 --> 2.13.5-hfdd30dd_0 \n", " libxslt pkgs/main::libxslt-1.1.37-h5eee18b_1 --> conda-forge::libxslt-1.1.39-h76b75d6_0 \n", " lxml pkgs/main::lxml-5.2.1-py312hdbbb534_0 --> conda-forge::lxml-5.2.2-py312hb90d8a5_0 \n", " openssl pkgs/main::openssl-3.0.14-h5eee18b_0 --> conda-forge::openssl-3.4.1-h7b32b05_0 \n", " pytables pkgs/main::pytables-3.9.2-py312h387d6~ --> conda-forge::pytables-3.9.2-py312h5531bb7_1 \n", " qt-webengine 5.15.9-h9ab4d14_7 --> 5.15.9-he2071f7_8 \n", " snappy pkgs/main::snappy-1.1.10-h6a678d5_1 --> conda-forge::snappy-1.2.1-h8bd8927_1 \n", " xarray pkgs/main/linux-64::xarray-2023.6.0-p~ --> conda-forge/noarch::xarray-2025.1.2-pyhd8ed1ab_0 \n", " zlib pkgs/main::zlib-1.2.13-h5eee18b_1 --> conda-forge::zlib-1.2.13-h4ab18f5_6 \n", " zstandard pkgs/main::zstandard-0.22.0-py312h2c3~ --> conda-forge::zstandard-0.23.0-py312hef9b889_1 \n", " zstd pkgs/main::zstd-1.5.5-hc292b87_2 --> conda-forge::zstd-1.5.6-ha6fb4c9_0 \n", "\n", "The following packages will be SUPERSEDED by a higher-priority channel:\n", "\n", " _libgcc_mutex pkgs/main::_libgcc_mutex-0.1-main --> conda-forge::_libgcc_mutex-0.1-conda_forge \n", " _openmp_mutex pkgs/main::_openmp_mutex-5.1-1_gnu --> conda-forge::_openmp_mutex-4.5-2_gnu \n", " numba pkgs/main::numba-0.59.1-py312h526ad5a~ --> conda-forge::numba-0.59.1-py312hacefee8_0 \n", " python pkgs/main::python-3.12.4-h5148396_1 --> conda-forge::python-3.12.2-hab00c5b_0_cpython \n", "\n", "\n", "\n", "Downloading and Extracting Packages:\n", "qt-webengine-5.15.9 | 53.7 MB | | 0% \n", "python-3.12.2 | 30.8 MB | | 0% \u001b[A\n", "\n", "numba-0.59.1 | 5.4 MB | | 0% \u001b[A\u001b[A\n", "\n", "\n", "libstdcxx-14.2.0 | 3.7 MB | | 0% \u001b[A\u001b[A\u001b[A\n", "\n", "\n", "\n", "hdf5-1.14.3 | 3.7 MB | | 0% \u001b[A\u001b[A\u001b[A\u001b[A\n", "\n", "\n", "\n", "\n", "openssl-3.4.1 | 2.8 MB | | 0% \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n", "\n", "\n", "\n", "\n", "\n", "libmamba-1.5.11 | 1.8 MB | | 0% \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n", "\n", "\n", "\n", "\n", "\n", "\n", "pytables-3.9.2 | 1.5 MB | | 0% \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "libgfortran5-14.2.0 | 1.4 MB | | 0% \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "lxml-5.2.2 | 1.3 MB | | 0% \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "h5py-3.12.1 | 1.3 MB | | 0% \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "conda-25.1.1 | 1.1 MB | | 0% \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "hdf4-4.2.15 | 951 KB | | 0% \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "dask-core-2025.2.0 | 946 KB | | 0% \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "libarchive-3.7.4 | 851 KB | | 0% \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "libsqlite-3.46.0 | 845 KB | | 0% \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "libnetcdf-4.9.2 | 829 KB | | 0% 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"\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n", "Preparing transaction: done\n", "Verifying transaction: failed\n", "\n", "EnvironmentNotWritableError: The current user does not have write permissions to the target environment.\n", " environment location: /usr/licensed/anaconda3/2024.6\n", " uid: 227132\n", " gid: 30119\n", "\n", "\n", "\n", "Note: you may need to restart the kernel to use updated packages.\n" ] } ], "source": [ "conda install -c conda-forge xarray dask netCDF4 bottleneck" ] }, { "cell_type": "code", "execution_count": 1, "id": "tribal-memorabilia", "metadata": { "scrolled": true }, "outputs": [], "source": [ "# all code from Wenchang\n", "import numpy as np\n", "import sys\n", "wython = '/tigress/wenchang/wython'\n", "if wython not in sys.path:\n", " sys.path.append(wython)\n", "import xarray as xr\n", "# from xtc.plot import trackplot\n", "# from xtc.basins import tracks_in_basin\n", "# from geoplots import mapplot\n", "# import regionmask\n", "\n", "# not the right file...\n", "ifile = '/projects/GEOCLIM/gvecchi/DATA/HURDAT2/VERSION_2020/NETCDF_TRACKS/tracks_NA.nc'\n", "NA_tracks = xr.open_dataset(ifile)\n", "\n", "all_tracks = '/projects/w/wenchang/data/ibtracs/v04r00/analysis/v2/IBTrACS.ALL.v04r00.2022-01-25.tracksByYear.1980-2021.nc'\n", "global_tracks = xr.open_dataset(all_tracks)\n", "global_tracks\n", "\n", "OLR_79 = 'Daily OLR 1979.nc'\n", "OLR_1979 = xr.open_dataset(OLR_79)\n", "\n", "# from Wenchang \n", "NA_tracks\n", "# only consider years between 1980 and 2019\n", "dwind24 = NA_tracks.WIND - NA_tracks.WIND.shift(XCOUNT = 4)\n", "isRI = dwind24 > 15.555555555\n", "\n", "\n", "monthRI = NA_tracks.MONTH.where(isRI).values\n", "dayRI = NA_tracks.DAY.where(isRI).values\n", "yearRI = NA_tracks.YEAR.where(isRI).values\n", "#hourRI = NA_tracks.HOUR.where(isRI)\n", "\n", "monthRI_num = monthRI[~np.isnan(monthRI)]\n", "monthRI_num\n", "\n", "dayRI_num = dayRI[~np.isnan(dayRI)]\n", "\n", "yearRI_num = yearRI[~np.isnan(yearRI)]\n", "#yearRI_num\n", "#month_storm_GoM = month_storm_GoM[~np.isnan(month_storm_GoM)]\n", "\n", "#need to remove all years before 1980 for dayRI_num, monthRI_num, yearRI_num\n", "\n" ] }, { "cell_type": "code", "execution_count": 2, "id": "be0890b7-2efa-4f70-a732-bae7bcb53c81", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "2023.6.0\n" ] } ], "source": [ "print(xr.__version__)" ] }, { "cell_type": "code", "execution_count": 2, "id": "b7e5147f-b304-49bb-b85b-26414710f032", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Channels:\n", " - defaults\n", "Platform: linux-64\n", "Collecting package metadata (repodata.json): done\n", "Solving environment: done\n", "\n", "## Package Plan ##\n", "\n", " environment location: /usr/licensed/anaconda3/2024.6\n", "\n", " added / updated specs:\n", " - h5netcdf\n", " - netcdf4\n", "\n", "\n", "The following NEW packages will be INSTALLED:\n", "\n", " cftime pkgs/main/linux-64::cftime-1.6.4-py312h5eee18b_0 \n", " h5netcdf pkgs/main/linux-64::h5netcdf-1.2.0-py312h06a4308_0 \n", " hdf4 pkgs/main/linux-64::hdf4-4.2.13-h3ca952b_2 \n", " libnetcdf pkgs/main/linux-64::libnetcdf-4.8.1-h14805e7_4 \n", " libzip pkgs/main/linux-64::libzip-1.8.0-h6ac8c49_1 \n", " netcdf4 pkgs/main/linux-64::netcdf4-1.6.2-py312h33ae428_0 \n", "\n", "The following packages will be UPDATED:\n", "\n", " ca-certificates 2024.3.11-h06a4308_0 --> 2024.12.31-h06a4308_0 \n", " certifi 2024.6.2-py312h06a4308_0 --> 2025.1.31-py312h06a4308_0 \n", " conda 24.5.0-py312h06a4308_0 --> 24.11.3-py312h06a4308_0 \n", " openssl 3.0.14-h5eee18b_0 --> 3.0.15-h5eee18b_0 \n", "\n", "\n", "\n", "Downloading and Extracting Packages:\n", "\n", "Preparing transaction: done\n", "Verifying transaction: failed\n", "\n", "EnvironmentNotWritableError: The current user does not have write permissions to the target environment.\n", " environment location: /usr/licensed/anaconda3/2024.6\n", " uid: 227132\n", " gid: 30119\n", "\n", "\n", "\n", "Note: you may need to restart the kernel to use updated packages.\n" ] } ], "source": [] }, { "cell_type": "code", "execution_count": 3, "id": "3eeae888-f834-4322-8caa-ff40454c6a64", "metadata": {}, "outputs": [], "source": [ "import sys\n", "wython = '/tigress/wenchang/wython'\n", "if wython not in sys.path: sys.path.append(wython)" ] }, { "cell_type": "code", "execution_count": 7, "id": "098a4348-8bda-4f29-90ef-b9be96650a56", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "There are some problems for the deprecated basemap package.\n" ] } ], "source": [ "from misc.seasons import sel_season\n", "from geoplots import mapplot" ] }, { "cell_type": "code", "execution_count": 10, "id": "700b0895-aac0-4f61-aab8-f48fd8202c6a", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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<xarray.DataArray (latitude: 721, longitude: 1440)> Size: 8MB\n",
       "dask.array<mean_agg-aggregate, shape=(721, 1440), dtype=float64, chunksize=(721, 1440), chunktype=numpy.ndarray>\n",
       "Coordinates:\n",
       "  * longitude  (longitude) float32 6kB 0.0 0.25 0.5 0.75 ... 359.2 359.5 359.8\n",
       "  * latitude   (latitude) float32 3kB 90.0 89.75 89.5 ... -89.5 -89.75 -90.0
" ], "text/plain": [ " Size: 8MB\n", "dask.array\n", "Coordinates:\n", " * longitude (longitude) float32 6kB 0.0 0.25 0.5 0.75 ... 359.2 359.5 359.8\n", " * latitude (latitude) float32 3kB 90.0 89.75 89.5 ... -89.5 -89.75 -90.0" ] }, "execution_count": 10, "metadata": {}, "output_type": "execute_result" } ], "source": [ "import os \n", "os.chdir('/projects/w/wenchang/data/era5/analysis_wy/plevels')\n", "\n", "zonal_wind_shear_200 = xr.open_mfdataset('u200/daily/era5.u200.daily.*.nc', combine = 'nested', concat_dim = \"time\")['u']\n", "\n", "zonal_wind_shear_850 = xr.open_mfdataset('u850/daily/era5.u850.daily.*.nc', combine = 'nested', concat_dim = \"time\")['u']\n", "#zonal_wind_shear_850\n", "\n", "meridional_wind_shear_200 = xr.open_mfdataset('v200/daily/era5.v200.daily.*.nc', combine = 'nested', concat_dim = \"time\")['v']\n", "#meridional_wind_shear_200\n", "\n", "meridional_wind_shear_850 = xr.open_mfdataset('v850/daily/era5.v850.daily.*.nc', combine = 'nested', concat_dim = \"time\")['v']\n", "#meridional_wind_shear_850\n", "\n", "V_shear = np.sqrt((zonal_wind_shear_200 - zonal_wind_shear_850)**2 + (meridional_wind_shear_200 - meridional_wind_shear_850)**2)\n", "mean = V_shear.mean('time')\n", "mean" ] }, { "cell_type": "code", "execution_count": null, "id": "40e355ed-0db7-4baf-8d9c-aa0e84413f6e", "metadata": {}, "outputs": [], "source": [ "mean.to_dataset(name='vshear_mean').to_netcdf('vshear_mean.nc')" ] }, { "cell_type": "code", "execution_count": null, "id": "fd6ff4d5-0430-467b-9b53-298a3c7e4698", "metadata": {}, "outputs": [], "source": [ "da = xr.open_dataarray('vshear_mean.nc')#equivelant to ds = xr.open_dataset('vshear_mean.nc')['vshear_mean']" ] }, { "cell_type": "code", "execution_count": 18, "id": "00911d60-51c2-496d-afd0-a7588b9e1587", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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<xarray.Dataset> Size: 64GB\n",
       "Dimensions:    (time: 15341, latitude: 721, longitude: 1440)\n",
       "Coordinates:\n",
       "  * time       (time) datetime64[ns] 123kB 1979-01-01 1979-01-02 ... 2020-12-31\n",
       "  * longitude  (longitude) float32 6kB 0.0 0.25 0.5 0.75 ... 359.2 359.5 359.8\n",
       "  * latitude   (latitude) float32 3kB 90.0 89.75 89.5 ... -89.5 -89.75 -90.0\n",
       "Data variables:\n",
       "    u          (time, latitude, longitude) float32 64GB dask.array<chunksize=(1, 721, 1440), meta=np.ndarray>
" ], "text/plain": [ " Size: 64GB\n", "Dimensions: (time: 15341, latitude: 721, longitude: 1440)\n", "Coordinates:\n", " * time (time) datetime64[ns] 123kB 1979-01-01 1979-01-02 ... 2020-12-31\n", " * longitude (longitude) float32 6kB 0.0 0.25 0.5 0.75 ... 359.2 359.5 359.8\n", " * latitude (latitude) float32 3kB 90.0 89.75 89.5 ... -89.5 -89.75 -90.0\n", "Data variables:\n", " u (time, latitude, longitude) float32 64GB dask.array" ] }, "execution_count": 18, "metadata": {}, "output_type": "execute_result" } ], "source": [ "\n" ] }, { "cell_type": "code", "execution_count": 16, "id": "8f2812c8-2d2c-4176-9fe1-e631338a2f5d", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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<xarray.Dataset> Size: 127GB\n",
       "Dimensions:    (time: 15341, latitude: 721, longitude: 1440)\n",
       "Coordinates:\n",
       "  * longitude  (longitude) float32 6kB 0.0 0.25 0.5 0.75 ... 359.2 359.5 359.8\n",
       "  * latitude   (latitude) float32 3kB 90.0 89.75 89.5 ... -89.5 -89.75 -90.0\n",
       "  * time       (time) datetime64[ns] 123kB 1979-01-01 1979-01-02 ... 2020-12-31\n",
       "Data variables:\n",
       "    v          (time, latitude, longitude) float64 127GB dask.array<chunksize=(1, 721, 1440), meta=np.ndarray>
" ], "text/plain": [ " Size: 127GB\n", "Dimensions: (time: 15341, latitude: 721, longitude: 1440)\n", "Coordinates:\n", " * longitude (longitude) float32 6kB 0.0 0.25 0.5 0.75 ... 359.2 359.5 359.8\n", " * latitude (latitude) float32 3kB 90.0 89.75 89.5 ... -89.5 -89.75 -90.0\n", " * time (time) datetime64[ns] 123kB 1979-01-01 1979-01-02 ... 2020-12-31\n", "Data variables:\n", " v (time, latitude, longitude) float64 127GB dask.array" ] }, "execution_count": 16, "metadata": {}, "output_type": "execute_result" } ], "source": [] }, { "cell_type": "code", "execution_count": 2, "id": "4bb01227-293d-4597-a568-0d3aeb7952a2", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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<xarray.DataArray 'olr' (time: 365, lat: 180, lon: 360)> Size: 95MB\n",
       "[23652000 values with dtype=float32]\n",
       "Coordinates:\n",
       "  * lon      (lon) float32 1kB 0.5 1.5 2.5 3.5 4.5 ... 356.5 357.5 358.5 359.5\n",
       "  * lat      (lat) float32 720B -89.5 -88.5 -87.5 -86.5 ... 86.5 87.5 88.5 89.5\n",
       "  * time     (time) datetime64[ns] 3kB 1979-01-01T12:00:00 ... 1979-12-31T12:...\n",
       "Attributes:\n",
       "    long_name:      NOAA Climate Data Record of Daily Mean Upward Longwave Fl...\n",
       "    standard_name:  toa_outgoing_longwave_flux\n",
       "    units:          W m-2\n",
       "    cell_methods:   time: mean area: mean\n",
       "    valid_min:      50.0\n",
       "    valid_max:      500.0
" ], "text/plain": [ " Size: 95MB\n", "[23652000 values with dtype=float32]\n", "Coordinates:\n", " * lon (lon) float32 1kB 0.5 1.5 2.5 3.5 4.5 ... 356.5 357.5 358.5 359.5\n", " * lat (lat) float32 720B -89.5 -88.5 -87.5 -86.5 ... 86.5 87.5 88.5 89.5\n", " * time (time) datetime64[ns] 3kB 1979-01-01T12:00:00 ... 1979-12-31T12:...\n", "Attributes:\n", " long_name: NOAA Climate Data Record of Daily Mean Upward Longwave Fl...\n", " standard_name: toa_outgoing_longwave_flux\n", " units: W m-2\n", " cell_methods: time: mean area: mean\n", " valid_min: 50.0\n", " valid_max: 500.0" ] }, "execution_count": 2, "metadata": {}, "output_type": "execute_result" } ], "source": [ "OLR_data_79 = OLR_1979['olr']\n", "OLR_data_79\n", "\n", "# plt.plot(OLR_data_79)\n", "\n", "# OLR_lat_79 = OLR_1979['lat']\n", "# OLR_lon_79 = OLR_1979['lon']\n", "\n", "# import matplotlib.pyplot as plt\n", "\n", "OLR_data_79\n", "# # # plt.plot(OLR_lon_79, OLR_lat_79)\n", "\n", "# # xs, ys = np.meshgrid(OLR_lon_79, OLR_lat_79)\n", "\n", "# # dataMesh = np.empty_like(xs)\n", "\n", "\n", "# for i, j, k in zip(OLR_lon_79, OLR_lat_79, OLR_data_79):\n", "# dataMesh[OLR_lon_79[i], OLR_lat_79[j]] = k\n", "\n", "# map = Basemap(llcrnrlon = 0, llcrnrlat = -90, urcrnrlon = 360, urcrnrlat = 90, resolution = 'i')\n", "# CS = map.contour(xs, ys, dataMesh)\n", "# map.drawstates()\n", "# plot.show()\n" ] }, { "cell_type": "code", "execution_count": 4, "id": "8662178a-666c-433a-b0ac-fa1c870d002c", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 4, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "OLR_1979.olr.mean('time').plot()\n" ] }, { "cell_type": "code", "execution_count": 9, "id": "d4320b86-689c-464d-8afe-fcd70aecfee0", "metadata": {}, "outputs": [], "source": [ "da = OLR_1979.olr" ] }, { "cell_type": "code", "execution_count": 15, "id": "0442e76f-6b2a-47d0-8c13-bb9977c4deb6", "metadata": {}, "outputs": [ { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "da.pipe(sel_season, 'JJA').mean('time').plot()\n", "mapplot()" ] }, { "cell_type": "code", "execution_count": 4, "id": "17da78b1-0221-41d8-b65e-4351d2a770d3", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "['Daily OLR 1979.nc',\n", " 'Daily OLR 1980.nc',\n", " 'Daily OLR 1981.nc',\n", " 'Daily OLR 1982.nc',\n", " 'Daily OLR 1983.nc',\n", " 'Daily OLR 1984.nc',\n", " 'Daily OLR 1985.nc',\n", " 'Daily OLR 1986.nc',\n", " 'Daily OLR 1987.nc',\n", " 'Daily OLR 1988.nc',\n", " 'Daily OLR 1989.nc',\n", " 'Daily OLR 1990.nc',\n", " 'Daily OLR 1991.nc',\n", " 'Daily OLR 1992.nc',\n", " 'Daily OLR 1993.nc',\n", " 'Daily OLR 1994.nc',\n", " 'Daily OLR 1995.nc',\n", " 'Daily OLR 1996.nc',\n", " 'Daily OLR 1997.nc',\n", " 'Daily OLR 1998.nc',\n", " 'Daily OLR 1999.nc',\n", " 'Daily OLR 2000.nc',\n", " 'Daily OLR 2001.nc',\n", " 'Daily OLR 2002.nc',\n", " 'Daily OLR 2003.nc',\n", " 'Daily OLR 2004.nc',\n", " 'Daily OLR 2005.nc',\n", " 'Daily OLR 2006.nc',\n", " 'Daily OLR 2007.nc',\n", " 'Daily OLR 2008.nc',\n", " 'Daily OLR 2009.nc',\n", " 'Daily OLR 2010.nc',\n", " 'Daily OLR 2011.nc',\n", " 'Daily OLR 2012.nc',\n", " 'Daily OLR 2013.nc',\n", " 'Daily OLR 2014.nc',\n", " 'Daily OLR 2015.nc',\n", " 'Daily OLR 2016.nc',\n", " 'Daily OLR 2017.nc',\n", " 'Daily OLR 2018.nc',\n", " 'Daily OLR 2019.nc',\n", " 'Daily OLR 2020.nc',\n", " 'Daily OLR 2021.nc',\n", " 'Daily OLR 2022.nc',\n", " 'Daily OLR 2023.nc']" ] }, "execution_count": 4, "metadata": {}, "output_type": "execute_result" } ], "source": [ "ifiles = [f'Daily OLR {year}.nc' for year in range(1979,2024)]\n", "ifiles" ] }, { "cell_type": "code", "execution_count": 5, "id": "07ac2d72-2392-4976-9ce4-bb1952896df9", "metadata": {}, "outputs": [], "source": [ "ds = xr.open_mfdataset(ifiles)" ] }, { "cell_type": "code", "execution_count": 6, "id": "5927bb1b-f2df-46da-ba40-34319614c24d", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "
<xarray.Dataset> Size: 4GB\n",
       "Dimensions:      (time: 16436, lat: 180, lon: 360, bnds: 2)\n",
       "Coordinates:\n",
       "  * lon          (lon) float32 1kB 0.5 1.5 2.5 3.5 ... 356.5 357.5 358.5 359.5\n",
       "  * lat          (lat) float32 720B -89.5 -88.5 -87.5 -86.5 ... 87.5 88.5 89.5\n",
       "  * time         (time) datetime64[ns] 131kB 1979-01-01T12:00:00 ... 2023-12-...\n",
       "Dimensions without coordinates: bnds\n",
       "Data variables:\n",
       "    olr          (time, lat, lon) float32 4GB dask.array<chunksize=(365, 180, 360), meta=np.ndarray>\n",
       "    lon_bounds   (time, lon, bnds) float32 47MB dask.array<chunksize=(365, 360, 2), meta=np.ndarray>\n",
       "    lat_bounds   (time, lat, bnds) float32 24MB dask.array<chunksize=(365, 180, 2), meta=np.ndarray>\n",
       "    time_bounds  (time, bnds) datetime64[ns] 263kB dask.array<chunksize=(365, 2), meta=np.ndarray>\n",
       "Attributes: (12/46)\n",
       "    conventions:                CF-1.6\n",
       "    title:                      Daily OLR CDR Product Ver01Rev02\n",
       "    source:                     NOAA Archive of HIRS L1B data from TIROS-N Se...\n",
       "    reference:                  doi:10.1175/2007JTECHA989.1  doi:10.1175/1520...\n",
       "    history:                    2014-06-10T18:57:59Z - generated by software ...\n",
       "    comment:                    Final TCDR\n",
       "    ...                         ...\n",
       "    software_version_id:        Ver01Rev02\n",
       "    Metadata_Link:              gov.noaa.ncdc:C00875\n",
       "    product_version:            Ver01Rev02\n",
       "    platform:                   TIROS-N > Television Infrared Observation Sat...\n",
       "    sensor:                     HIRS-2 > High Resolution Infra-red Sounder/2,...\n",
       "    spatial_resolution:         1.0 by 1.0 degree equal angle
" ], "text/plain": [ " Size: 4GB\n", "Dimensions: (time: 16436, lat: 180, lon: 360, bnds: 2)\n", "Coordinates:\n", " * lon (lon) float32 1kB 0.5 1.5 2.5 3.5 ... 356.5 357.5 358.5 359.5\n", " * lat (lat) float32 720B -89.5 -88.5 -87.5 -86.5 ... 87.5 88.5 89.5\n", " * time (time) datetime64[ns] 131kB 1979-01-01T12:00:00 ... 2023-12-...\n", "Dimensions without coordinates: bnds\n", "Data variables:\n", " olr (time, lat, lon) float32 4GB dask.array\n", " lon_bounds (time, lon, bnds) float32 47MB dask.array\n", " lat_bounds (time, lat, bnds) float32 24MB dask.array\n", " time_bounds (time, bnds) datetime64[ns] 263kB dask.array\n", "Attributes: (12/46)\n", " conventions: CF-1.6\n", " title: Daily OLR CDR Product Ver01Rev02\n", " source: NOAA Archive of HIRS L1B data from TIROS-N Se...\n", " reference: doi:10.1175/2007JTECHA989.1 doi:10.1175/1520...\n", " history: 2014-06-10T18:57:59Z - generated by software ...\n", " comment: Final TCDR\n", " ... ...\n", " software_version_id: Ver01Rev02\n", " Metadata_Link: gov.noaa.ncdc:C00875\n", " product_version: Ver01Rev02\n", " platform: TIROS-N > Television Infrared Observation Sat...\n", " sensor: HIRS-2 > High Resolution Infra-red Sounder/2,...\n", " spatial_resolution: 1.0 by 1.0 degree equal angle" ] }, "execution_count": 6, "metadata": {}, "output_type": "execute_result" } ], "source": [ "ds" ] }, { "cell_type": "code", "execution_count": 7, "id": "52679789-66f8-4746-9eb4-52c2c1bfda3b", "metadata": {}, "outputs": [], "source": [ "da = ds.olr" ] }, { "cell_type": "code", "execution_count": 24, "id": "b255f333-5bd3-4567-9bdc-b63f4911ae89", "metadata": {}, "outputs": [ { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "da.sel(time='1980').mean('time').plot(); mapplot()" ] }, { "cell_type": "code", "execution_count": 8, "id": "ead1c52f-09a7-49a7-94a5-9cbd664eb0bd", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "Text(0.5, 1.0, 'Time-Averaged OLR for June-November, 1979-2023')" ] }, "execution_count": 8, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# time-averaged OLR for June-November, 1979-2023\n", "import matplotlib.pyplot as plt\n", "da.pipe(sel_season, 'JJASON').mean('time').plot(); mapplot()\n", "plt.title('Time-Averaged OLR for June-November, 1979-2023')" ] }, { "cell_type": "code", "execution_count": 18, "id": "56b9b022-04c2-4957-8665-8fa336bf9ab4", "metadata": {}, "outputs": [], "source": [ "# all days when MJO phase is 1\n", "from datetime import datetime, timedelta \n", "import time\n", "\n", "def MJO_phase_date(df):\n", " list_dates = []\n", " MJO_phase_yr_list = df['year'].tolist() \n", " MJO_phase_month_list = df['month'].tolist()\n", " MJO_phase_day_list = df['day'].tolist() \n", " for i in range(len(MJO_phase_yr_list)):\n", " date = (str(MJO_phase_yr_list[i]) + str(MJO_phase_month_list[i]) + str(MJO_phase_day_list[i]))\n", " if (len(date) == 6):\n", " # both month and day are only 1 digit\n", " date_format = datetime(year = int(date[0:4]), month = int(date[4:5]), day = int(date[5:6]), hour = 00)\n", " elif (len(date) == 7): \n", " # either month is 2 digits and day is 1 or day is 2 digits and month is 1\n", " # if month is 2 digits and day is 1 digit\n", " if (int(date[4:6]) == 10 or int(date[4:6]) == 11): \n", " date_format = datetime(year = int(date[0:4]), month = int(date[4:6]), day = int(date[6:7]), hour = 00)\n", " # # if the month is 1 digit and the day is 2\n", " else: \n", " date_format = datetime(year = int(date[0:4]), month = int(date[4:5]), day = int(date[5:7]), hour = 00)\n", " \n", " else:\n", " date_format = datetime(year = int(date[0:4]), month = int(date[4:6]), day = int(date[6:8]), hour = 00)\n", "\n", " string_format = date_format.strftime(\"%Y-%m-%dT%H:%M:%S\")\n", " list_dates.append(string_format)\n", " return (list_dates)\n" ] }, { "cell_type": "code", "execution_count": 17, "id": "e24a3abb-1c78-4162-92f2-6536cd672f5a", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "433" ] }, "execution_count": 17, "metadata": {}, "output_type": "execute_result" } ], "source": [] }, { "cell_type": "code", "execution_count": null, "id": "8fc89f68-ccf6-42e0-8ca2-628f620cebdc", "metadata": {}, "outputs": [], "source": [ "V_shear_phase8 = V_shear.sel(time = ['1979-07-07T00:00:00',\n", " '1979-07-08T00:00:00',\n", " '1979-07-09T00:00:00',\n", " '1979-07-10T00:00:00',\n", " '1979-07-11T00:00:00',\n", " '1979-07-15T00:00:00',\n", " '1979-07-17T00:00:00',\n", " '1979-07-18T00:00:00',\n", " '1979-08-18T00:00:00',\n", " '1979-08-19T00:00:00',\n", " '1979-08-20T00:00:00',\n", " '1979-08-21T00:00:00',\n", " '1979-10-18T00:00:00',\n", " '1979-10-19T00:00:00',\n", " '1979-10-20T00:00:00',\n", " '1979-10-21T00:00:00',\n", " '1979-10-22T00:00:00',\n", " '1981-10-04T00:00:00',\n", " '1981-10-05T00:00:00',\n", " '1981-10-06T00:00:00',\n", " '1982-07-24T00:00:00',\n", " '1982-07-25T00:00:00',\n", " '1982-11-17T00:00:00',\n", " '1982-11-18T00:00:00',\n", " '1982-11-19T00:00:00',\n", " '1982-11-20T00:00:00',\n", " '1982-11-21T00:00:00',\n", " '1984-07-06T00:00:00',\n", " '1984-07-07T00:00:00',\n", " '1984-09-08T00:00:00',\n", " '1984-09-09T00:00:00',\n", " '1984-09-10T00:00:00',\n", " '1984-09-11T00:00:00',\n", " '1984-09-12T00:00:00',\n", " '1984-09-13T00:00:00',\n", " '1984-09-17T00:00:00',\n", " '1984-09-18T00:00:00',\n", " '1984-09-19T00:00:00',\n", " '1984-09-20T00:00:00',\n", " '1984-09-21T00:00:00',\n", " '1984-10-24T00:00:00',\n", " '1984-10-27T00:00:00',\n", " '1984-10-28T00:00:00',\n", " '1984-10-29T00:00:00',\n", " '1984-10-30T00:00:00',\n", " '1984-10-31T00:00:00',\n", " '1985-09-21T00:00:00',\n", " '1985-09-22T00:00:00',\n", " '1985-09-23T00:00:00',\n", " '1985-09-24T00:00:00',\n", " '1985-10-23T00:00:00',\n", " '1985-10-24T00:00:00',\n", " '1985-10-25T00:00:00',\n", " '1985-10-26T00:00:00',\n", " '1985-10-27T00:00:00',\n", " '1985-10-28T00:00:00',\n", " '1985-10-29T00:00:00',\n", " '1986-07-05T00:00:00',\n", " '1986-09-23T00:00:00',\n", " 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"V_shear_phase8\n", "\n", "phase8_anomaly = (V_shear_phase8.mean('time') - V_shear.mean('time'))\n", "phase8_anomaly.plot" ] }, { "cell_type": "code", "execution_count": 27, "id": "e5805aef-6255-4225-a8c5-6ecea4006b20", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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<xarray.Dataset> Size: 12kB\n",
       "Dimensions:    (longitude: 1440, latitude: 721, time: 366)\n",
       "Coordinates:\n",
       "  * longitude  (longitude) float32 6kB 0.0 0.25 0.5 0.75 ... 359.2 359.5 359.8\n",
       "  * latitude   (latitude) float32 3kB 90.0 89.75 89.5 ... -89.5 -89.75 -90.0\n",
       "  * time       (time) datetime64[ns] 3kB 1979-07-06 1979-08-12 ... 2020-10-31\n",
       "Data variables:\n",
       "    *empty*
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<xarray.Dataset> Size: 13kB\n",
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<xarray.Dataset> Size: 14kB\n",
       "Dimensions:    (longitude: 1440, latitude: 721, time: 682)\n",
       "Coordinates:\n",
       "  * longitude  (longitude) float32 6kB 0.0 0.25 0.5 0.75 ... 359.2 359.5 359.8\n",
       "  * latitude   (latitude) float32 3kB 90.0 89.75 89.5 ... -89.5 -89.75 -90.0\n",
       "  * time       (time) datetime64[ns] 5kB 1979-06-24 1979-06-26 ... 2020-10-25\n",
       "Data variables:\n",
       "    *empty*
" ], "text/plain": [ " Size: 14kB\n", "Dimensions: (longitude: 1440, latitude: 721, time: 682)\n", "Coordinates:\n", " * longitude (longitude) float32 6kB 0.0 0.25 0.5 0.75 ... 359.2 359.5 359.8\n", " * latitude (latitude) float32 3kB 90.0 89.75 89.5 ... -89.5 -89.75 -90.0\n", " * time (time) datetime64[ns] 5kB 1979-06-24 1979-06-26 ... 2020-10-25\n", "Data variables:\n", " *empty*" ] }, "execution_count": 25, "metadata": {}, "output_type": "execute_result" } ], "source": [ "V_shear_phase5 = V_shear.sel(time = ['1979-06-24T00:00:00',\n", " '1979-06-26T00:00:00',\n", " '1979-06-27T00:00:00',\n", " '1979-07-30T00:00:00',\n", " '1979-07-31T00:00:00',\n", " '1979-08-01T00:00:00',\n", " '1979-08-02T00:00:00',\n", " '1979-08-03T00:00:00',\n", " '1979-08-04T00:00:00',\n", " '1979-08-05T00:00:00',\n", " '1979-08-06T00:00:00',\n", " '1979-08-07T00:00:00',\n", " '1979-09-26T00:00:00',\n", " '1979-09-27T00:00:00',\n", " '1979-09-28T00:00:00',\n", " '1979-09-29T00:00:00',\n", " 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<xarray.Dataset> Size: 13kB\n",
       "Dimensions:    (longitude: 1440, latitude: 721, time: 516)\n",
       "Coordinates:\n",
       "  * longitude  (longitude) float32 6kB 0.0 0.25 0.5 0.75 ... 359.2 359.5 359.8\n",
       "  * latitude   (latitude) float32 3kB 90.0 89.75 89.5 ... -89.5 -89.75 -90.0\n",
       "  * time       (time) datetime64[ns] 4kB 1979-06-20 1979-06-21 ... 2020-11-27\n",
       "Data variables:\n",
       "    *empty*
" ], "text/plain": [ " Size: 13kB\n", "Dimensions: (longitude: 1440, latitude: 721, time: 516)\n", "Coordinates:\n", " * longitude (longitude) float32 6kB 0.0 0.25 0.5 0.75 ... 359.2 359.5 359.8\n", " * latitude (latitude) float32 3kB 90.0 89.75 89.5 ... -89.5 -89.75 -90.0\n", " * time (time) datetime64[ns] 4kB 1979-06-20 1979-06-21 ... 2020-11-27\n", "Data variables:\n", " *empty*" ] }, "execution_count": 24, "metadata": {}, "output_type": "execute_result" } ], "source": [ "V_shear_phase4 = V_shear.sel(time = ['1979-06-20T00:00:00',\n", " '1979-06-21T00:00:00',\n", " '1979-06-22T00:00:00',\n", " '1979-06-23T00:00:00',\n", " '1979-06-25T00:00:00',\n", " '1979-09-22T00:00:00',\n", " '1979-09-23T00:00:00',\n", " '1979-09-24T00:00:00',\n", " '1979-09-25T00:00:00',\n", " '1979-11-26T00:00:00',\n", " '1979-11-27T00:00:00',\n", " '1979-11-28T00:00:00',\n", " '1979-11-29T00:00:00',\n", " '1980-07-02T00:00:00',\n", " '1980-08-21T00:00:00',\n", " '1980-08-22T00:00:00',\n", " 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<xarray.Dataset> Size: 12kB\n",
       "Dimensions:    (longitude: 1440, latitude: 721, time: 447)\n",
       "Coordinates:\n",
       "  * longitude  (longitude) float32 6kB 0.0 0.25 0.5 0.75 ... 359.2 359.5 359.8\n",
       "  * latitude   (latitude) float32 3kB 90.0 89.75 89.5 ... -89.5 -89.75 -90.0\n",
       "  * time       (time) datetime64[ns] 4kB 1979-06-15 1979-06-16 ... 2020-11-22\n",
       "Data variables:\n",
       "    *empty*
" ], "text/plain": [ " Size: 12kB\n", "Dimensions: (longitude: 1440, latitude: 721, time: 447)\n", "Coordinates:\n", " * longitude (longitude) float32 6kB 0.0 0.25 0.5 0.75 ... 359.2 359.5 359.8\n", " * latitude (latitude) float32 3kB 90.0 89.75 89.5 ... -89.5 -89.75 -90.0\n", " * time (time) datetime64[ns] 4kB 1979-06-15 1979-06-16 ... 2020-11-22\n", "Data variables:\n", " *empty*" ] }, "execution_count": 23, "metadata": {}, "output_type": "execute_result" } ], "source": [ "V_shear_phase3 = V_shear.sel(time = ['1979-06-15T00:00:00',\n", " '1979-06-16T00:00:00',\n", " '1979-06-17T00:00:00',\n", " '1979-06-18T00:00:00',\n", " '1979-06-19T00:00:00',\n", " '1979-09-19T00:00:00',\n", " '1979-09-20T00:00:00',\n", " '1979-09-21T00:00:00',\n", " '1979-11-05T00:00:00',\n", " '1979-11-10T00:00:00',\n", " '1979-11-17T00:00:00',\n", " '1979-11-18T00:00:00',\n", " '1979-11-19T00:00:00',\n", " '1979-11-20T00:00:00',\n", " '1979-11-21T00:00:00',\n", " '1979-11-22T00:00:00',\n", " 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<xarray.Dataset> Size: 14kB\n",
       "Dimensions:    (longitude: 1440, latitude: 721, time: 709)\n",
       "Coordinates:\n",
       "  * longitude  (longitude) float32 6kB 0.0 0.25 0.5 0.75 ... 359.2 359.5 359.8\n",
       "  * latitude   (latitude) float32 3kB 90.0 89.75 89.5 ... -89.5 -89.75 -90.0\n",
       "  * time       (time) datetime64[ns] 6kB 1979-06-07 1979-06-08 ... 2020-11-20\n",
       "Data variables:\n",
       "    *empty*
" ], "text/plain": [ " Size: 14kB\n", "Dimensions: (longitude: 1440, latitude: 721, time: 709)\n", "Coordinates:\n", " * longitude (longitude) float32 6kB 0.0 0.25 0.5 0.75 ... 359.2 359.5 359.8\n", " * latitude (latitude) float32 3kB 90.0 89.75 89.5 ... -89.5 -89.75 -90.0\n", " * time (time) datetime64[ns] 6kB 1979-06-07 1979-06-08 ... 2020-11-20\n", "Data variables:\n", " *empty*" ] }, "execution_count": 29, "metadata": {}, "output_type": "execute_result" } ], "source": [ "\n", "V_shear_phase2 = V_shear.sel(time = ['1979-06-07T00:00:00',\n", " '1979-06-08T00:00:00',\n", " '1979-06-09T00:00:00',\n", " '1979-06-10T00:00:00',\n", " '1979-06-11T00:00:00',\n", " '1979-06-12T00:00:00',\n", " '1979-06-13T00:00:00',\n", " '1979-06-14T00:00:00',\n", " '1979-09-08T00:00:00',\n", " '1979-09-09T00:00:00',\n", " '1979-09-12T00:00:00',\n", " '1979-09-16T00:00:00',\n", " '1979-09-17T00:00:00',\n", " '1979-09-18T00:00:00',\n", " '1979-10-31T00:00:00',\n", " '1979-11-01T00:00:00',\n", " 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'2020-07-23T00:00:00',\n", " '2020-07-24T00:00:00',\n", " '2020-07-25T00:00:00',\n", " '2020-07-26T00:00:00',\n", " '2020-08-28T00:00:00',\n", " '2020-08-29T00:00:00',\n", " '2020-08-30T00:00:00',\n", " '2020-11-15T00:00:00',\n", " '2020-11-16T00:00:00',\n", " '2020-11-17T00:00:00',\n", " '2020-11-18T00:00:00',\n", " '2020-11-19T00:00:00',\n", " '2020-11-20T00:00:00'])\n", "\n", "V_shear_phase2" ] }, { "cell_type": "code", "execution_count": 20, "id": "33f493bb-5358-4385-8803-faa0e8df8856", "metadata": {}, "outputs": [], "source": [ "# first - do MJO phase anomaly only considering MJO phase days that occurred between June 1 and November 30\n", "\n", "import datetime\n", "V_shear_phase1 = V_shear.sel(time = ['1979-06-01T00:00:00',\n", " '1979-06-02T00:00:00',\n", " '1979-06-03T00:00:00',\n", " '1979-06-04T00:00:00',\n", " '1979-06-05T00:00:00',\n", " '1979-06-06T00:00:00',\n", " '1979-07-12T00:00:00',\n", " '1979-07-13T00:00:00',\n", " '1979-07-14T00:00:00',\n", " 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" * latitude (latitude) float32 3kB 90.0 89.75 89.5 ... -89.5 -89.75 -90.0\n", " * time (time) datetime64[ns] 123kB 1979-01-01 1979-01-02 ... 2020-12-31\n", "Data variables:\n", " *empty*>" ] }, "execution_count": 43, "metadata": {}, "output_type": "execute_result" } ], "source": [ "import matplotlib.pyplot as plt\n", "phase1_anomaly = \n" ] }, { "cell_type": "code", "execution_count": 137, "id": "satisfied-maintenance", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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level_0index\"yearmonthdayRMM1RMM2MJO phaseMJO amplitudemean have been removed in these RMMvalues; 20140101-: Only the 120-day has been removed.\",,,,,,,,,,,
89019883812NaN1984116-2.23457-0.8265600212.38254WH04_method:_OLR_&_NCEP_wind,,,,,,,,,,,
\n", "
" ], "text/plain": [ " level_0 index \" year month day RMM1 RMM2 MJO phase \\\n", "890 1988 3812 NaN 1984 11 6 -2.23457 -0.82656002 1 \n", "\n", " MJO amplitude mean have been removed in these RMM \\\n", "890 2.38254 WH04_method:_OLR_&_NCEP_wind \n", "\n", " values; 20140101-: Only the 120-day has been removed.\",,,,,,,,,,, \n", "890 ,,,,,,,,,,, " ] }, "execution_count": 137, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# need to change monthRI and dayRI back so that they only tag the RI events in the GoM and Caribbean \n", "# need to add back the .where(L) term\n", "\n", "# find numerator of normalized ACE for phases 1 + 2, phases 3 + 4, phases 5 + 6, phases 7 + 8 of WH index (first)\n", "# find all TCs that FORMED in phases 1 + 2, phases 3 + 4, phases 5 + 6, phases 7 + 8, and sum up the ACE generated by those TCs\n", "# Category: TCs that formed in MJO phases 1 + 2 \n", "\n", "# identify the MJO phase on the first day that each TC reached tropical storm strength \n", "\n", "\n", "\n", "\n" ] }, { "cell_type": "code", "execution_count": 89, "id": "vietnamese-annual", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "array([], dtype=float64)" ] }, "execution_count": 89, "metadata": {}, "output_type": "execute_result" } ], "source": [ "year = 2019\n", "#storm = 1\n", "\n", "wind = NA_tracks.WIND\n", "month = NA_tracks.MONTH\n", "day = NA_tracks.DAY\n", "tropical_storm = (wind >= 17)\n", "\n", "month_storm_GoM = month.where(isRI).where(L).sel(YRT=year).values.ravel()\n", "month_storm_GoM = month_storm_GoM[~np.isnan(month_storm_GoM)]\n", "month_storm_GoM\n" ] }, { "cell_type": "code", "execution_count": 90, "id": "dramatic-parking", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "array([], dtype=float64)" ] }, "execution_count": 90, "metadata": {}, "output_type": "execute_result" } ], "source": [ "day_storm_GoM = day.where(isRI).where(L).sel(YRT=year).values.ravel()\n", "day_storm_GoM = day_storm_GoM[~np.isnan(day_storm_GoM)]\n", "day_storm_GoM" ] }, { "cell_type": "markdown", "id": "c55e0b3f-802e-4b09-9866-60be83975c38", "metadata": {}, "source": [ "Check: RI days in the Gulf of Mexico and Caribbean\n", "\n", "1980 \n", "8/7 \n", "\n", "1981 \n", "11/5\n", "\n", "1982 \n", "6/3 \n", "6/4\n", "\n", "1985 \n", "8/15 \n", "8/29\n", "\n", "1988 \n", "9/2\n", "9/3 \n", "9/14\n", "10/21\n", "10/22\n", "\n", "1989\n", "8/1\n", "\n", "1990\n", "8/7\n", "\n", "1993 \n", "9/20\n", "\n", "1995 \n", "10/4\n", "10/10\n", "\n", "1997 \n", "7/18\n", "\n", "1998\n", "8/22\n", "9/2\n", "10/24\n", "10/25\n", "\n", "2000\n", "9/21 \n", "9/22 \n", "9/30 \n", "10/1\n", "10/5\n", "\n", "2001\n", "10/8\n", "10/9 \n", "11/3\n", "\n", "2002 \n", "9/20 \n", "9/21\n", "9/22 \n", "10/2\n", "\n", "2004 \n", "8/13\n", "\n", "2005 \n", "7/6\n", "7/8 \n", "7/10 \n", "7/16 \n", "7/20 \n", "8/28 \n", "8/29 \n", "9/21\n", "9/22\n", "10/19\n", "\n", "2007\n", "9/13 \n", "9/28\n", "\n", "2008 \n", "8/30\n", "8/31\n", "11/7 \n", "11/8\n", "\n", "2009\n", "11/5\n", "11/8\n", "\n", "2010\n", "9/17\n", "10/12\n", "\n", "2011\n", "10/24\n", "10/25\n", "\n", "2016 \n", "11/24\n", "\n", "2017 \n", "8/10 \n", "8/24\n", "8/25\n", "8/26\n", "9/6 \n", "9/7 \n", "10/7\n", "\n", "2018\n", "10/9 \n", "10/10\n", "\n", "2019\n" ] }, { "cell_type": "markdown", "id": "8048ec93-b5b9-486a-9693-44acd189080a", "metadata": {}, "source": [ "prob (TC forms | MJO phase x) = # TCs that formed during phase x / total # days in phase x in NA hurricane season\n", "GoM NOT ENTIRE NA\n", "Record what phase MJO was in on the first day that a storm reached 17 m/s while in the GoM / Caribbean\n", "\n", "1980 \n", "8/6\n", "9/5\n", "9/21\n", "11/9\n", "\n", "1981 \n", "8/16\n", "11/4\n", "\n", "1982 \n", "6/3\n", "6/18\n", "9/10\n", "\n", "1983\n", "8/15\n", "8/24\n", "\n", "1984 \n", "9/8\n", "9/14\n", "9/26\n", "\n", "1985 \n", "7/22\n", "8/14\n", "8/28\n", "10/10\n", "10/26\n", "11/19\n", "\n", "1986 \n", "6/6\n", "6/24\n", "\n", "1987\n", "8/9\n", "10/10\n", "\n", "1988\n", "8/8\n", "8/28\n", "9/2\n", "9/7\n", "9/13\n", "10/19\n", "11/20\n", "\n", "1989 \n", "6/26\n", "7/31\n", "9/21\n", "10/13\n", "11/30\n", "\n", "1990\n", "8/5\n", "10/10\n", "\n", "1991 \n", "10/15\n", "\n", "1992 \n", "8/24\n", "9/29\n", "\n", "1993 \n", "6/19\n", "8/10\n", "9/15\n", "\n", "1994\n", "7/2\n", "8/15\n", "11/10\n", "\n", "1995\n", "6/3\n", "7/30\n", "8/1\n", "8/10\n", "8/23\n", "9/30\n", "10/9\n", "\n", "1996 \n", "7/11\n", "7/27\n", "8/19\n", "10/6\n", "10/11\n", "10/16\n", "11/19\n", "\n", "1997 \n", "7/17\n", "\n", "1998 \n", "8/21\n", "8/31\n", "9/9\n", "9/24\n", "9/19\n", "10/22\n", "\n", "1999\n", "8/19\n", "9/15\n", "9/20\n", "10/13\n", "10/29\n", "11/14\n", "\n", "2000 \n", "8/14\n", "9/16\n", "9/21\n", "9/29\n", "\n", "2001\n", "6/5\n", "8/2\n", "8/19\n", "9/13\n", "10/7\n", "11/1\n", "\n", "2002 \n", "8/5\n", "9/2\n", "9/6\n", "9/12\n", "9/18\n", "10/11\n", "9/29\n", "\n", "2003\n", "6/29\n", "7/9\n", "8/14\n", "8/30\n", "9/5\n", "9/30\n", "\n", "2004\n", "8/9\n", "8/12\n", "9/4\n", "9/11\n", "9/25\n", "10/8\n", "\n", "2005\n", "6/9\n", "6/28\n", "7/5\n", "7/8\n", "7/16\n", "7/24\n", "8/22\n", "8/25\n", "9/7\n", "9/20\n", "10/2\n", "10/5\n", "10/17\n", "10/27\n", "11/18\n", "\n", "2006 \n", "6/11\n", "8/29\n", "\n", "2007 \n", "6/1\n", "8/20\n", "8/15\n", "9/3\n", "9/12\n", "9/27\n", "10/31\n", "\n", "2008 \n", "7/20\n", "8/4\n", "8/17\n", "8/29\n", "9/5\n", "9/8\n", "10/6\n", "11/6\n", "\n", "2009 \n", "8/16\n", "11/4\n", "\n", "2010 \n", "6/26\n", "7/23\n", "9/6\n", "9/14\n", "9/24\n", "9/28\n", "10/11\n", "10/21\n", "\n", "2011 \n", "6/28\n", "7/18\n", "7/27\n", "8/7\n", "8/19\n", "9/2\n", "9/7\n", "10/24\n", "\n", "2012 \n", "6/23\n", "8/5\n", "8/17\n", "8/26\n", "10/22\n", "\n", "2013 \n", "6/5\n", "6/19\n", "8/25\n", "9/13\n", "10/3\n", "\n", "2014\n", "7/1\n", "9/2\n", "10/27\n", "\n", "2015\n", "6/16\n", "\n", "2016\n", "6/5\n", "6/20\n", "8/2\n", "8/31\n", "9/13\n", "10/6\n", "11/21\n", "\n", "2017 \n", "6/19\n", "7/31\n", "8/7\n", "8/23\n", "9/9\n", "9/6\n", "10/5\n", "10/28\n", "\n", "2018\n", "9/3\n", "10/7\n", "\n", "2019 \n", "7/11\n", "9/2\n", "9/3\n", "9/15\n", "9/17\n", "10/17\n", "10/25" ] }, { "cell_type": "markdown", "id": "affected-yacht", "metadata": {}, "source": [ "\n" ] }, { "cell_type": "code", "execution_count": 13, "id": "radio-reggae", "metadata": {}, "outputs": [], "source": [ "\n", "\n", "phase_TCgen_GOM = [0, 5, 1, 0, 0, 4, 4, 0, 0, 4, 0, 8, 7, 0, 1, 0, 0, 0, 8, 6, 2, 6, 2, 0, 0, 1, 1, 0, 0, 6, 0, 0, 0, 2, 4, 8, 0, 1, 3, 0, 0, 8, 7, 0, \n", " 0, 0, 2, 0, 2, 2, 1, 0, 0, 7, 5, 6, 3, 1, 0, 0, 1, 4, 2, 8, 8, 4, 3, 0, 1, 0, 0, 1, 0, 4, 7, 0, 2, 2, 2, 2, 0, 6, 2, 5, 3, 3, 0, 0, \n", " 0, 0, 0, 0, 0, 2, 0, 0, 0, 4, 6, 6, 1, 2, 3, 5, 0, 0, 2, 0, 0, 0, 0, 0, 4, 7, 0, 1, 5, 4, 8, 1, 2, 1, 0, 0, 2, 5, 6, 0, 3, 0, 2, 2, \n", " 3, 4, 0, 0, 2, 2, 2, 3, 2, 0, 0, 0, 5, 0, 0, 0, 0, 0, 2, 0, 0, 2, 1, 0, 2, 3, 2, 0, 6, 8, 0, 5, 0, 4, 0, 4, 0, 4, 0, 0, 4, 5, 2, 1, \n", " 0, 0, 0, 0, 0, 0, 7, 0, 1, 1, 0, 5, 8, 8, 1, 3]\n", " " ] }, { "cell_type": "code", "execution_count": 15, "id": "3119d26e-f67f-435a-b50f-8ae74b248f06", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "0.023434639326254118" ] }, "execution_count": 15, "metadata": {}, "output_type": "execute_result" } ], "source": [ "val, count = np.unique(phase_TCgen_GOM, return_counts=True)\n", "val, count\n", "\n", "freq_0 = 84\n", "freq_1 = 19\n", "freq_2 = 28\n", "freq_3 = 11\n", "freq_4 = 15\n", "freq_5 = 10\n", "freq_6 = 9\n", "freq_7 = 6\n", "freq_8 = 10\n", "\n", "prob_0 = freq_0 / phase0\n", "prob_1 = freq_1 / phase1\n", "prob_2 = freq_2 / phase2\n", "prob_3 = freq_3 / phase3\n", "prob_4 = freq_4 / phase4\n", "prob_5 = freq_5 / phase5\n", "prob_6 = freq_6 / phase6\n", "prob_7 = freq_7 / phase7\n", "prob_8 = freq_8 / phase8\n", "\n", "TC_gen_nonzero_GoM = freq_1 + freq_2 + freq_3 + freq_4 + freq_5 + freq_6 + freq_7 + freq_8\n", "nonzero_MJO_days = phase1 + phase2 + phase3 + phase4 + phase5 + phase6 + phase7 + phase8\n", "prob_genesis_nonzero_GoM = TC_gen_nonzero_GoM / nonzero_MJO_days\n", "prob_genesis_nonzero_GoM\n", "\n", "TC_gen_all = TC_gen_nonzero_GoM + freq_0\n", "MJO_days_all = nonzero_MJO_days + phase0\n", "prob_TC_gen_GoM = TC_gen_all / MJO_days_all\n", "prob_TC_gen_GoM" ] }, { "cell_type": "code", "execution_count": 227, "id": "3d71f6f4-b6cb-44f1-85d9-4dcd2e9c310a", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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level_0index\"yearmonthdayRMM1RMM2MJO phaseMJO amplitudemean have been removed in these RMMvalues; 20140101-: Only the 120-day has been removed.\",,,,,,,,,,,
84917643405NaN19839261.776850.4607079951.83561WH04_method:_OLR_&_NCEP_wind,,,,,,,,,,,
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" ], "text/plain": [ " level_0 index \" year month day RMM1 RMM2 MJO phase \\\n", "849 1764 3405 NaN 1983 9 26 1.77685 0.46070799 5 \n", "\n", " MJO amplitude mean have been removed in these RMM \\\n", "849 1.83561 WH04_method:_OLR_&_NCEP_wind \n", "\n", " values; 20140101-: Only the 120-day has been removed.\",,,,,,,,,,, \n", "849 ,,,,,,,,,,, " ] }, "execution_count": 227, "metadata": {}, "output_type": "execute_result" } ], "source": [] }, { "cell_type": "markdown", "id": "c1275352-b536-4c72-9c3f-8c8c85a41dc3", "metadata": {}, "source": [ "Phase 0\n", "Storm 6, 1980\n", "Storm 14, 1980\n", "Storm 16, 1980\n", "Storm 18, 1980\n", "Storm 6, 1981\n", "Storm 22, 1981\n", "Storm 2, 3, 5, 6, and 8, 1982\n", "Storm 4, 1983\n", "Storm 6, 7, 8, 1984\n", "Storm 14, 15, 16, 1984\n", "Storm 1, 1985\n", "Storm 3, 4, 5, 1985\n", "Storm 8, 9, 1985\n", "Storm 11, 1985\n", "Storm 7, 1987\n", "Storm 13, 1987\n", "Storm 1, 2, 1988\n", "Storm 5, 1988\n", "Storm 6, 7, 8 1988\n", "Storm 12, 1988\n", "Storm 2, 3, 4, 5 1989\n", "Storm 8, 1989\n", "Storm 10, 11, 1989\n", "Storm 2, 3, 4, 5, 6, 7, 1990\n", "Storm 9, 10, 1990\n", "Storm 13, 14, 1990\n", "Storm 1, 1991\n", "Storm 11, 12, 1991\n", "Storm 9, 1992\n", "Storm 4, 5, 6, 7, 8, 9, 1993\n", "Storm 1, 1994\n", "Storm 3, 4, 1994\n", "Storm 1, 1995\n", "Storm 3, 1995\n", "Storm 7, 1995\n", "Storm 9, 10, 11, 1995\n", "Storm 15, 16, 17, 18, 1995\n", "Storm 20, 21, 1995\n", "Storm 5, 1996\n", "Storm 7, 8, 1996\n", "Storm 11, 12, 1996\n", "Storm 7, 8, 1997\n", "Storm 1, 1998\n", "Storm 7, 1998\n", "Storm 13, 1998\n", "Storm 1, 1999\n", "Storm 9, 1999\n", "Storm 13, 1999\n", "Storm 5, 2000\n", "Storm 10, 2000\n", "Storm 14, 2000\n", "Storm 3, 2001\n", "Storm 6, 2001\n", "Storm 16, 17, 2001\n", "Storm 5, 6, 2002\n", "Storm 8, 9, 10, 11, 12, 2002\n", "Storm 3, 2003\n", "Storm 5, 2003\n", "Storm 8, 2003\n", "Storm 10, 11, 12, 13, 2003\n", "Storm 15, 16, 2003\n", "Storm 1, 2004\n", "Storm 8, 2004\n", "Storm 16, 2004\n", "Storm 1, 2, 2005\n", "Storm 6, 7, 2005\n", "Storm 11, 12, 13, 2005\n", "Storm 18, 2005\n", "Storm 20, 21, 2005\n", "Storm 26, 2005\n", "Storm 28, 2005\n", "Storm 30, 2005\n", "Storm 7, 2006\n", "Storm 3, 4, 5, 2007\n", "Storm 12, 2007\n", "Storm 14, 2007\n", "Storm 5, 2008\n", "Storm 12, 13, 14, 15, 2008\n", "Storm 17, 2008\n", "Storm 5, 2009\n", "Storm 4, 2010\n", "Storm 6, 2010\n", "Storm 8, 9, 2010\n", "Storm 11, 12, 13, 2010\n", "Storm 15, 16, 2010\n", "Storm 19, 20, 21, 2010\n", "Storm 1, 2, 2011\n", "Storm 4, 5, 2011\n", "Storm 13, 14, 15, 16, 17, 18, 2011\n", "Storm 6, 2012\n", "Storm 16, 17, 2012\n", "Storm 1, 2013\n", "Storm 5, 2013\n", "Storm 7, 2013\n", "Storm 9, 10, 2013\n", "Storm 13, 14, 2013\n", "Storm 1, 2014\n", "Storm 3, 2014\n", "Storm 6, 7, 8, 9, 2014\n", "Storm 4, 2015\n", "Storm 6, 2015\n", "Storm 8, 2015\n", "Storm 10, 11, 2015\n", "Storm 3, 2016\n", "Storm 5, 2016\n", "Storm 9, 2016\n", "Storm 6, 7, 8, 9, 10, 11, 12, 2017\n", "Storm 15, 2017\n", "Storm 18, 2017\n", "Storm 2, 2018\n", "Storm 6, 7, 2018\n", "Storm 10, 2018\n", "Storm 4, 2019\n", "Storm 9, 2019" ] }, { "cell_type": "code", "execution_count": 252, "id": "77528804-389f-4f21-bd35-8d3d914a0a14", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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level_0index\"yearmonthdayRMM1RMM2MJO phaseMJO amplitudemean have been removed in these RMMvalues; 20140101-: Only the 120-day has been removed.\",,,,,,,,,,,
6184709914026NaN20121024-0.53828579-1.210545121.324829WH04_method:_OLR_&_NCEP_wind,,,,,,,,,,,
\n", "
" ], "text/plain": [ " level_0 index \" year month day RMM1 RMM2 \\\n", "6184 7099 14026 NaN 2012 10 24 -0.53828579 -1.2105451 \n", "\n", " MJO phase MJO amplitude mean have been removed in these RMM \\\n", "6184 2 1.324829 WH04_method:_OLR_&_NCEP_wind \n", "\n", " values; 20140101-: Only the 120-day has been removed.\",,,,,,,,,,, \n", "6184 ,,,,,,,,,,, " ] }, "execution_count": 252, "metadata": {}, "output_type": "execute_result" } ], "source": [ "august_2 = large_MJO.loc[(large_MJO['year'] == 2012) & (large_MJO['month'] == 10) & (large_MJO['day'] == 24)]\n", "august_2" ] }, { "cell_type": "code", "execution_count": 268, "id": "f8400a3b-e56a-463b-8083-46c5facadfbd", "metadata": {}, "outputs": [], "source": [ "storm_dates(2012, 35)" ] }, { "cell_type": "markdown", "id": "270eb8d2-b2f8-4d5e-a415-9eb90cdf5ea4", "metadata": {}, "source": [ "MOVE STORM 10 OF 1986 FROM PHASE 34 TO PHASE 78\n", "\n", "2012\n", "6/17 storm 3 phase 1\n", "6/23 storm 4 phase 1\n", "8/2 storm 5 phase 6\n", "8/4 storm 6 phase 0\n", "8/17 storm 7 phase 2\n", "8/16 storm 8 phase 1\n", "8/21 storm 9 phase 2\n", "8/23 storm 10 phase 3\n", "8/29 storm 11 phase 3\n", "8/30 storm 12 phase 3\n", "9/4 storm 13 phase 3\n", "9/12 storm 14 phase 5\n", "10/3 storm 15 phase 6\n", "10/11 storm 16 phase 0\n", "10/12 storm 17 phase 0\n", "10/22 storm 18 phase 2\n", "10/24 storm 19 phase 2\n", "\n", "2011\n", "6/28 storm 1 phase 0\n", "7/18 storm 2 phase 0\n", "7/20 storm 3 phase 4\n", "7/27 storm 4 phase 0\n", "8/2 storm 5 phase 0\n", "8/13 storm 6 phase 2\n", "8/14 storm 7 phase 2\n", "8/19 storm 8 phase 2\n", "8/21 storm 9 phase 1\n", "8/27 storm 11 phase 3\n", "8/30 storm 12 phase 3\n", "9/1 storm 13 phase 0\n", "9/2 storm 14 phase 0\n", "9/7 storm 15 phase 0\n", "9/7 storm 16 phase 0\n", "9/21 storm 17 phase 0\n", "9/24 storm 18 phase 0\n", "10/24 storm 19 phase 2\n", "11/6 storm 20 phase 5\n", "\n", "2010 \n", "6/26 storm 1 phase 2\n", "7/22 storm 3 phase 3\n", "8/3 storm 4 phase 0\n", "8/22 storm 6 phase 0\n", "8/25 storm 7 phase 5\n", "8/30 storm 8 phase 0\n", "9/1 storm 9 phase 0\n", "9/6 storm 10 phase 2\n", "9/8 storm 11 phase 0\n", "9/12 storm 12 phase 0\n", "9/14 storm 13 phase 0\n", "9/21 storm 14 phase 1\n", "9/23 storm 15 phase 0\n", "9/28 storm 16 phase 0\n", "10/6 storm 17 phase 4\n", "10/11 storm 18 phase 5\n", "10/21 storm 19 phase 0\n", "10/29 storm 20 phase 0\n", "10/29 storm 21 phase 0\n", "\n", "2009\n", "8/12 storm 2 phase 1\n", "8/15 storm 3 phase 2\n", "8/16 storm 4 phase 2\n", "8/26 storm 5 phase 0\n", "9/1 storm 6 phase 4\n", "9/8 storm 7 phase 4\n", "9/27 storm 9 phase 5\n", "10/6 storm 10 phase 4\n", "11/4 storm 11 phase 2\n", "\n", "2008\n", "7/3 storm 2 phase 1\n", "7/19 storm 3 phase 3\n", "7/20 storm 4 phase 3\n", "8/4 storm 5 phase 0\n", "8/15 storm 6 phase 2\n", "8/25 storm 7 phase 2\n", "8/28 storm 8 phase 2\n", "9/1 storm 9 phase 2\n", "9/2 storm 10 phase 2\n", "9/25 storm 11 phase 6\n", "9/26 storm 12 phase 0\n", "10/6 storm 13 phase 0 \n", "10/12 storm 14 phase 0\n", "10/14 storm 15 phase 0\n", "11/6 storm 17 phase 0\n", "\n", "2007 \n", "6/1 storm 2 phase 1\n", "7/31 storm 3 phase 0\n", "8/14 storm 4 phase 0\n", "8/15 storm 5 phase 0\n", "9/1 storm 6 phase 2\n", "9/8 storm 7 phase 4\n", "9/13 storm 8 phase 5\n", "9/12 storm 9 phase 5\n", "9/23 storm 11 phase 5\n", "9/25 storm 12 phase 0\n", "9/27 storm 13 phase 6\n", "9/29 storm 14 phase 0\n", "10/16 storm 15 phase 8\n", "10/28 storm 16 phase 5\n", "\n", "2006\n", "6/11 storm 1 phase 1\n", "7/17 storm 2 phase 8\n", "7/18 storm 3 phase 8\n", "8/1 storm 4 phase 2\n", "8/23 storm 5 phase 1\n", "8/25 storm 6 phase 1\n", "9/5 storm 7 phase 0\n", "9/11 storm 8 phase 3\n", "9/14 storm 9 phase 3\n", "9/28 storm 10 phase 4\n", "\n", "2005\n", "6/9 storm 1 phase 0\n", "6/28 storm 2 phase 0\n", "7/5 storm 3 phase 2\n", "7/5 storm 4 phase 2\n", "7/12 storm 5 phase 1\n", "7/22 storm 6 phase 0\n", "7/24 storm 7 phase 0\n", "8/3 storm 8 phase 6\n", "8/7 storm 9 phase 6\n", "8/22 storm 11 phase 0\n", "8/24 storm 12 phase 0\n", "8/31 storm 13 phase 0\n", "9/2 storm 14 phase 3\n", "9/6 storm 15 phase 4\n", "9/7 storm 16 phase 4\n", "9/17 storm 17 phase 5\n", "9/18 storm 18 phase 0\n", "10/2 storm 20 phase 0\n", "10/4 storm 21 phase 0\n", "10/5 storm 22 phase 1\n", "10/12 storm 23 phase 2\n", "10/8 storm 24 phase 1\n", "10/17 storm 25 phase 5\n", "10/22 storm 26 phase 0\n", "10/27 storm 27 phase 4\n", "11/15 storm 28 phase 0\n", "11/20 storm 29 phase 8\n", "11/29 storm 30 phase 0\n", "\n", "2004\n", "8/1 storm 1 phase 0\n", "8/9 storm 2 phase 6\n", "8/10 storm 3 phase 6 \n", "8/14 storm 4 phase 6\n", "8/14 storm 5 phase 6\n", "8/25 storm 6 phase 8 \n", "8/28 storm 7 phase 8\n", "8/29 storm 8 phase 0\n", "9/3 storm 9 phase 1\n", "9/14 storm 11 phase 2\n", "9/16 storm 12 phase 2\n", "9/20 storm 13 phase 2\n", "10/8 storm 14 phase 5\n", "10/10 storm 15 phase 5\n", "11/26 storm 16 phase 0\n", "\n", "2003 \n", "6/29 storm 3 phase 0\n", "7/7 storm 4 phase 2\n", "7/17 storm 5 phase 0\n", "8/14 storm 8 phase 0\n", "8/28 storm 10 phase 0\n", "8/30 storm 11 phase 0\n", "9/5 storm 12 phase 0\n", "9/6 storm 13 phase 0\n", "9/25 storm 15 phase 0\n", "9/27 storm 16 phase 0\n", "9/30 storm 17 phase 4\n", "10/10 storm 18 phase 4\n", "10/14 storm 19 phase 5\n", "\n", "2002\n", "7/15 storm 1 phase 8\n", "8/5 storm 2 phase 3\n", "8/6 storm 3 phase 3\n", "8/29 storm 4 phase 8\n", "9/2 storm 5 phase 0\n", "9/6 storm 6 phase 0\n", "9/8 storm 8 phase 0\n", "9/12 storm 9 phase 0\n", "9/18 storm 10 phase 0\n", "9/18 storm 11 phase 0\n", "9/21 storm 12 phase 0\n", "9/23 storm 13 phase 2\n", "\n", "2001\n", "6/5 storm 1 phase 2\n", "8/2 storm 3 phase 0\n", "8/17 storm 4 phase 6\n", "8/22 storm 5 phase 7\n", "9/2 storm 6 phase 0\n", "9/11 storm 7 phase 1\n", "9/13 storm 8 phase 2\n", "9/22 storm 10 phase 2\n", "10/5 storm 11 phase 4\n", "10/7 storm 12 phase 5\n", "10/11 storm 13 phase 6\n", "10/30 storm 14 phase 2\n", "11/1 storm 15 phase 3\n", "11/4 storm 16 phase 0\n", "11/24 storm 17 phase 0\n", "\n", "2000\n", "8/4 storm 3 phase 1\n", "8/14 storm 5 phase 0\n", "8/18 storm 6 phase 5\n", "8/20 storm 7 phase 5\n", "9/2 storm 8 phase 8\n", "9/11 storm 10 phase 0 \n", "9/16 storm 11 phase 2\n", "9/21 storm 12 phase 2\n", "9/22 storm 13 phase 1\n", "9/26 storm 14 phase 0\n", "9/29 storm 15 phase 2\n", "10/5 storm 16 phase 3\n", "10/16 storm 17 phase 5\n", "10/20 storm 18 phase 5\n", "10/25 storm 19 phase 6\n", "\n", "\n", "1999\n", "6/12 storm 1 phase 0 \n", "8/19 storm 3 phase 1\n", "8/20 storm 4 phase 1\n", "8/24 storm 5 phase 2\n", "8/24 storm 6 phase 2\n", "9/8 storm 8 phase 8\n", "9/12 storm 9 phase 0\n", "9/20 storm 10 phase 1\n", "10/13 storm 13 phase 0 \n", "10/18 storm 14 phase 3\n", "10/29 storm 15 phase 4\n", "11/14 storm 16 phase 7\n", "\n", "1998\n", "7/29 storm 1 phase 0\n", "8/20 storm 2 phase 2\n", "8/21 storm 3 phase 2\n", "8/24 storm 4 phase 1 \n", "8/31 storm 5 phase 8\n", "9/9 storm 6 phase 8\n", "9/16 storm 7 phase 0\n", "9/19 storm 8 phase 3\n", "9/20 storm 9 phase 4\n", "9/21 storm 10 phase 4\n", "9/24 storm 11 phase 4\n", "10/5 storm 12 phase 5\n", "10/22 storm 13 phase 0\n", "11/24 storm 14 phase 6\n", "\n", "1997\n", "6/1 storm 1 phase 7\n", "7/1 storm 2 phase 3\n", "7/11 storm 3 phase 4\n", "7/13 storm 4 phase 3\n", "7/17 storm 5 phase 4\n", "9/3 storm 7 phase 0\n", "10/5 storm 8 phase 0\n", "10/15 storm 9 phase 1\n", "\n", "\n", "1996\n", "6/19 storm 1 phase 5\n", "7/5 storm 2 phase 2\n", "7/25 storm 3 phase 6\n", "8/19 storm 4 phase 3\n", "8/22 storm 5 phase 0\n", "8/27 storm 6 phase 3\n", "8/28 storm 7 phase 0\n", "9/7 storm 8 phase 0 \n", "9/25 storm 9 phase 7\n", "10/6 storm 10 phase 1\n", "10/11 storm 11 phase 0\n", "10/16 storm 12 phase 0\n", "11/19 storm 13 phase 1\n", "\n", "1995\n", "6/3 storm 1 phase 0\n", "7/7 storm 2 phase 3\n", "7/14 storm 3 phase 0\n", "7/30 storm 4 phase 2\n", "7/31 storm 5 phase 2\n", "8/8 storm 7 phase 0\n", "8/10 storm 8 phase 1\n", "8/22 storm 9 phase 0\n", "8/22 storm 10 phase 0\n", "8/23 storm 11 phase 0\n", "8/28 storm 12 phase 3\n", "8/29 storm 13 phase 4\n", "9/13 storm 15 phase 0\n", "9/27 storm 16 phase 0\n", "9/30 storm 17 phase 0\n", "10/5 storm 18 phase 0\n", "10/9 storm 19 phase 7\n", "10/21 storm 20 phase 0\n", "10/27 storm 21 phase 0\n", "\n", "1994\n", "7/2 storm 1 phase 0\n", "8/15 storm 3 phase 0\n", "8/17 storm 4 phase 0\n", "9/10 storm 6 phase 6\n", "9/22 storm 7 phase 7\n", "11/2 storm 11 phase 1\n", "11/10 storm 12 phase 2\n", "\n", "1993 \n", "6/2 storm 1 phase 3\n", "6/19 storm 2 phase 8\n", "8/5 storm 3 phase 6\n", "8/14 storm 4 phase 0\n", "8/25 storm 5 phase 0\n", "8/24 storm 6 phase 0 \n", "9/7 storm 7 phase 0\n", "9/15 storm 8 phase 0\n", "9/20 storm 9 phase 0\n", "\n", "1992 \n", "8/17 storm 4 phase 5\n", "9/18 storm 5 phase 8\n", "9/22 storm 6 phase 1\n", "9/22 storm 7 phase 1\n", "9/29 storm 9 phase 0\n", "10/22 storm 10 phase 5\n", "\n", "1991\n", "7/4 storm 1 phase 0 \n", "8/16 storm 3 phase 5\n", "9/5 storm 6 phase 5\n", "9/8 storm 7 phase 6\n", "9/9 storm 8 phase 6\n", "10/15 storm 9 phase 3\n", "10/26 storm 11 phase 0\n", "10/29 storm 12 phase 0\n", "\n", "1990\n", "7/24 storm 2 phase 0\n", "7/28 storm 3 phase 0\n", "8/2 storm 4 phase 0\n", "8/3 storm 5 phase 0\n", "8/5 storm 6 phase 0\n", "8/13 storm 7 phase 0\n", "8/25 storm 8 phase 6\n", "8/26 storm 9 phase 0\n", "9/5 storm 10 phase 0\n", "9/24 storm 12 phase 2\n", "10/3 storm 13 phase 0\n", "10/6 storm 14 phase 0\n", "10/10 storm 15 phase 1\n", "10/16 storm 16 phase 1\n", "\n", "1989\n", "6/26 storm 2 phase 0\n", "7/11 storm 3 phase 0\n", "7/31 storm 4 phase 0\n", "8/1 storm 5 phase 0\n", "8/19 storm 7 phase 7\n", "8/26 storm 8 phase 0\n", "8/31 storm 10 phase 0 \n", "9/11 storm 11 phase 0\n", "9/18 storm 12 phase 2 \n", "10/13 storm 14 phase 4\n", "11/30 storm 15 phase 8 \n", "\n", "1988\n", "8/7 storm 1 phase 0 \n", "8/8 storm 2 phase 0 \n", "8/28 storm 3 phase 1\n", "9/2 storm 4 phase 1\n", "9/3 storm 5 phase 0\n", "9/7 storm 6 phase 0\n", "9/7 storm 7 phase 0\n", "9/9 storm 8 phase 0\n", "9/20 storm 9 phase 4\n", "9/30 storm 10 phase 5\n", "10/11 storm 11 phase 6\n", "11/20 storm 12 phase 0\n", "\n", "1987 \n", "8/9 storm 2 phase 2\n", "8/11 storm 3 phase 2 \n", "8/18 storm 5 phase 3\n", "9/7 storm 7 phase 0\n", "9/10 storm 10 phase 4\n", "9/20 storm 12 phase 2\n", "10/10 storm 13 phase 0\n", "\n", "1986 \n", "6/6 storm 1 phase 2\n", "6/24 storm 2 phase 6\n", "8/15 storm 5 phase 6\n", "9/7 storm 8 phase 3\n", "9/11 storm 9 phase 4\n", "11/19 storm 10 phase 7\n", "\n", "1985\n", "7/16 storm 1 phase 0\n", "7/22 storm 2 phase 1\n", "8/11 storm 3 phase 0\n", "8/14 storm 4 phase 0\n", "8/28 storm 5 phase 0\n", "9/16 storm 8 phase 0\n", "9/17 storm 9 phase 0\n", "9/23 storm 10 phase 8\n", "10/7 storm 11 phase 0 \n", "10/26 storm 12 phase 8 \n", "11/15 storm 13 phase 5\n", "\n", "1984 \n", "8/19 storm 5 phase 5\n", "8/29 storm 6 phase 0\n", "8/31 storm 7 phase 0\n", "8/31 storm 8 phase 0\n", "9/8 storm 10 phase 8 \n", "9/14 storm 11 phase 7\n", "9/16 storm 12 phase 7 \n", "9/18 storm 13 phase 8 \n", "9/23 storm 14 phase 0\n", "9/26 storm 15 phase 0 \n", "10/8 storm 16 phase 0\n", "11/6 storm 18 phase 1\n", "\n", "1979 \n", "6/22 storm 2 phase 4\n", "7/10 storm 4 phase 8\n", "7/17 storm 6 phase 8 \n", "8/26 storm 9 phase 1\n", "8/30 storm 11 phase 1\n", "8/30 storm 12 phase 1\n", "9/6 storm 14 phase 1\n", "9/16 storm 15 phase 2\n", "10/24 storm 18 phase 1\n", "\n", "1980\n", "8/2 storm 4 phase 1\n", "8/14 storm 6 phase 0 \n", "8/21 storm 7 phase 4 \n", "9/7 storm 9 phase 5 \n", "9/5 storm 10 phase 5\n", "9/5 storm 11 phase 5\n", "9/6 storm 12 phase 5\n", "9/21 storm 13 phase 1\n", "10/4 storm 14 phase 0 \n", "11/9 storm 16 phase 0\n", "11/25 storm 18 phase 0\n", "\n", "1981 \n", "6/29 storm 6 phase 0\n", "8/3 storm 9 phase 6\n", "8/8 storm 10 phase 6\n", "9/1 storm 13 phase 2\n", "9/4 storm 14 phase 2\n", "9/8 storm 15 phase 2\n", "9/12 storm 16 phase 2 \n", "9/23 storm 18 phase 5\n", "10/30 storm 20 phase 3\n", "11/4 storm 21 phase 4 \n", "11/12 storm 22 phase 0 \n", "\n", "1982\n", "6/3 storm 1 phase 4\n", "6/18 storm 2 phase 0\n", "8/28 storm 3 phase 0\n", "9/10 storm 5 phase 0\n", "9/14 storm 6 phase 0 \n", "10/1 storm 8 phase 0\n", "\n", "1983 \n", "8/15 storm 3 phase 4\n", "8/24 storm 4 phase 0\n", "9/11 storm 5 phase 2\n", "9/26 storm 6 phase 5" ] }, { "cell_type": "markdown", "id": "floppy-belly", "metadata": {}, "source": [ "Checked up to 2012\n", "\n", "Phase 12 \n", "Storm 9 of 1979\n", "Storm 11, 12 of 1979\n", "Storm 14, 15 of 1979\n", "Storm 18, 1979\n", "Storm 4 of 1980 \n", "Storm 13 of 1980 \n", "Storm 13, 14, 15, 16 of 1981\n", "Storm 5 of 1983\n", "Storm 18 of 1984\n", "Storm 2 of 1985\n", "Storm 1 of 1986\n", "Storm 2, 3 of 1987\n", "Storm 12 of 1987\n", "Storm 3, 4 of 1988\n", "Storm 12 of 1989\n", "Storm 12 of 1990\n", "Storm 15, 16 of 1990\n", "Storm 6, 7 of 1992\n", "Storm 11, 12 of 1994\n", "Storm 4, 5 of 1995\n", "Storm 8 of 1995\n", "Storm 2 of 1996\n", "Storm 10 of 1996\n", "Storm 13 of 1996\n", "Storm 9 of 1997\n", "Storm 2, 3, 4 of 1998\n", "Storm 3, 4, 5, 6 of 1999\n", "Storm 10 of 1999\n", "Storm 3 of 2000 \n", "Storm 11, 12, 13 of 2000\n", "Storm 15 of 2000\n", "Storm 1 of 2001\n", "Storm 7, 8 of 2001\n", "Storm 10 of 2001\n", "Storm 14 of 2001\n", "Storm 13 of 2002\n", "Storm 4 of 2003\n", "Storm 9 of 2004\n", "Storm 11, 12, 13 of 2004\n", "Storm 3, 4, 5 of 2005\n", "Storm 22, 23, 24 of 2005\n", "Storm 1 of 2006\n", "Storm 4, 5, 6 of 2006\n", "Storm 2 of 2007\n", "Storm 6 of 2007\n", "Storm 2 of 2008\n", "Storm 6, 7, 8, 9, 10 of 2008\n", "Storm 2, 3, 4 of 2009\n", "Storm 11 of 2009\n", "Storm 1 of 2010\n", "Storm 10 of 2010\n", "Storm 14 of 2010\n", "Storm 6, 7, 8, 9 of 2011\n", "Storm 19 of 2011\n", "Storm 3, 4 of 2012\n", "Storm 7, 8, 9 of 2012\n", "Storm 18, 19 of 2012\n", "Storm 3 of 2013\n", "Storm 4 of 2014\n", "Storm 5 of 2015\n", "Storm 7 of 2015\n", "Storm 16 of 2016\n", "Storm 2, 3 of 2017\n", "Storm 14, 15 of 2018\n", "Storm 2 of 2019\n", "Storm 12, 13, 14 of 2019\n", "Storm 16 of 2019\n", "Storm 18 of 2019\n", "\n", "Phase 34 \n", "Storm 2 of 1979\n", "Storm 7 of 1980\n", "Storm 20, 21 of 1981\n", "Storm 1 of 1982\n", "Storm 3 of 1983\n", "Storm 8, 9 of 1986\n", "Storm 5 of 1987\n", "Storm 10 of 1987\n", "Storm 9 of 1988\n", "Storm 14 of 1989\n", "Storm 9 of 1991\n", "Storm 1 of 1993\n", "Storm 2 of 1995\n", "Storm 12, 13 of 1995\n", "Storm 4 of 1996\n", "Storm 6 of 1996\n", "Storm 2, 3, 4, 5 of 1997\n", "Storm 8, 9, 10, 11 of 1998\n", "Storm 14, 15 of 1999\n", "Storm 16 of 2000\n", "Storm 11 of 2001\n", "Storm 15 of 2001\n", "Storm 2, 3 of 2002\n", "Storm 17, 18 of 2003\n", "Storm 14, 15, 16 of 2005\n", "Storm 27 of 2005\n", "Storm 8, 9, 10 of 2006\n", "Storm 7 of 2007\n", "Storm 3, 4 of 2008\n", "Storm 6, 7 of 2009\n", "Storm 10 of 2009\n", "Storm 3 of 2010\n", "Storm 17 of 2010\n", "Storm 3 of 2011\n", "Storm 11, 12 of 2011\n", "Storm 10, 11, 12, 13 of 2012\n", "Storm 5 of 2014\n", "Storm 2 of 2015\n", "Storm 12 of 2015\n", "Storm 4 of 2016\n", "Storm 10, 11, 12 of 2016\n", "Storm 5 of 2017\n", "Storm 13, 14 of 2017\n", "Storm 16 of 2017\n", "Storm 3 of 2018\n", "Storm 5, 6 of 2019\n", "Storm 17 of 2019\n", "Storm 19 of 2019\n", "\n", "Phase 56\n", "Storm 9, 10, 11, 12 of 1980\n", "Storm 9, 10 of 1981\n", "Storm 18 of 1981\n", "Storm 6 of 1983\n", "Storm 5 of 1984\n", "Storm 13 of 1985\n", "Storm 2 of 1986\n", "Storm 5 of 1986\n", "Storm 10, 11 of 1988\n", "Storm 8 of 1990\n", "Storm 3 of 1991\n", "Storm 6, 7, 8 of 1991\n", "Storm 4 of 1992\n", "Storm 10 of 1992\n", "Storm 3 of 1993\n", "Storm 6 of 1994\n", "Storm 1 of 1996\n", "Storm 3 of 1996\n", "Storm 12 of 1998\n", "Storm 14 of 1998\n", "Storm 6, 7 of 2000\n", "Storm 17, 18, 19 of 2000\n", "Storm 4 of 2001\n", "Storm 12, 13 of 2001\n", "Storm 19 of 2003\n", "Storm 2, 3, 4, 5 of 2004\n", "Storm 14, 15 of 2004\n", "Storm 8, 9 of 2005\n", "Storm 17 of 2005\n", "Storm 25 of 2005\n", "Storm 8, 9 of 2007\n", "Storm 11 of 2007\n", "Storm 13 of 2007\n", "Storm 16 of 2007\n", "Storm 11 of 2008\n", "Storm 9 of 2009\n", "Storm 7 of 2010\n", "Storm 18 of 2010\n", "Storm 20 of 2011\n", "Storm 5 of 2012\n", "Storm 14, 15 of 2012\n", "Storm 2 of 2013\n", "Storm 11, 12 of 2013\n", "Storm 6, 7 of 2016\n", "Storm 13, 14, 15 of 2016\n", "Storm 5 of 2018\n", "Storm 7, 8 of 2019\n", "\n", "Phase 78\n", "Storm 4 of 1979\n", "Storm 6 of 1979\n", "Storm 10, 11, 12, 13 of 1984\n", "Storm 10 of 1985\n", "Storm 12 of 1985\n", "**Storm 10 of 1986\n", "Storm 7 of 1989\n", "Storm 15 of 1989\n", "Storm 5 of 1992\n", "Storm 2 of 1993\n", "Storm 7 of 1994\n", "Storm 19 of 1995\n", "Storm 9 of 1996\n", "Storm 1 of 1997\n", "Storm 5, 6 of 1998\n", "Storm 8 of 1999\n", "Storm 16 of 1999\n", "Storm 8 of 2000\n", "Storm 5 of 2001\n", "Storm 1 of 2002\n", "Storm 4 of 2002\n", "Storm 6, 7 of 2004\n", "Storm 29 of 2005\n", "Storm 2, 3 of 2006\n", "Storm 15 of 2007\n", "Storm 4, of 2013\n", "Storm 6 of 2013\n", "Storm 3 of 2015\n", "Storm 17 of 2017\n", "Storm 4 of 2018\n", "Storm 8, 9 of 2018\n", "Storm 12, 13 of 2018\n", "Storm 16 of 2018\n", "Storm 10, 11 of 2019\n", "Storm 20 of 2019" ] }, { "cell_type": "code", "execution_count": 3, "id": "abstract-height", "metadata": {}, "outputs": [], "source": [ "# ACE function: inputs - year, storm\n", "# should access the wind speed at each 6 hour interval starting from when it became a tropical storm (above 17 m/s) \n", "# and SQUARE each wind speed and add them up for each storm\n", "\n", "# only include data points for wind speeds of at least 17 m/s \n", "\n", "import numpy as np\n", "\n", "def ace(yearnum, stormnum):\n", "\n", " wind = NA_tracks.WIND\n", " tropical_storm = (wind >= 17)\n", " ts_wind = wind.where(tropical_storm).sel(YRT=yearnum, ZSTORM1 = stormnum).values\n", " ts_wind = ts_wind[~np.isnan(ts_wind)]\n", " ts_wind_sq = np.square(ts_wind)\n", " ACE = np.sum(ts_wind_sq)\n", " return ACE\n", "\n" ] }, { "cell_type": "markdown", "id": "efb6e3bc-50dd-4234-8d86-c2cecedfcda3", "metadata": {}, "source": [] }, { "cell_type": "markdown", "id": "62e53b95-6566-4bd7-bf27-694cbcf76d05", "metadata": {}, "source": [] }, { "cell_type": "markdown", "id": "a365f3c6-821f-48c8-84b4-c0a02aaf6e19", "metadata": {}, "source": [] }, { "cell_type": "code", "execution_count": 4, "id": "broken-ministry", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "3052067.0517581897" ] }, "execution_count": 4, "metadata": {}, "output_type": "execute_result" } ], "source": [ "ACE_phase12 = (ace(1979, 9) + ace(1979, 11) + ace(1979, 12) + ace(1979, 14) + ace(1979, 15) + ace(1979, 18) + \n", " ace(1980, 4) + ace(1980, 13) + ace(1981, 13) + ace(1981, 14) + ace(1981, 15) + ace(1981, 16) + ace(1983, 5) + \n", " ace(1984, 18) + ace(1985, 2) + ace(1986, 1) + ace(1987, 2) + ace(1987, 3) + ace(1987, 12) + ace(1988, 3) + \n", " ace(1988, 4) + ace(1989, 12) + ace(1990, 12) + ace(1990, 15) + ace(1990, 16) + ace(1992, 6) + ace(1992, 7) + \n", " ace(1994, 11) + ace(1994, 12) + ace(1995, 4) + ace(1995, 5) + ace(1995, 8) + ace(1996, 2) + ace(1996, 10) + \n", " ace(1996, 13) + ace(1997, 9) + ace(1998, 2) + ace(1998, 3) + ace(1998, 4) + ace(1999, 3) + ace(1999, 4) + \n", " ace(1999, 5) + ace(1999, 6) + ace(1999, 10) + ace(2000, 3) + ace(2000, 11) + ace(2000, 12) + ace(2000, 13) + \n", " ace(2000, 15) + ace(2001, 1) + ace(2001, 7) + ace(2001, 8) + ace(2001, 10) + ace(2001, 14) + ace(2002, 13) + \n", " ace(2003, 4) + ace(2004, 9) + ace(2004, 11) + ace(2004, 12) + ace(2004, 13) + ace(2005, 3) + ace(2005, 4) + \n", " ace(2005, 5) + ace(2005, 22) + ace(2005, 23) + ace(2005, 24) + ace(2006, 1) + ace(2006, 4) + ace(2006, 5) + \n", " ace(2006, 6) + ace(2007, 2) + ace(2007, 6) + ace(2008, 2) + ace(2008, 6) + ace(2008, 7) + ace(2008, 8) + \n", " ace(2008, 9) + ace(2008, 10) + ace(2009, 2) + ace(2009, 3) + ace(2009, 4) + ace(2009, 11) + ace(2010, 1) + \n", " ace(2010, 10) + ace(2010, 14) + ace(2011, 6) + ace(2011, 7) + ace(2011, 8) + ace(2011, 9) + \n", " ace(2011, 19) + ace(2012, 3) + ace(2012, 4) + ace(2012, 7) + ace(2012, 8) + ace(2012, 9) + ace(2012, 18) + \n", " ace(2012, 19))\n", "ACE_phase12\n", "\n", "# ace(2013, 3) + ace(2014, 4) + ace(2015, 5) + ace(2015, 7) + ace(2016, 16) + ace(2017, 2) + \n", "# ace(2017, 3) + ace(2018, 14) + ace(2018, 15) + ace(2019, 2) + ace(2019, 12) + ace(2019, 13) + ace(2019, 14) + \n", "# ace(2019, 16) + ace(2019, 18))\n", "\n", " \n", "# 106\n", " \n", " " ] }, { "cell_type": "markdown", "id": "constitutional-location", "metadata": {}, "source": [] }, { "cell_type": "code", "execution_count": 5, "id": "653ba266-06c3-4252-8f8a-8d5d7b2f92ff", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "1368631.49508039" ] }, "execution_count": 5, "metadata": {}, "output_type": "execute_result" } ], "source": [ "ACE_phase34 = (ace(1979, 2) + ace(1980, 7) + ace(1981, 20) + ace(1981, 21) + ace(1982, 1) + ace(1983, 3) + ace(1986, 8) + ace(1986, 9) + ace(1987, 5) + \n", " ace(1987, 10) + ace(1988, 9) + ace(1989, 14) + ace(1991, 9) + ace(1993, 1) + ace(1995, 2) + ace(1995, 12) + ace(1995, 13) + ace(1996, 4) + \n", " ace(1996, 6) + ace(1997, 2) + ace(1997, 3) + ace(1997, 4) + ace(1997, 5) + ace(1998, 8) + ace(1998, 9) + ace(1998, 10) + ace(1998, 11) + \n", " ace(1999, 14) + ace(1999, 15) + ace(2000, 16) + ace(2001, 11) + ace(2001, 15) + ace(2002, 2) + ace(2002, 3) + ace(2003, 17) + ace(2003, 18) + \n", " ace(2005, 14) + ace(2005, 15) + ace(2005, 16) + ace(2005, 27) + ace(2006, 8) + ace(2006, 9) + ace(2006, 10) + ace(2007, 7) + ace(2008, 3) + \n", " ace(2008, 4) + ace(2009, 6) + ace(2009, 7) + ace(2009, 10) + ace(2010, 3) + ace(2010, 17) + ace(2011, 3) + ace(2011, 11) + ace(2011, 12) + \n", " ace(2012, 10) + ace(2012, 11) + ace(2012, 12) + ace(2012, 13)) \n", "\n", "\n", "ACE_phase34\n", "\n", "# + ace(2014, 5) + ace(2015, 2) + ace(2015, 12) + ace(2016, 4) + ace(2016, 10) + \n", "# ace(2016, 11) + ace(2016, 12) + ace(2017, 5) + ace(2017, 13) + ace(2017, 14) + ace(2017, 16) + ace(2018, 3) + ace(2019, 5) + ace(2019, 6) + \n", "# ace(2019, 17) + ace(2019, 19))\n", "\n", "#74" ] }, { "cell_type": "markdown", "id": "02d372a7-0d66-4793-9732-7188bb00909d", "metadata": {}, "source": [] }, { "cell_type": "code", "execution_count": 6, "id": "18c4a89e-2dd2-4f25-a696-43bceda47765", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "1402705.48301283" ] }, "execution_count": 6, "metadata": {}, "output_type": "execute_result" } ], "source": [ "ACE_phase56 = (ace(1980, 9) + ace(1980, 10) + ace(1980, 11) + ace(1980, 12) + ace(1981, 9) + ace(1981, 10) + ace(1981, 18) +\n", " ace(1983, 6) + ace(1984, 5) + ace(1985, 13) + ace(1986, 2) + ace(1986, 5) + ace(1988, 10) + ace(1988, 11) + \n", " ace(1990, 8) + ace(1991, 3) + ace(1991, 6) + ace(1991, 7) + ace(1991, 8) + ace(1992, 4) + ace(1992, 10) + \n", " ace(1993, 3) + ace(1994, 6) + ace(1996, 1) + ace(1996, 3) + ace(1998, 12) + ace(1998, 14) + ace(2000, 6) + \n", " ace(2000, 7) + ace(2000, 17) + ace(2000, 18) + ace(2000, 19) + ace(2001, 4) + ace(2001, 12) + ace(2001, 13) + \n", " ace(2003, 19) + ace(2004, 2) + ace(2004, 3) + ace(2004, 4) + ace(2004, 5) + ace(2004, 14) + ace(2004, 15) + \n", " ace(2005, 8) + ace(2005, 9) + ace(2005, 17) + ace(2005, 25) + ace(2007, 8) + ace(2007, 9) + ace(2007, 11) + \n", " ace(2007, 13) + ace(2007, 16) + ace(2008, 11) + ace(2009, 9) + ace(2010, 7) + ace(2010, 18) + ace(2011, 20) + \n", " ace(2012, 5) + ace(2012, 14) + ace(2012, 15))\n", "\n", "ACE_phase56\n", "\n", "# + ace(2013, 2) + ace(2013, 11) + ace(2013, 12) + ace(2016, 6) + \n", "# ace(2016, 7) + ace(2016, 13) + ace(2016, 14) + ace(2016, 15) + ace(2018, 5) + ace(2019, 7) + ace(2019, 8))\n", "\n", "#70" ] }, { "cell_type": "markdown", "id": "fe941460-7b5b-4763-8caa-91cb5e48dc2d", "metadata": {}, "source": [] }, { "cell_type": "code", "execution_count": 7, "id": "a4f882f0-1436-4fc8-a713-48d6f158e261", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "683233.8472949099" ] }, "execution_count": 7, "metadata": {}, "output_type": "execute_result" } ], "source": [ "ACE_phase78 = (ace(1979, 4) + ace(1979, 6) + ace(1984, 10) + ace(1984, 11) + ace(1984, 12) + ace(1984, 13) + ace(1985, 10) + \n", " ace(1985, 12) + ace(1986, 10) + ace(1989, 7) + ace(1989, 15) + ace(1992, 5) + ace(1993, 2) + ace(1994, 7) + \n", " ace(1995, 19) + ace(1996, 9) + ace(1997, 1) + ace(1998, 5) + ace(1998, 6) + ace(1999, 8) + ace(1999, 16) + \n", " ace(2000, 8) + ace(2001, 5) + ace(2002, 1) + ace(2002, 4) + ace(2004, 6) + ace(2004, 7) + ace(2005, 29) + \n", " ace(2006, 2) + ace(2006, 3) + ace(2007, 15))\n", "\n", "ACE_phase78\n", " # ace(2013, 4) + ace(2013, 6) + ace(2015, 3) + ace(2017, 17) + ace(2018, 4) + ace(2018, 8) + ace(2018, 9) + \n", " # ace(2018, 12) + ace(2018, 13) + ace(2018, 16) + ace(2019, 10) + ace(2019, 11) + ace(2019, 20))\n", "#41" ] }, { "cell_type": "code", "execution_count": 11, "id": "7c6487f6-1be9-4516-9d4a-dfcc640615a7", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "Text(0.5, 1.0, 'Normalized ACE by MJO Phase, North Atlantic (1979-2012)')" ] }, "execution_count": 11, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# norm_phase0 = (ACE_phase0 / phase0) * 100\n", "norm_phase12 = (ACE_phase12 / phase12) * 100\n", "norm_phase34 = (ACE_phase34 / phase34) * 100\n", "norm_phase56 = (ACE_phase56 / phase56) * 100\n", "norm_phase78 = (ACE_phase78 / phase78) * 100\n", "\n", "import matplotlib.pyplot as plt\n", "plt.bar(['12', '34', '56', '78'], [norm_phase12, norm_phase34, norm_phase56, norm_phase78])\n", "plt.xlabel('MJO Phase')\n", "plt.ylabel('Normalized ACE')\n", "plt.title('Normalized ACE by MJO Phase, North Atlantic (1979-2012)')" ] }, { "cell_type": "code", "execution_count": 12, "id": "9d46b7d2-3c35-4d7d-a445-e9247654e99a", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "Text(0.5, 1.0, 'Percent of Normalized ACE Generated in Each MJO Phase')" ] }, "execution_count": 12, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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"text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "norm_ACE_tot = (norm_phase12 + norm_phase34 + norm_phase56 + norm_phase78)\n", "#perc0 = (norm_phase0 / norm_ACE_tot) * 100\n", "perc12 = (norm_phase12 / norm_ACE_tot) * 100\n", "perc34 = (norm_phase34 / norm_ACE_tot) * 100\n", "perc56 = (norm_phase56 / norm_ACE_tot) * 100\n", "perc78 = (norm_phase78 / norm_ACE_tot) * 100\n", "\n", "plt.bar(['12', '34', '56', '78'], [perc12, perc34, perc56, perc78])\n", "plt.xlabel('MJO Phase')\n", "plt.ylabel('Normalized ACE (%)')\n", "plt.title('Percent of Normalized ACE Generated in Each MJO Phase')" ] }, { "cell_type": "code", "execution_count": 116, "id": "virtual-columbus", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "array([11.])" ] }, "execution_count": 116, "metadata": {}, "output_type": "execute_result" } ], "source": [ "year = 1981\n", "monthRI_vec = monthRI.sel(YRT=year).values.ravel()\n", "monthRI_vec[~np.isnan(monthRI_vec)]\n", "\n", "\n" ] }, { "cell_type": "code", "execution_count": 113, "id": "revolutionary-parts", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "array([ 5., 6., 6., 10., 11., 11., 13., 13., 13., 13., 5.])" ] }, "execution_count": 113, "metadata": {}, "output_type": "execute_result" } ], "source": [] }, { "cell_type": "code", "execution_count": 117, "id": "russian-scroll", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "array([5.])" ] }, "execution_count": 117, "metadata": {}, "output_type": "execute_result" } ], "source": [ "dayRI_vec = dayRI.sel(YRT=year).values.ravel()\n", "dayRI_vec[~np.isnan(dayRI_vec)]\n" ] }, { "cell_type": "code", "execution_count": 833, "id": "reported-warning", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "array([], dtype=float64)" ] }, "execution_count": 833, "metadata": {}, "output_type": "execute_result" } ], "source": [ "\n", "year = 2019\n", "storm = 35\n", "\n", "wind = NA_tracks.WIND\n", "tropical_storm = (wind >= 17)\n", "\n", "month_storm = NA_tracks.MONTH.where(L).where(tropical_storm).sel(YRT=year, ZSTORM1 = storm).values.ravel()\n", "month_storm = month_storm[~np.isnan(month_storm)]\n", "month_storm" ] }, { "cell_type": "code", "execution_count": 815, "id": "sweet-indianapolis", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "array([25., 25., 26., 26.])" ] }, "execution_count": 815, "metadata": {}, "output_type": "execute_result" } ], "source": [ "day_storm = NA_tracks.DAY.where(L).where(tropical_storm).sel(YRT=year, ZSTORM1 = storm).values.ravel()\n", "day_storm = day_storm[~np.isnan(day_storm)]\n", "day_storm" ] }, { "cell_type": "code", "execution_count": 812, "id": "earned-neighbor", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
level_0index\"yearmonthdayRMM1RMM2MJO phaseMJO amplitudemean have been removed in these RMMvalues; 20140101-: Only the 120-day has been removed.\",,,,,,,,,,,
\n", "
" ], "text/plain": [ "Empty DataFrame\n", "Columns: [level_0, index, \", year, month, day, RMM1, RMM2, MJO phase, MJO amplitude, mean have been removed in these RMM, values; 20140101-: Only the 120-day has been removed.\",,,,,,,,,,,]\n", "Index: []" ] }, "execution_count": 812, "metadata": {}, "output_type": "execute_result" } ], "source": [ "MJO_nonzero = large_MJO.loc[(large_MJO['year'] == 2019) & (large_MJO['month'] == 10) & (large_MJO['day'] == 26)]\n", "MJO_nonzero " ] }, { "cell_type": "code", "execution_count": null, "id": "38a3a6a9-fbb4-4f2a-aa99-bd09f7192be1", "metadata": {}, "outputs": [], "source": [ "# change this so that it goes from 1979 - 2012\n", "ACE_phase0 = (ace(1980, 6) + ace(1980, 14) + ace(1980, 16) + ace(1980, 18) + ace(1981, 6) + ace(1981, 22) + ace(1982, 2) + ace(1982, 3) + ace(1982, 5) +\n", " ace(1982, 6) + ace(1982, 8) + ace(1983, 4) + ace(1984, 6) + ace(1984, 7) + ace(1984, 8) + ace(1984, 14) + ace(1984, 15) + ace(1984, 16) + \n", " ace(1985, 1) + ace(1985, 3) + ace(1985, 4) + ace(1985, 5) + ace(1985, 8) + ace(1985, 9) + ace(1985, 11) + ace(1987, 7) + ace(1987, 13) + \n", " ace(1988, 1) + ace(1988, 2) + ace(1988, 5) + ace(1988, 6) + ace(1988, 7) + ace(1988, 8) + ace(1988, 12) + ace(1989, 2) + ace(1989, 3) + \n", " ace(1989, 4) + ace(1989, 5) + ace(1989, 8) + ace(1989, 10) + ace(1989, 11) + ace(1990, 2) + ace(1990, 3) + ace(1990, 4) + ace(1990, 5) + \n", " ace(1990, 6) + ace(1990, 7) + ace(1990, 9) + ace(1990, 10) + ace(1990, 13) + ace(1990, 14) + ace(1991, 1) + ace(1991, 11) + ace(1991, 12) + \n", " ace(1992, 9) + ace(1993, 4) + ace(1993, 5) + ace(1993, 6) + ace(1993, 7) + ace(1993, 8) + ace(1993, 9) + ace(1994, 1) + ace(1994, 3) + \n", " ace(1994, 4) + ace(1995, 1) + ace(1995, 3) + ace(1995, 7) + ace(1995, 9) + ace(1995, 10) + ace(1995, 11) + ace(1995, 15) + ace(1995, 16) + \n", " ace(1995, 17) + ace(1995, 18) + ace(1995, 20) + ace(1995, 21) + ace(1996, 5) + ace(1996, 7) + ace(1996, 8) + ace(1996, 11) + ace(1996, 12) + \n", " ace(1997, 7) + ace(1997, 8) + ace(1998, 1) + ace(1998, 7) + ace(1998, 13) + ace(1999, 1) + ace(1999, 9) + ace(1999, 13) + ace(2000, 5) + \n", " ace(2000, 10) + ace(2000, 14) + ace(2001, 3) + ace(2001, 6) + ace(2001, 16) + ace(2001, 17) + ace(2002, 5) + ace(2002, 6) + ace(2002, 8) + \n", " ace(2002, 9) + ace(2002, 10) + ace(2002, 11) + ace(2002, 12) + ace(2003, 3) + ace(2003, 5) + ace(2003, 8) + ace(2003, 10) + ace(2003, 11) + \n", " ace(2003, 12) + ace(2003, 13) + ace(2003, 15) + ace(2003, 16) + ace(2004, 1) + ace(2004, 8) + ace(2004, 16) + ace(2005, 1) + ace(2005, 2) + \n", " ace(2005, 6) + ace(2005, 7) + ace(2005, 11) + ace(2005, 12) + ace(2005, 13) + ace(2005, 18) + ace(2005, 20) + ace(2005, 21) + ace(2005, 26) +\n", " ace(2005, 28) + ace(2005, 30) + ace(2006, 7) + ace(2007, 3) + ace(2007, 4) + ace(2007, 5) + ace(2007, 12) + ace(2007, 14) + ace(2008, 5) + \n", " ace(2008, 12) + ace(2008, 13) + ace(2008, 14) + ace(2008, 15) + ace(2008, 17) + ace(2009, 5) + ace(2010, 4) + ace(2010, 6) + ace(2010, 8) + \n", " ace(2010, 9) + ace(2010, 11) + ace(2010, 12) + ace(2010, 13) + ace(2010, 15) + ace(2010, 16) + ace(2010, 19) + ace(2010, 20) + ace(2010, 21) +\n", " ace(2011, 1) + ace(2011, 2) + ace(2011, 4) + ace(2011, 5) + ace(2011, 13) + ace(2011, 14) + ace(2011, 15) + ace(2011, 16) + ace(2011, 17) + \n", " ace(2011, 18) + ace(2012, 6) + ace(2012, 16) + ace(2012, 17))\n", "\n", "ACE_phase0\n", "#ace(2013, 1) + ace(2013, 5) + ace(2013, 7) + ace(2013, 9) + ace(2013, 10) + \n", " # ace(2013, 13) + ace(2013, 14) + ace(2014, 1) + ace(2014, 3) + ace(2014, 6) + ace(2014, 7) + ace(2014, 8) + ace(2014, 9) + ace(2015, 4) + \n", " # ace(2015, 6) + ace(2015, 8) + ace(2015, 10) + ace(2015, 11) + ace(2016, 3) + ace(2016, 5) + ace(2016, 9) + ace(2017, 6) + ace(2017, 7) + \n", " # ace(2017, 8) + ace(2017, 9) + ace(2017, 10) + ace(2017, 11) + ace(2017, 12) + ace(2017, 15) + ace(2017, 18) + ace(2018, 2) + ace(2018, 6) + \n", " # ace(2018, 7) + ace(2018, 10) + ace(2019, 4) + ace(2019, 9))" ] }, { "cell_type": "code", "execution_count": 2, "id": "blond-daisy", "metadata": {}, "outputs": [], "source": [ "# MJO phase for all dates when there was a TC in the Caribbean / GoM west of 77.5 W \n", "# only include dates within NA hurricane season (June 1 - November 30)\n", "MJO_TC_days = [0, 1, 1, 1, 1, 5, 5, 1, 1, 1, 1, 0, 0, 1, 1, 1, 2, 2, 0, 0, 0, 0, 4, 0, 0, 4, 4, 0, 0, 0, 4, 4, 4, 4, \n", " 0, 0, 0, 0, 8, 8, 8, 7, 7, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 8, 8, 8, 8, 1, 1, 6, 6, \n", " 6, 6, 2, 6, 6, 6, 2, 2, 0, 0, 0, 0, 0, 2, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 6, 6, 7, 7, 7, 0, 0, 0, 4, \n", " 5, 0, 0, 0, 0, 0, 2, 4, 4, 4, 4, 8, 0, 0, 0, 1, 1, 3, 3, 0, 0, 0, 0, 0, 8, 8, 7, 0, 0, 0, 0, 0, 0, 0, \n", " 0, 0, 2, 2, 2, 2, 2, 0, 0, 0, 0, 0, 0, 2, 2, 2, 2, 2, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 7, 7, 7, 7, 0, 0, \n", " 0, 0, 0, 0, 5, 5, 6, 6, 3, 3, 3, 0, 0, 1, 1, 1, 0, 0, 0, 0, 0, 0, 1, 1, 0, 0, 0, 4, 0, 0, 4, 2, 2, 8, \n", " 8, 8, 8, 8, 8, 0, 4, 4, 4, 4, 4, 5, 3, 4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 1, 1, 1, 2, 2, 0, 0, \n", " 1, 1, 1, 0, 0, 0, 0, 3, 4, 4, 7, 8, 0, 5, 2, 1, 1, 2, 1, 2, 2, 2, 2, 3, 3, 3, 2, 2, 0, 0, 3, 3, 3, 4, \n", " 6, 7, 7, 2, 2, 1, 2, 5, 5, 5, 3, 3, 0, 0, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2, 2, 2, 2, \n", " 0, 0, 0, 0, 0, 0, 0, 2, 2, 2, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 4, 0, 0, 0, 0, 0, 3, 6, 6, 6, 6, 6, \n", " 6, 6, 1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 3, 3, 3, 5, 5, 5, 0, 2, 0, 0, 2, 2, 2, 0, 0, 1, 0, 0, 0, 0, \n", " 0, 0, 5, 0, 0, 0, 0, 0, 0, 0, 4, 4, 5, 5, 7, 8, 8, 8, 8, 0, 0, 0, 1, 0, 5, 5, 5, 5, 0, 0, 0, 0, 4, 4, \n", " 4, 4, 8, 8, 8, 1, 1, 1, 2, 2, 0, 1, 1, 0, 0, 0, 0, 2, 2, 0, 0, 5, 5, 6, 0, 0, 0, 2, 3, 3, 0, 0, 0, 0, \n", " 0, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 3, 4, 4, 4, 5, 5, 5, 0, 0, 0, 0, 0, 4, 2, 2, 2, 2, 2, 3, 3, 3, \n", " 3, 2, 2, 2, 2, 1, 1, 3, 2, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 6, 6, 6, 6, 0, 0, 0, 0, 0, 0, 0, 0, 0, \n", " 0, 0, 0, 0, 0, 2, 2, 1, 1, 0, 0, 0, 0, 0, 0, 0, 3, 0, 2, 2, 2, 0, 0, 1, 1, 1, 1, 0, 0, 8, 8, 1, 1, 2, \n", " 2, 3, 3, 3, 3, 3, 2, 2, 0, 0, 0, 6, 6, 8, 1, 0, 4, 5, 4, 5, 5, 5, 0, 0, 0, 4, 4, 0, 4, 4, 0, 0, 0, 4, \n", " 0, 0, 0, 0, 5, 0, 0, 0, 4, 4, 5, 0, 0, 2, 3, 3, 0, 3, 3, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2, 2, 3, \n", " 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 4, 7, 0, 0, 8, 1, 1, 1, 2, 1, 0, 0, 0, 0, 5, 5, 6, 5, 5, 8, 8, 8, \n", " 1, 2, 2, 3, 0]\n", "\n" ] }, { "cell_type": "code", "execution_count": 3, "id": "fourth-atmosphere", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "Text(0.5, 1.0, 'Number of Gulf of Mexico Storm Days by MJO Index, 1980-2019')" ] }, "execution_count": 3, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "val, count = np.unique(MJO_TC_days, return_counts=True)\n", "val, count\n", "\n", "freq_0_TC = 299\n", "freq_1_TC = 60\n", "freq_2_TC = 97\n", "freq_3_TC = 42\n", "freq_4_TC = 44\n", "freq_5_TC = 36\n", "freq_6_TC = 27 \n", "freq_7_TC = 15\n", "freq_8_TC = 31\n", "\n", "import matplotlib.pyplot as plt\n", "plt.hist(MJO_TC_days, bins = 20)\n", "plt.xlabel('MJO Index')\n", "plt.ylabel('Number of Tropical Storm Days in the Gulf')\n", "plt.title('Number of Gulf of Mexico Storm Days by MJO Index, 1980-2019')" ] }, { "cell_type": "code", "execution_count": 400, "id": "featured-belfast", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "array([], dtype=float64)" ] }, "execution_count": 400, "metadata": {}, "output_type": "execute_result" } ], "source": [ "\n", "year = 2019\n", "#storm = 35\n", "\n", "wind = NA_tracks.WIND\n", "tropical_storm = (wind >= 17)\n", "\n", "#month_storm_RI = monthRI.where(tropical_storm).sel(YRT=year, ZSTORM1 = storm).values.ravel()\n", "month_storm_RI = monthRI.where(tropical_storm).sel(YRT=year).values.ravel()\n", "month_storm_RI = month_storm_RI[~np.isnan(month_storm_RI)]\n", "month_storm_RI\n" ] }, { "cell_type": "code", "execution_count": 341, "id": "regulated-motel", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "array([ 9., 10., 10., 10.])" ] }, "execution_count": 341, "metadata": {}, "output_type": "execute_result" } ], "source": [ "day_storm_RI = dayRI.where(tropical_storm).sel(YRT=year).values.ravel()\n", "#day_storm_RI = dayRI.where(tropical_storm).sel(YRT=year, ZSTORM1 = storm).values.ravel()\n", "day_storm_RI = day_storm_RI[~np.isnan(day_storm_RI)]\n", "day_storm_RI" ] }, { "cell_type": "markdown", "id": "improving-uganda", "metadata": {}, "source": [ "TC Days (winds of 17 m/s or more) in the GoM & Caribbean\n", "\n", "2019\n", "7/11\n", "7/12\n", "7/13\n", "7/14\n", "9/2\n", "9/3\n", "9/4\n", "9/5\n", "9/3\n", "9/4\n", "9/15\n", "9/16\n", "9/17\n", "10/17\n", "10/18\n", "10/19\n", "10/25\n", "10/26\n", "\n", "2018\n", "9/3\n", "9/4\n", "9/5\n", "10/7\n", "10/8\n", "10/9\n", "10/10\n", "\n", "2017\n", "6/19\n", "6/20\n", "6/21\n", "6/22\n", "7/31\n", "8/7\n", "8/8\n", "8/9\n", "8/10\n", "8/23\n", "8/24\n", "8/25\n", "8/26\n", "8/27\n", "8/28\n", "8/29\n", "8/30\n", "9/9\n", "9/10\n", "9/11\n", "9/6\n", "9/7\n", "9/8\n", "9/9\n", "10/5\n", "10/6\n", "10/7\n", "10/8\n", "10/28\n", "\n", "2016\n", "6/5\n", "6/6\n", "6/7\n", "6/20\n", "8/2\n", "8/3\n", "8/4\n", "8/5\n", "8/6\n", "8/31\n", "9/1\n", "9/2\n", "9/13\n", "9/14\n", "10/6\n", "10/7\n", "10/8\n", "11/21\n", "11/22\n", "11/23\n", "11/24\n", "11/25\n", "11/26\n", "\n", "2015\n", "6/16\n", "6/17 \n", "\n", "2014\n", "7/1\n", "7/2\n", "7/3\n", "9/2\n", "9/3\n", "10/27\n", "\n", "2013\n", "6/5\n", "6/6\n", "6/7\n", "6/19\n", "6/20\n", "8/25\n", "8/26\n", "9/13\n", "9/14\n", "9/15\n", "9/16\n", "10/3\n", "10/4\n", "10/5\n", "\n", "2012\n", "6/23\n", "6/24\n", "6/25\n", "6/26\n", "8/5 \n", "8/6\n", "8/7 \n", "8/8\n", "8/9 \n", "8/10\n", "8/17\n", "8/18\n", "8/26\n", "8/27\n", "8/28\n", "8/29\n", "8/30\n", "10/22\n", "10/23\n", "\n", "2011\n", "6/28\n", "6/29\n", "6/30\n", "7/18\n", "7/27\n", "7/28\n", "7/29\n", "7/30\n", "8/7\n", "8/19\n", "8/20\n", "8/21\n", "8/22\n", "9/2\n", "9/3\n", "9/4\n", "9/5\n", "9/7\n", "9/8\n", "9/9\n", "9/10\n", "9/11\n", "10/24\n", "10/25\n", "10/26\n", "10/27\n", "10/28\n", "\n", "2010\n", "6/26\n", "6/27\n", "6/28\n", "6/29\n", "6/30\n", "7/1\n", "7/23\n", "9/6\n", "9/7\n", "9/14\n", "9/15\n", "9/16\n", "9/17\n", "9/18\n", "9/24\n", "9/25\n", "9/28\n", "9/29\n", "9/30\n", "10/11\n", "10/12\n", "10/13\n", "10/14\n", "10/15\n", "10/21\n", "10/22\n", "10/23\n", "10/24\n", "10/25\n", "\n", "2009\n", "8/16\n", "8/17\n", "11/4\n", "11/5\n", "11/6\n", "11/7\n", "11/8\n", "11/9\n", "11/10\n", "\n", "2008\n", "6/1\n", "7/20\n", "7/21\n", "7/22\n", "7/23\n", "7/24\n", "8/4\n", "8/5\n", "8/17\n", "8/18\n", "8/19\n", "8/20\n", "8/21\n", "8/22\n", "8/23\n", "8/29\n", "8/30\n", "8/31\n", "9/1\n", "9/2\n", "9/5\n", "9/8\n", "9/9\n", "9/10\n", "9/11\n", "9/12\n", "9/13\n", "10/6 \n", "10/7\n", "11/6\n", "11/7\n", "11/8\n", "11/9\n", "\n", "2007\n", "6/1\n", "6/2\n", "8/20\n", "8/21\n", "8/22\n", "8/15\n", "8/16\n", "9/3\n", "9/4\n", "9/5\n", "9/12\n", "9/13\n", "9/27\n", "9/28\n", "10/31\n", "11/1\n", "\n", "2006\n", "6/11\n", "6/12\n", "6/13\n", "8/29\n", "8/30\n", "8/31\n", "\n", "2005\n", "6/9\n", "6/10\n", "6/11\n", "6/28\n", "6/29\n", "7/5\n", "7/6\n", "7/8\n", "7/9\n", "7/10\n", "7/16\n", "7/17\n", "7/18\n", "7/19\n", "7/20\n", "7/24\n", "7/25\n", "8/22\n", "8/23\n", "8/25\n", "8/26\n", "8/27\n", "8/28 \n", "8/29\n", "9/7\n", "9/8\n", "9/9\n", "9/10\n", "9/20\n", "9/21\n", "9/22\n", "9/23\n", "9/24\n", "10/2\n", "10/3\n", "10/4\n", "10/5\n", "10/6\n", "10/17\n", "10/18\n", "10/19\n", "10/20\n", "10/21\n", "10/22\n", "10/23\n", "10/24\n", "10/27\n", "10/28\n", "10/29\n", "10/30\n", "11/18\n", "11/19\n", "11/20\n", "\n", "2004\n", "8/9\n", "8/10\n", "8/11\n", "8/12\n", "8/12\n", "8/13\n", "8/14\n", "9/4\n", "9/5\n", "9/6\n", "9/7\n", "9/11\n", "9/12\n", "9/13\n", "9/14\n", "9/15\n", "9/16\n", "9/20\n", "9/23\n", "9/25\n", "9/26\n", "9/27\n", "10/8\n", "10/9\n", "10/10\n", "\n", "\n", "2003\n", "6/29\n", "6/30\n", "7/1\n", "7/9\n", "7/10\n", "7/11\n", "7/12\n", "7/13\n", "7/14\n", "7/15\n", "8/14\n", "8/15\n", "8/16\n", "8/30\n", "8/31\n", "9/5\n", "9/30\n", "10/1\n", "10/2\n", "10/3\n", "10/4\n", "10/5\n", "10/6\n", "\n", "2002\n", "8/5\n", "9/2\n", "9/3\n", "9/4\n", "9/5\n", "9/6\n", "9/7\n", "9/12\n", "9/13\n", "9/14\n", "9/18\n", "9/19\n", "9/20\n", "9/21\n", "9/22\n", "9/23\n", "9/24\n", "9/25\n", "9/26\n", "10/11\n", "9/29\n", "9/30\n", "10/1\n", "10/2\n", "10/3\n", "\n", "2001\n", "6/5\n", "6/6\n", "6/11\n", "8/2\n", "8/3\n", "8/4\n", "8/5\n", "8/6\n", "8/19\n", "8/20\n", "8/21\n", "9/13\n", "9/14\n", "9/15\n", "9/16\n", "10/7\n", "10/8\n", "10/9\n", "11/1\n", "11/2\n", "11/3\n", "11/4\n", "11/5\n", "\n", "2000\n", "8/14\n", "8/15\n", "9/16\n", "9/17\n", "9/18\n", "9/21\n", "9/22\n", "9/29\n", "9/30\n", "10/1\n", "10/2\n", "10/3\n", "10/4\n", "10/5\n", "\n", "1999\n", "8/19\n", "8/20\n", "8/21\n", "8/22\n", "8/23\n", "8/29\n", "9/15\n", "9/20\n", "9/21\n", "9/22\n", "10/13\n", "10/14\n", "10/15\n", "10/16\n", "10/17\n", "10/29\n", "10/30\n", "11/14\n", "11/15\n", "\n", "1998 \n", "8/21\n", "8/22\n", "8/31\n", "9/1\n", "9/2\n", "9/3\n", "9/9\n", "9/10\n", "9/11\n", "9/24\n", "9/25\n", "9/26\n", "9/27\n", "9/28\n", "9/29\n", "9/19\n", "9/20\n", "10/22\n", "10/23\n", "10/24\n", "10/25\n", "10/26\n", "10/27\n", "10/28\n", "10/29\n", "10/30\n", "10/31\n", "11/3\n", "11/4\n", "11/5\n", "\n", "1997\n", "7/17\n", "7/18\n", "7/19\n", "7/20\n", "\n", "1996\n", "7/11\n", "7/12\n", "7/27 \n", "7/28\n", "8/19\n", "8/20\n", "8/21\n", "8/22\n", "8/23\n", "10/6\n", "10/7\n", "10/8\n", "10/11\n", "10/12\n", "10/16\n", "10/17\n", "10/18\n", "10/19\n", "11/19\n", "11/20\n", "11/24\n", "11/25\n", "11/26\n", "\n", "1980 \n", "8/6\n", "8/7\n", "8/8\n", "8/9 \n", "8/10\n", "9/5\n", "9/6\n", "9/21\n", "9/22\n", "9/23\n", "9/24\n", "9/25\n", "11/9\n", "11/10\n", "11/11\n", "11/12\n", "11/13\n", "11/14\n", "\n", "1981 \n", "8/16\n", "8/17\n", "8/18\n", "8/19\n", "11/4\n", "11/5\n", "11/6\n", "\n", "1982\n", "6/3\n", "6/4\n", "6/18\n", "9/10\n", "9/11\n", "\n", "1983\n", "8/15\n", "8/16\n", "8/17\n", "8/18\n", "8/24\n", "8/25\n", "8/27\n", "8/28\n", "\n", "1984 \n", "9/8\n", "9/9\n", "9/10\n", "9/14\n", "9/15\n", "9/26\n", "9/27\n", "9/28\n", "9/29\n", "\n", "1985\n", "7/22\n", "7/23\n", "7/24\n", "8/14\n", "8/15\n", "8/16\n", "8/28\n", "8/29\n", "8/30\n", "8/31\n", "9/1\n", "9/2\n", "10/10\n", "10/26\n", "10/27\n", "10/28\n", "10/29\n", "10/30\n", "10/31\n", "11/19\n", "11/20\n", "11/21\n", "11/22\n", "\n", "1986\n", "6/6\n", "6/24\n", "6/25\n", "6/26\n", "\n", "1987\n", "8/9\n", "8/10\n", "10/10\n", "10/11\n", "10/12\n", "10/13\n", "\n", "1988\n", "8/8\n", "8/9\n", "8/28\n", "9/2\n", "9/3\n", "9/7\n", "9/8\n", "9/9\n", "9/10\n", "9/13\n", "9/14\n", "9/15\n", "9/16\n", "10/19\n", "10/20\n", "10/21\n", "10/22\n", "10/23\n", "11/20\n", "11/21\n", "11/22\n", "11/23\n", "11/24\n", "\n", "1989\n", "6/26\n", "6/27\n", "7/31\n", "8/1\n", "8/2\n", "9/21\n", "10/13\n", "10/14\n", "10/15\n", "10/16\n", "11/30\n", "\n", "1990\n", "8/5\n", "8/6 \n", "8/7\n", "10/10\n", "10/11\n", "\n", "1991\n", "10/15\n", "10/16\n", "\n", "1992\n", "8/24\n", "8/25\n", "8/26\n", "9/29\n", "9/30\n", "\n", "1993\n", "6/19\n", "6/20\n", "8/10\n", "9/15\n", "9/17 \n", "9/18\n", "9/19\n", "9/20\n", "\n", "1994\n", "7/2\n", "7/3\n", "8/15\n", "8/16\n", "11/10\n", "11/11\n", "11/12\n", "11/13\n", "11/14\n", "11/15\n", "11/16\n", "11/17\n", "\n", "1995\n", "6/3\n", "6/4\n", "6/5\n", "7/30\n", "7/31\n", "8/1\n", "8/2\n", "8/3\n", "8/10\n", "8/11\n", "8/23\n", "8/24\n", "9/30\n", "10/1\n", "10/2\n", "10/3\n", "10/4\n", "10/5\n", "10/9\n", "10/10\n", "10/11\n", "10/12\n", "10/13\n", "10/14\n", "10/15\n", "10/16\n", "10/17\n", "10/18" ] }, { "cell_type": "markdown", "id": "innocent-basin", "metadata": {}, "source": [ "RI Dates in the GoM / Caribbean \n", "\n", "1980\n", "8/7\n", "\n", "1981\n", "11/5\n", "\n", "1982\n", "6/3\n", "6/4\n", "\n", "1983\n", "none \n", "\n", "1984\n", "none\n", "\n", "1985\n", "8/15\n", "8/29\n", "\n", "1986\n", "none\n", "\n", "1987\n", "none\n", "\n", "1988\n", "9/2\n", "9/3\n", "9/14\n", "10/21\n", "10/22\n", "\n", "1989\n", "8/1\n", "\n", "1990\n", "8/7\n", "\n", "1991\n", "none\n", "\n", "1992 \n", "none\n", "\n", "1993\n", "9/20\n", "\n", "1994\n", "none\n", "\n", "1995\n", "10/4\n", "10/10\n", "\n", "1996\n", "none\n", "\n", "1997\n", "7/18\n", "\n", "1998\n", "8/22\n", "9/2\n", "10/24\n", "10/25\n", "\n", "1999\n", "8/21\n", "8/22\n", "10/14\n", "11/15\n", "\n", "2000\n", "9/21\n", "9/22\n", "9/30\n", "10/1\n", "10/5\n", "\n", "2001\n", "10/8\n", "10/9\n", "11/3\n", "\n", "2002\n", "9/20\n", "9/21\n", "9/22\n", "10/2\n", "\n", "2003\n", "none\n", "\n", "2004\n", "8/13\n", "\n", "2005\n", "7/6\n", "7/8\n", "7/10\n", "7/16\n", "7/20\n", "8/28\n", "8/29\n", "9/21\n", "9/22\n", "10/19\n", "\n", "2006\n", "none\n", "\n", "2007\n", "9/13\n", "9/28\n", "\n", "2008\n", "8/30\n", "8/31\n", "11/7\n", "11/8\n", "\n", "2009\n", "11/5\n", "11/8\n", "\n", "2010\n", "9/17\n", "10/12\n", "\n", "2011\n", "10/24\n", "10/25\n", "\n", "2012\n", "none\n", "\n", "2013\n", "none\n", "\n", "2014\n", "none\n", "\n", "2015\n", "none\n", "\n", "2016\n", "11/24\n", "\n", "2017\n", "8/10\n", "8/24\n", "8/25 \n", "8/26\n", "9/6\n", "9/7\n", "10/7\n", "\n", "2018\n", "10/9\n", "10/10\n", "\n", "2019\n", "none" ] }, { "cell_type": "code", "execution_count": 9, "id": "38bd81d8-fd4e-4f02-9466-f02c4cc3e86d", "metadata": {}, "outputs": [ { "ename": "ValueError", "evalue": "can only convert an array of size 1 to a Python scalar", "output_type": "error", "traceback": [ "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", "\u001b[0;31mValueError\u001b[0m Traceback (most recent call last)", "Cell \u001b[0;32mIn[9], line 2\u001b[0m\n\u001b[1;32m 1\u001b[0m \u001b[38;5;66;03m# want the MJO phase at TC genesis for all storms IN GOM AND CARIB to calculate prob(TC gen & MJO phase x) \u001b[39;00m\n\u001b[0;32m----> 2\u001b[0m \u001b[43mstorm_dates\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m1980\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m1\u001b[39;49m\u001b[43m)\u001b[49m\n", "Cell \u001b[0;32mIn[8], line 19\u001b[0m, in \u001b[0;36mstorm_dates\u001b[0;34m(yearnum, stormnum)\u001b[0m\n\u001b[1;32m 17\u001b[0m j \u001b[38;5;241m=\u001b[39m np\u001b[38;5;241m.\u001b[39mwhere(np\u001b[38;5;241m.\u001b[39misclose(storm, stormnum))\n\u001b[1;32m 18\u001b[0m \u001b[38;5;66;03m# get arrays of day and month values in the year specified in the function argument\u001b[39;00m\n\u001b[0;32m---> 19\u001b[0m index \u001b[38;5;241m=\u001b[39m \u001b[43mnp\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43masarray\u001b[49m\u001b[43m(\u001b[49m\u001b[43mi\u001b[49m\u001b[43m)\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mitem\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 20\u001b[0m index_j \u001b[38;5;241m=\u001b[39m np\u001b[38;5;241m.\u001b[39masarray(j)\u001b[38;5;241m.\u001b[39mitem()\n\u001b[1;32m 21\u001b[0m \u001b[38;5;66;03m# go thru each storm in a year and determine whether it underwent RI, extract dates\u001b[39;00m\n\u001b[1;32m 22\u001b[0m \u001b[38;5;66;03m# for each storm, determine whether the wind speed at a track point is at least 56.0 km per hour = 15.555555 m/s more than \u001b[39;00m\n\u001b[1;32m 23\u001b[0m \u001b[38;5;66;03m# the wind speed at a track point <= than 4 away (4 track points = 1 day)\u001b[39;00m\n", "\u001b[0;31mValueError\u001b[0m: can only convert an array of size 1 to a Python scalar" ] } ], "source": [ "# want the MJO phase at TC genesis for all storms IN GOM AND CARIB to calculate prob(TC gen & MJO phase x) \n", "storm_dates(1980, 1)" ] }, { "cell_type": "code", "execution_count": 364, "id": "every-recycling", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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level_0index\"yearmonthdayRMM1RMM2MJO phaseMJO amplitudemean have been removed in these RMMvalues; 20140101-: Only the 120-day has been removed.\",,,,,,,,,,,
7085818316203NaN20181010-1.4072213-1.692191422.20086Gottschalk10_method:_OLR_&_ACCESS_wind ,,,,,,,,,,,
\n", "
" ], "text/plain": [ " level_0 index \" year month day RMM1 RMM2 \\\n", "7085 8183 16203 NaN 2018 10 10 -1.4072213 -1.6921914 \n", "\n", " MJO phase MJO amplitude mean have been removed in these RMM \\\n", "7085 2 2.20086 Gottschalk10_method:_OLR_&_ACCE \n", "\n", " values; 20140101-: Only the 120-day has been removed.\",,,,,,,,,,, \n", "7085 SS_wind ,,,,,,,,,,, " ] }, "execution_count": 364, "metadata": {}, "output_type": "execute_result" } ], "source": [ "MJO_nonzero = large_MJO.loc[(large_MJO['year'] == 2018) & (large_MJO['month'] == 10) & (large_MJO['day'] == 10)]\n", "MJO_nonzero " ] }, { "cell_type": "code", "execution_count": 4, "id": "senior-thought", "metadata": {}, "outputs": [], "source": [ "# MJO phase on RI days in the Gulf / Caribbean\n", "MJO_phase_RI_GoM = [1, 0, 4, 4, 0, 0, 1, 0, 0, 7, 7, 0, 0, 0, 0, 7, 0, 2, 8, 0, 0, 1, 2, 0, 8, 2, 1, 2, 2, 3, 5, 5, 0, \n", " 0, 0, 0, 0, 6, 2, 0, 1, 0, 0, 0, 0, 8, 8, 5, 5, 0, 2, 2, 0, 0, 2, 3, 0, 6, 2, 2, 0, 0, 0, 0, 2, 0, \n", " 0, 0, 1, 2] \n" ] }, { "cell_type": "code", "execution_count": 8, "id": "actual-health", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "0.10752688172043011" ] }, "execution_count": 8, "metadata": {}, "output_type": "execute_result" } ], "source": [ "val, count = np.unique(MJO_phase_RI_GoM, return_counts=True)\n", "val, count\n", "\n", "freq_0 = 34\n", "freq_1 = 6\n", "freq_2 = 13\n", "freq_3 = 2\n", "freq_4 = 2\n", "freq_5 = 4\n", "freq_6 = 2\n", "freq_7 = 3\n", "freq_8 = 4\n", "\n", "import matplotlib.pyplot as plt\n", "# plt.hist(MJO_phase_RI_GoM, bins = 20)\n", "# plt.xlabel('MJO Index')\n", "# plt.ylabel('Number of RI Days in the Gulf')\n", "# plt.title('Number of Gulf of Mexico RI Days by MJO Index, 1980-2019')\n", "\n", "prob_0 = freq_0/freq_0_TC\n", "prob_1 = freq_1/freq_1_TC\n", "prob_2 = freq_2/freq_2_TC\n", "prob_3 = freq_3/freq_3_TC\n", "prob_4 = freq_4/freq_4_TC\n", "prob_5 = freq_5/freq_5_TC\n", "prob_6 = freq_6/freq_6_TC\n", "prob_7 = freq_7/freq_7_TC\n", "prob_8 = freq_8/freq_8_TC\n", "prob_8\n", "\n", "RI_days_GoM_nonzero = freq_1 + freq_2 + freq_3 + freq_4 + freq_5 + freq_6 + freq_7 + freq_8\n", "storm_days_GoM_nonzero = freq_1_TC + freq_2_TC + freq_3_TC + freq_4_TC + freq_5_TC + freq_6_TC + freq_7_TC + freq_8_TC\n", "RI_storm_exists_nonzero = RI_days_GoM_nonzero / storm_days_GoM_nonzero\n", "RI_storm_exists_nonzero\n", "RI_days_all = freq_0 + RI_days_GoM_nonzero\n", "storm_days_all = freq_0_TC + storm_days_GoM_nonzero\n", "\n", "# baseline probability, unconditioned on MJO phase\n", "prob_RI_given_storm = RI_days_all / storm_days_all\n", "prob_RI_given_storm" ] }, { "cell_type": "code", "execution_count": 17, "id": "banned-discipline", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "Text(0.5, 1.0, 'Number of Gulf of Mexico RI Events by MJO Index, 1980-2019')" ] }, "execution_count": 17, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "\n", "MJO_phase_GoM = [0, 1, 2, 2, 2, 2, 2, 0, 4, 4, 0, 0, 0, 8, 5, 2, 3, 1, 0, 0, 5, 0, 7, 7, 0, 0, 6, 0, 0, 0, 6, 1, 0, 7, 0, \n", " 2, 8, 0, 0, 1, 2, 0, 0, 0, 8, 7, 0, 8, 2, 1, 2, 2, 3, 1, 5, 5, 0, 0, 0, 0, 0, 6, 2, 2, 0, 1, 1, 0, 0, 0, \n", " 0, 8, 8, 5, 2, 2, 2, 5, 0, 2, 2, 2, 3, 0, 0, 2, 3, 0, 0, 6, 6, 6, 2, 2, 0, 1, 8, 5, 5, 0, 0, 0, 0, 0, 0, \n", " 0, 2, 0, 0, 0, 0, 0, 8, 8, 1, 2, 0]\n", "\n", "import matplotlib.pyplot as plt\n", "plt.hist(MJO_phase_GoM, bins = 20)\n", "plt.xlabel('MJO Index')\n", "plt.ylabel('Number of RI Events in the Gulf of Mexico')\n", "plt.title('Number of Gulf of Mexico RI Events by MJO Index, 1980-2019')" ] }, { "cell_type": "code", "execution_count": 18, "id": "demographic-palmer", "metadata": { "scrolled": true }, "outputs": [ { "data": { "text/plain": [ "0.014280483339436104" ] }, "execution_count": 18, "metadata": {}, "output_type": "execute_result" } ], "source": [ "val, count = np.unique(MJO_phase_GoM, return_counts=True)\n", "val, count\n", "\n", "freq_0 = 50\n", "freq_1 = 10\n", "freq_2 = 24\n", "freq_3 = 4\n", "freq_4 = 2\n", "freq_5 = 8\n", "freq_6 = 6\n", "freq_7 = 4\n", "freq_8 = 9\n", "\n", "RI_given_0 = freq_0/len(MJO_phase0)\n", "RI_given_1 = freq_1/len(MJO_phase1)\n", "RI_given_2 = freq_2/len(MJO_phase2)\n", "RI_given_3 = freq_3/len(MJO_phase3)\n", "RI_given_4 = freq_4/len(MJO_phase4)\n", "RI_given_5 = freq_5/len(MJO_phase5)\n", "RI_given_6 = freq_6/len(MJO_phase6)\n", "RI_given_7 = freq_7/len(MJO_phase7)\n", "RI_given_8 = freq_8/len(MJO_phase8)\n", "\n", "nonzero_MJO_GoM = freq_1 + freq_2 + freq_3 + freq_4 + freq_5 + freq_6 + freq_7 + freq_8\n", "nonzero_MJO_days_GoM = phase1 + phase2 + phase3 + phase4 + phase5 + phase6 + phase7 + phase8\n", "RI_given_nonzero_GoM = nonzero_MJO_GoM / nonzero_MJO_days_GoM\n", "RI_given_nonzero_GoM\n", "\n", "GoM_RI_days = nonzero_MJO_GoM + freq_0\n", "GoM_MJO_days = nonzero_MJO_days_GoM + phase0\n", "prob_RI_GoM = GoM_RI_days / GoM_MJO_days\n", "prob_RI_GoM" ] }, { "cell_type": "code", "execution_count": 20, "id": "offshore-clark", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "169" ] }, "execution_count": 20, "metadata": {}, "output_type": "execute_result" } ], "source": [ "lat = NA_tracks.LAT\n", "lon = NA_tracks.LON\n", "\n" ] }, { "cell_type": "code", "execution_count": 4, "id": "marked-audio", "metadata": {}, "outputs": [], "source": [ "# Maloney and Hartmann (\"west of 77.5 W\")\n", "L = (lat<=31)&(lat>=9)&(lon<=360-77.5)&(lon>=360-98)" ] }, { "cell_type": "code", "execution_count": 159, "id": "unavailable-valuation", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 159, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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NiBgvnWgsHuUP4p8BsyTtAvwaOBL4yyHutR3wP4HtbR9S9tJ8g+1z2sXZ7omgZYt2O7ZvpPmjTbqLRkRXszs26dywfhBL2h74mu15ttdKOoFikNhU4Fzbdw5xr/MoZoH4dLl/D3ARRSIaUruFaa5v3Je0RbsyERH1J/oq9ApqZ7g/iG0vB+Y17F/V6twmtrV9saRPlmXXSuqrUrDSl7qk4ygaNJ4G+inXwiTTUEfEJFWxjaCb/F7SC3m+19DewJNVClb9df8PwO7tBpFFREwGNV2P4KPAFcDLJP0HMB14d5WCVRPBL4E/jCy2iIiacdFOUBflKOS3ltuuFLU2d9t+tkr5qongk8B/SrqJhsnmbH9keOFGRNRDnZaitN0n6TDbpwFDNSg3VTURnAX8iGIQWf9wbxIRUSfuUGPxOPsPSV+l6Cn0+4GDA1NcDKVqIlhbZbmziIjJok5VQ6WBhcM+23DMwP7tClZNBD8uew59j3Wrhn5bNcKIiDqpW68h2/uNtGzVRDAwmu2Tjfcl3UcjYhKy65cIJDWrtXkSWGx7yVBlq65HsMsI4oqIqK0adh+dU27fK/f/lGKair+V9O1yueGmqg4oe1+z47a/McxAIyJqoYZtBC8EXmP7KQBJpwDfAd4CLAZGlwiA1zW83phigZpbgCSCiJh0jOivX6+hnYE1DfvPAi+x/bSkIdeYr1o19OHGfUlbAucPN8qIiLqo3wMB3wR+Kunycv/twIXltNStlrcERj6B3B+AWSMsGxHR3WrYWGz7c5KuAt5EMbL4b20PLJrznqHKVm0jGFiXAIrlLXcDLh5ZuBERNVDDRwLgBcAq21+XNF3SLrYfaFeo6hNB47oEa4GHbC8bSZQREXVQtyeCsnF4DsVcQ18HpgH/l2JNhCFVbSO4vv1ZERGTg4H+/nolAoqVzl5N0ZEH28slbV6lYKVmcUnvknSvpCclrZK0WtKqkccbEdHFDFjtt+6yxrZ5fj2CTasWrFo19EXg7baXjiC4iIjaqeE4goslnQVsJelY4Bjg7CoFqyaCR5IEIqKn1CwR2P6ypIOAVRTtBP/d9sIqZasmgkWSLgK+y7qTzl06zFgjImpAdWws3gp4gqJH5z22Ky1TCdUTwRYUYwcObjhmIIkgIianmjwRSNoQmA/8GXA/RdvvSyRdRjGWYM0QxYHqvYb+egTB7UQxBcWLKRazmW/7dEnbUCycMBN4EDjC9u+Ge/2IiDFjcAd6DQ3xPfglipG/ayiWAv5r2080Kf8gsBroo1gXZk6T23yGoqvoTrZXl+U2B84A/lu5DWksJ9NYC3zM9p8AewPHS9oNOBm41vYs4NpyPyKiy6jC1lar78GFwB62XwXcw7pT/A+2n+3ZLZIAwLuAYweSAED5+kMUXUrbGrNEYHvFwBJpZVBLgR2Aw4AF5WkLKB5nIiK6iyts7S7R4nvQ9jW215an/RTYcRSR9tv+Q5N7P1UtypHPNTQskmZSDHS4CdjO9goo/pEkvWg8YoiIGJZqbQTbSlrUsD/f9vxmJw76Hmx0DEV1easorpFk4KwW17akrWn+iFJpjfmqcw1tBbyPol7/uTK2P1Kh7GbAJcBJtldJ1erdyqUxjwPYeeedK5WJiOiIgQFl7a0cosrmOYO/BxuOf5qi+uiCFkX3KUcIvwhYKOku2zcMOmdLivUGmgXc0SeCqygeX26nYoYBkDSN4sNf0NDV9BFJM8qngRnAo83KlplvPsCcOXNq0n4fEZNFpwaUtfgeRNLRwKHAAeWI4CYxeHn599GyF9BewA2Dzpk52hirJoKNbTdbD7MlFT/9zwGW2v6nhreuAI4GvlD+vbxJ8YiIidWZXkNNvwclzQU+Aby1Wf1+ec6mwBTbq8vXBwOfbXLei23/pk0cQ55TtbH4fEnHSpohaZuBrU2ZfYD3AvtLWlJu8ygSwEGS7gUOKvcjIrqK3H6roNX34FeBzSmqe5ZI+jcASduXawoAbAfcKOlW4Gbg+7avbnKPq5ocG9Y5VZ8I1gBfAj7N83VOBl7aqoDtG2ndv+qAiveNiBh/FXsFtb1M6+/Bpl/MZVXQvPL1/cCeFW6zZ5tJQEUx7URLVRPBR4GX215Z8fyIiBrrytlFm7I9dbTXqJoI7qSYYiIiojf0UBeVqomgD1gi6cesO+lc2+6jERG1VLl/ZP1VTQTfLbeIiMmv+jiCSaFtIpA0FXiv7QPHIZ6IiK5QsVdQV5H0JmDWwOL1wGZVFq9v233Udh/wB0lbdiDOiIh66MBcQ+OpXLz+Ezw/gd3A4vVtVa0a+iNwu6SFwO8HDqaNICKia4x48fqqieD75RYR0RNqWDW0xrbLCeo6v3i97QXlKjivKA/dbfvZ4ccZEVEDpiNTTIyzsV28XtK+FGsHPEgxSm0nSUc3mQUvImJyqNkTwXgsXv8V4GDbdwNIegVwIfDaEcQbEdH1alg1RPnFX+nLv1HVRDBtIAmUN7unnFo1ImJyqkkikLSaIaK1vUW7a1RNBIsknQOcX+6/h2IhhIiIyakmicD25gCSPgv8huJ7WhTf0x3tNfR3wPHAR8ob3ACcMcx4IyJqYRjTTHeTt9l+fcP+mZJuAr7YrmDVRPC35aIKjQsrnAicPqwwIyLqon69hvokvQf4FsXzzFEU88S1VXVhmqObHHt/xbIREbXToYVpxtNfAkcAj5Tb4eWxtoZ8IpB0VHmhXSRd0fDWFsDjIwo1IqIOuu+Lfki2HwQOG0nZdlVD/wmsALal6EI6YDVw20huGBHR9brzF/+QJH2dJunL9jHtyg6ZCGw/BDwk6UDgadv95RiCVwK3jzDeiIjuV7NEAFzZ8HpjirmHllcpWLWx+AbgzZK2Bq4FFgF/QdE9KSJi0lHNFqaxfUnjvqQLgX+vUrZqY7Fs/wF4F/Avtt8J7DasKCMieoyknST9WNJSSXeWvS2RtI2khZLuLf9u3aL8XEl3S7pP0snDvP0sYOcqJ1ZOBJLeQPEEMDALadWniYiI+unMegRrgY/Z/hNgb+B4SbsBJwPX2p5FUcuy3pd8uSjYGcAhFD+8jyrLNiVptaRVAxvwPYr1Cdqq+mV+IsViB5fZvlPSS4EfVywbEVEvHWostr2CosMNtldLWgrsQNG7Z9/ytAXAdaz/pb0XcJ/t+wEkfass94sW96o0iriZSk8Etm+w/Q7b/7vcv7/dojSSzpX0qKQ7Go6dKunXkpaU27yRBh4RMaaqPRFsK2lRw3Zcq8tJmkmxcMxNwHZlkhhIFi9qUmQH4FcN+8vKY62uf22VY80MmQgkndruAkOccx4wt8nx02zPLrer2l0/ImJCVEsEK23PadjmN7uUpM2AS4CTbK+qGEGzoc3rPadI2ljSNhRJaeuy/WGbMvFsX+VG7aqG/qasaxoq0COBU9eL1r6hDCQiolZE53oNlTM1XwJcYPvS8vAjkmbYXiFpBvBok6LLgJ0a9nekeXfQDwInUXzp39JwfBUV54RrVzV0NsXsda22zai4Ak6DEyTdVlYdNW0pB5B03MDj1mOPPTbMW0REjEKF6SWqtCFIEnAOsLScr23AFTw/dc/RwOVNiv8MmCVpl3KFyCPLcuuGap9uexfgv9repWHb0/ZXq3zcdgPK/rHKRYbhTOBzFI83n6MYrdx01Fv5iDUfYM6cOfUb2hER9daZb519gPcCt0taUh77FPAFiqUlPwA8TDEvEJK2B75me57ttZJOAH4ITAXOtX3n4BtI2t/2j4BfS3rXeh/j+aeQlsa1C6jtRwZeSzqbdUfCRUR0j870GrqR5nX9AAc0OX85MK9h/yqgXVvqW4EfAW9vFgLQXYlgoE6s3H0ncMdQ50dETJS6zDVk+5Ty5WdtP9D4nqRdqlxjzBJBObx5X4qW7GXAKcC+kmZTZKkHKRo5IiK6T00SQYNLgNcMOvYdKqwtXykRlBPNnUnR93UPSa8C3mH7f7QqY/uoJofPqXK/iIgJ5frMNSTplcDuwJaD2gi2oJh8rq2qU0ycTTGy+FkA27dRtGBHRExOnZliYjzsChwKbEXRTjCwvQY4tsoFqlYNbWL75qIn1HPWVg4zIqJmatRGcDlwuaQ32P7JSK5RNRGslPQyyhwo6d2U82dERExKNUkEDX4u6XiKaqLnqoSqLExTtWroeOAs4JWSfk0xiu3vhh9nREQNVKkW6r5EcT7wYuBtwPUUI5FXVylY6YmgnP3uQEmbAlNsV7p4REQdifpUDTV4ue3DJR1me4Gkb1IMRmur3eL1H21xHIBBQ6YjIiaNGiaCZ8u/T0jaA/gNMLNKwXZPBAPzW+8KvI7n57l4O8XylRERk1P9EsH8cv62z1B8V28G/LcqBSvNNSTpGuA1A1VC5dTT3x5FwBER3a1micD218qXNwAvBZD051XKVm0s3hlY07C/hoqPHBERtdOh2Ue7wGlVTqraffR84GZJl1HkyXcC3xhhYBER3a8eX/TttJrwbh1Vew19XtIPgDeXh/7a9s9HGllERLeryxQTbVRKZ1XnGtoZWAlc1njM9sMjiy0iorvVpOoHSbfT/AtfwHZVrlG1auj7DTd6AbALcDfFCLaIiMmlOweMtXLoaC9QtWrovzTuS3oNmUI6IiazmiQC2w+N9hojWo/A9i2SXjfam0dEdKOajiwesaptBI0jjKdQTG+aFeUjYtJSf+9kgqpPBJs3vF5L0WZwSefDiYjoAvVqIxi1qongF7bXGUks6XAyujgiJqlOVQ1JOpeiQfdR23uUxy6imLoHigVlnrA9u0nZBylmEO0D1tqeM8R9DgU+B7yE4rtdgG1v0S7GqiOLP1nxWETE5NC5aajPA+auc2n7L2zPLr/8LwEuHaL8fuW5LZNA6f8ARwMvtL2F7c2rJAFoP/voIcA8YAdJ/9zw1hZkhbKImMQ69URg+wZJM5veo5jK+Qhg/w7c6lfAHbaHHXm7qqHlwCLgHcDihuOrgb8f7s0iImqj2tfptpIWNezPtz1/GHd5M/CI7XuHiOIaSQbOanPtjwNXSboeeOa5C1RYLqDd7KO3ArdKusB2ngAioje48hQTKytU2QzlKODCId7fx/ZySS8CFkq6y3arJQA+DzxFsUzlhsMJol3V0MW2j6BYC3O9/Gj7VUOUbdZAsg1wEcXMpQ8CR9j+3XACjogYa+MxjkDSBsC7gNe2Osf28vLvo+Wkn3vRei2YbWwfPJJY2jUWn1j+PZRiMZrB21DOY1ADCXAycK3tWcC15X5ERPex22+jcyBwl+1lzd6UtKmkzQdeAwcDdwxxvX+X1PlEYHtF+fJDth9q3IAPtSl7A/DbQYcPAxaUrxcAfzb8kCMixl6n1iOQdCHwE2BXScskfaB860gGVQtJ2l7SVeXudsCNkm4Fbga+b/vqIW51PHC1pKclrZK0WtKqKjFWHUdwEPCJQccOaXKsne0GkovtFWW9V1OSjgOOA9h5552HeZuIiFHo4IAy20e1OP7+JseWU/TUxPb9wJ5V7iFpCjDX9n+MJMYhnwgk/V05xemukm5r2B4AbhvJDauyPd/2HNtzpk+fPpa3iohYj/rbb93Cdj/w5ZGWb/dE8E3gB8D/Yt36/NW2B1f7VPGIpBnl08AM4NERXCMiYsx10xd9RdeUaxRfOtyxBO0SwVRgFUXd0zokbTOCZHAFxci3L5R/Lx9m+YiIsWc60Rg83j4KbAr0SXqaYUwx0S4RLOb5mrLBa18aeGmrgmUDyb4UAy6WAadQJICLy8aSh4HD2wUYETER6jYNte3N25/VXLsBZbuM9MKtGkiAA0Z6zYiIcVOzRAAg6R3AW8rd62xfWaVc5YVpJG0NzKIYtQY810U0ImJSqePCNJK+ALwOuKA8dKKkN9luO16r6sI0f0MxuGxHYAmwN0W/2E5MlBQR0V3sOi5MMw+YXfYgQtIC4OdUGLhbdRrqEykyzUO29wNeTVYoi4jJrHPTUI+nrRpeb1m1UNWqoT/a/qMkJG1k+y5Ju7YvFhFRT3WrGqLo5v9zST+mqN16C/CpKgWrJoJlkrYCvksxA97vKKaojoiYfAzUrGrI9oWSrqOovRHwCdu/qVK2UiKw/c7y5allttkSGGrOi4iIeqtXHkDStbYPoBivNfjYkCr3Ghpg+/rhlomIqJu6VA1J2hjYhGLM1tY8P+ZrC2D7KtcYdiKIiOgFNeo19EHgJIov/cU8nwhWAWdUuUASQUTEYN3bK2g9tk8HTpf0Ydv/MpJrVO0+GhHRM4oBZW67dQNJr5P04oEkIOl9ki6X9M/lqpBtJRFERDTTX2HrDmcBawAkvYViTrdvAE8CQy12/5xUDUVENNEtv/grmNowE/RfAPNtXwJcImlJlQvkiSAiYrAqo4q7J09MlTTwo/4A4EcN71X6sZ8ngoiI9dRqrqELgeslrQSeBv4fgKSXU1QPtZVEEBHRTE2qhmx/XtK1wAzgmobVyaYAH65yjVokglXP3MkPH9iNraY8DcDmU9YAMH1q8f4Lp2y6zvlTXnzPuMYXEZOMO7dUpaRzgUOBR23vUR47FTiW5yfv/JTtq5qUnQucTrFa5Ndsf6FpuPZPmxyr/EWYNoKIiGbs9ls15wFzmxw/zfbscmuWBKZSDAg7BNgNOErSbiP8NENKIoiIaKZDjcXlAl7DXd8dYC/gPtv3214DfAs4bATXaSuJICKiCfX3t90o5vdZ1LAdN4xbnCDpNknnlnMEDbYD8KuG/WXlsY5LIoiIGMxUHVC20vachq3SAC7gTOBlwGxgBfCVJueoybExacGuRWNxRMR4EmM7hYTtR567l3Q20GyR+WXATg37OzJG68DkiSAiopnONRavR9KMht13Anc0Oe1nwCxJu0jaEDiShrUGOmlCnggkPQisBvqAtbbnDHX+Fhvtztt2WTQeoUVEFDr0RCDpQmBfivaEZcApwL6SZlNU9TxIMZU0kran6CY6z/ZaSScAP6ToPnqu7Ts7EtQgE1k1tJ/tlRN4/4iI5gbaCDpxKfuoJofPaXHucmBew/5VwHpdSzstbQQREU2UvYJ6wkS1ERi4RtLiVt2tJB030CXrsccea3ZKRMQYqdA+UJMpKKqYqESwj+3XUIyYO76cQ3sdtucPdMmaPn36+EcYEb3L9FQimJCqobIeDNuPSrqMYgTdDWNxr7fO+yIA/Rs9n/P6phXdc/unUf4t9vs2XPc4QN9G5d8N193v3+j5c9a+oPgPov8F5aPkJn0ATN1o7XPnbLzxs8VbGxbzJG220TMAbLNxMX/S1hv+4blzt5n2ewC2nfYUANtNKyYQ3Grq8+e8ctqjxblTi5gb51vKXEsRHdA7NUPj/0QgaVNJmw+8Bg6medepiIgJU5elKjthIp4ItgMukzRw/2/avnoC4oiIaG0SfdG3M+6JwPb9wJ7jfd+IiMps6OuduqF0H42IaCZPBBERPS6JICKihxmoz5rFo1aLRHDP4vs5aMrhACzs//YERxMRk5/BaSOYNK6/6uMTHUJE1I1JY3FERM9LG0FERI9LIoiI6GWTay6hdpIIIiIGM9BD01AnEURENJMngu7yzEs24Z7P7DXRYUREz8gUExERvc3gjCOIiOhxPTSyeKJWKIuI6G4dWqFM0rmSHpV0R8OxL0m6S9Jtki6TtFWLsg9Kul3SEkmLOvPB1pdEEBExmF30Gmq3VXMeMHfQsYXAHrZfBdwDfHKI8vvZnm17zrA/R0W1qxpacO8bn3s9pVxLbqrWz8zT9PwykYe/bPHYBxYRk0uHeg3ZvkHSzEHHrmnY/Snw7o7cbIRqkQi23/wJTn3rZRMdRkT0DOO+vionbjuoyma+7fnDvNkxwEUtA4FrJBk4awTXrqQWiSAiYlxVn4Z65WiqbCR9GlgLXNDilH1sL5f0ImChpLts3zDS+7WSNoKIiGbc334bBUlHA4cC77Gb10PZXl7+fRS4DBiTAVVJBBERgxhwv9tuIyVpLvAJ4B22/9DinE0lbT7wGjgYuKPZuaOVRBARMZjdsScCSRcCPwF2lbRM0geArwKbU1T3LJH0b+W520u6qiy6HXCjpFuBm4Hv27660x8V0kYQEdFUxcbi9texj2py+JwW5y4H5pWv7wf27EgQbahF1VRXkfQY8NBEx1HRtsDKiQ5imBLz2KtbvFDfmDe1PX00F5F0dXmtdlbaHjxGoHZqkQjqRNKisRz4MRYS89irW7yQmHtJ2ggiInpcEkFERI9LIui8MRn5N8YS89irW7yQmHtG2ggiInpcnggiInpcEkFERI9LIhgFSTtJ+rGkpZLulHRieXwbSQsl3Vv+3XqiY20kaaqkn0u6stzv9ni3kvSdciGPpZLeUIOY/778b+IOSRdK2rjbYm6xYErLGCV9UtJ9ku6W9LYuibflAi8THW+dJBGMzlrgY7b/BNgbOF7SbsDJwLW2ZwHXlvvd5ERgacN+t8d7OnC17VdSjLRcShfHLGkH4CPAHNt7AFOBI+m+mM9j/QVTmsZY/nd9JLB7WeZfJU0dv1CBYSzw0iXx1kYSwSjYXmH7lvL1aoovqB2Aw4AF5WkLgD+bkACbkLQj8KfA1xoOd3O8WwBvoRySb3uN7Sfo4phLGwAvkLQBsAmwnC6LuZzO+LeDDreK8TDgW7afsf0AcB9jNBNmK83itX2N7YFVqH4K7Fi+nvB46ySJoEPKFYheDdwEbGd7BRTJAnjRBIY22P8BPg40zpjVzfG+FHgM+HpZnfW1cibGro3Z9q+BLwMPAyuAJ8sVqbo25gatYtwB+FXDecvKY93kGOAH5es6xNs1kgg6QNJmwCXASbZXTXQ8rUg6FHjUdp3W7twAeA1wpu1XA79n4qtUhlTWqx8G7AJsD2wq6a8mNqpRU5NjXdP3vMkCL10db7dJIhglSdMoksAFti8tDz8iaUb5/gzg0YmKb5B9gHdIehD4FrC/pP9L98YLxS+5ZbZvKve/Q5EYujnmA4EHbD9m+1ngUuCNdHfMA1rFuAzYqeG8HSmquyZciwVeujbebpREMAqSRFF3vdT2PzW8dQVwdPn6aODy8Y6tGduftL2j7ZkUDWk/sv1XdGm8ALZ/A/xK0q7loQOAX9DFMVNUCe0taZPyv5EDKNqPujnmAa1ivAI4UtJGknYBZlHMkT+hhljgpSvj7Vq2s41wA95E8bh5G7Ck3OYBL6TocXFv+XebiY61Sez7AleWr7s6XmA2sKj8d/4usHUNYv5H4C6KFaXOBzbqtpiBCynaMJ6l+AX9gaFiBD4N/BK4GzikS+K9j6ItYOD/f//WLfHWacsUExERPS5VQxERPS6JICKixyURRET0uCSCiIgel0QQEdHjkghiXJQztT4gaZtyf+ty/yWSzpL0y3K2zhskvb48Z0dJl5czYf5S0umSNizfe7+krw66x3WS5pSvH5R0ScN775Z0nqS/lrSk3NZIur18/YXx+9eI6C5JBDEubP8KOBMY+ML9AsWygv+bYiKxWbZ3B94PbFsOxLoU+K6LmTBfAWwGfH4Yt50jafdBcXzd9mzbsylGmu5X7nf1tBURYymJIMbTaRQjbk+iGIx3KfB64DO2+wFs32/7+8D+wB9tf7083gf8PXCMpE0q3u/LwKc6+xEiJp8NJjqA6B22n5X0D8DVwMHArsCS8kt+sN2BxYPKr5L0MPDyire8GPiQpKrnR/SkPBHEeDuEYpqAPdqcJ5rPFjlwvNWQ+MbjfcCXKBcriYjmkghi3EiaDRxEsZrb3wOPA3tKavbf4Z3AnEHlt6CYUfKXZdnBSz1uA6wcdOx8ioVtdh5l+BGTVhJBjIuy8fdMijUbHqb4pf4hisnk/rF8H0mzJB1GMeHZJpLeVx6fCnwFOM/FLJM/A/aR9OLy/TkUE7s1LkaCi2mgTwNOGvMPGVFTSQQxXo4FHra9sNz/V+CVwBnAi4H7JN0OnA0sdzEb4juBwyXdS7Ee7R8pG39tP0Kx9vJVkpZQrLx21ECj8yDnkPawiJYy+2hERI/LE0FERI9LIoiI6HFJBBERPS6JICKixyURRET0uCSCiIgel0QQEdHj/j8gXKD+rGhtvgAAAABJRU5ErkJggg==\n", 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\n", 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5V0862ltT2U8lJ1vfB3zCzF4NLAI+JOk1wFLgbjN7JXB3+DpV550wM+1dOudczc0+tEoZP2OcbN3MdprZveHz54AHgA7g3cA14WrXEMT7T9XlnXNTDWjknHP14J5H0glDU5XJ1iXNBhYA64GXmtlOCC4OwEtitrlQ0gZJG3btKq0Lk4dscM41osGUmi8rPtm6pIOAVcBFZpZ4wJeZXW1mC81s4bRp05JuBnjIBuecK6Sik61LyhJk+teZ2c3h4ickTTeznZKmA0+OMe2xPGSDc64RtWbT6YhZNOMHCDP6RJl9jiQB3wIeMLMvRN66FXgfsCL8e0sp+03CQzY45xrRy6ZUuHFX0nOSno17JNj3icB7gZMlbQof7yTI8N8u6SHg7eHrVC1ZPIfWbCbt3TrnXE099OTuVPZTKB7/wQCSLgP+APwnQWC280nWq+e/yT+JC8BbS05pCXITFaxcvc1L/s45N0KSqp7FZnZC5PXXJK0HPluhNKWic0HH0AXgkq6tXLvusRqnyDnn6kOSloIBSedLykhqkXQ+MK66zCw8fCrZzPCbj0yLaG9NJ7a1c85Vw0sPnpjKfpJk/H8JnAM8ET7ODpeNGytXb6N/YHgH2IFBY9IBE9i+4lQmTfT2AOdc/fvj8+lMvZikO+d2gtG241Zc986e3j4WXHYnu/eOqxsY51yTSitIW9GMX9J3CEftRpnZ+1NJQRUU6t759J50rqDOOTdeJGncvS3y/ECC2D07KpOc9HR19wz16vFYnc45t1+Sqp5V0deSricI21C3urp7WHbz1qGwDR6d3znXCGo5EcsrgVmpHL1CPFaPc64RVbOO/zmGF5r/QBCfv255rB7nXCNKq8SfpKqn6CjdeuOxepxzjahqUy9KujvJsnrisXqccy5ebIlf0oFAG3BYOC9u7h7jEGBGFdI2ZiNj9WQkBszo8DsB55wrWNXz98BFBJn8vZHlzwJfqWCaUhGN1RN15LI7Urtdcs658ahQdM4vAl+U9BEz+1IV01RRnuk755pdoaqek83sp0CPpDNGvh+ZUWtciavumdKWpW3iBHb09jG5NcvuvftGxfdxzrlaOuSAdNouC1X1vBn4KXBanvcMGJcZ/0lHTcsbovnUY6ZzeefcodfRkb+FtGZb6OsfTD2dzjk30sGt6UTnLFTVc2n49DIz+130PUlHpHL0Gljz4K7Y5bnMfkdvHzPaWznpqGlct+6x2JG/Gckzfedc1aQ1RinJyN1VeZb9IJWj10ChSJ3Lbt5KT28fFr6+tkCmD95e4Jyrrhnt6cy5W6iO/yjgaGDyiDr+QwiCtY1LcYO7gtK7h3lwztWvJYvnpLKfQiX+OcC7gHaCev7c41jgA6kcvQbyDe4SXnp3ztW/fF3Ux6JQHf8twC2SXm9m96RytDrQuaCDDY8+Nazu3ggy/yRZv4ADvUHXOTeOJYnH3y3pQwTVPkNVPONpIpaR1jy4a1QmnzTzv/Lc+QDDwj6nJenFxznnypGkcfc/gT8DFgM/B14GPFfJRFVaXAOvEfTzLyQ3IviKM+YWXbdUuYuPc85VUpKM/xVm9ilgt5ldA5wKzC2yTV2LaxnvaG9l7dKTOfHIqXnfjy7vXNDB2qUnc9W588m2FM6uJchmhq8Tt0WxzN8vDM65ciXJ+HOT0vZKei0wGZhdsRRVQb4G3tZsZqjF/LoPvH5U5n/ikVO57gOvH7WvzgUdFAuRbQZYMDpYBBeYXJVR3vWBzIiLSaZFXHXufK48d35qMbmdc+PLJV1bU9lPkjr+q8PonJcAtwIHAZ9K5eg1Eo3emRustWTxnGEt5vky+Xy6unvYmyC0Q/+g0TZxAt2fPmVo2Sdu3Bzbm+i842dy2+ad9PYF191DDpwwLO2VaGNwztW369c/PizCwFglmYjlm+HTXwAvB5B0ZtlHrrG46J2lWrl6W+J1R7YtFOpCetvmnby4b3/Poaf39LPs5uBqn0v3RTdsKiGlzrnxrmpTL8a4kvwjehvSyFAOuSqhJLF8oka2LRSaHyBX0o/q6x/gohs2sfzW++kf8O6kzrmxGWvG3zSVzF3dPcOqVXp6+1hy02YQJUXvjLYh5CxZPGdMpfZ8FwXnnEsqSeNuPuOqu3lXdw8nrvgpRyy9nRNX/JSu7p7E265cvW1UXXr/oJWU6Xe0t3LFGXNHVS11LuigLTvWf4Fzrtmk1a+jUKyereTP4AW8NJ3DV16+EvvIuvJCyo2GJ2Dt0pPzpmvl6m3s8RHAzrmE0oosU6iq513pHKK28pXY+/oHWLl6W6KMPy6oW1L5xgyMvBilKTeozOcWds7Fia1nMLNHCz2qmchyxJXYk5bklyyeU3SAFgQDtPKt19PbN6p6Kd/FKA2ZFrFk8ZzYQHRj1TQNOs7VufbWbCr7afgK5rhRuiXFtS6S82UkVp41j3OPn5l31Vz1Ui7zL7X6SMArXzKp6Hq5f2bngg7OPK5jaKBXRiqrUebKc+fT6m0RztXc8tOPTmU/Df9rLjZKt5iVq7cVbMhtzWb4/Dnz6FzQkTf4W06ueglKn0zBgEd27Sm6Xv+gsXL1Nrq6e1i1sWeoz2+hvr/FRgF3tLeGsYmOKSnNzrn61fAZfzSgWi5cQr4eNnEKlc5H7qtYST73fr6LUTFJB27s6O1LXJXUms1w3gkzY9MSvUAWO1/ZjFK7DXXO5VfKgNFCivbjl/Qu4F+Bw8P1BZiZHVJku28TNBA/aWavDZctJ5jEJTfx7SfN7I4xpz6hckbpxjXu5gK6JVk3+n4uPbA/ZER7W5YX+wdS6eEzo701UVVSRhq6aC08fOrQYLSMxIAZHXnCWBTSP2BIDG3vnEtfWnPuJhnAdRVwBrDVrKRf9HeBLwPfG7H8SjP7XAn7qakli+eM6oETV1W0ZPEclvxgc96qoWxGw7aJuxiV0+Mnl64kI4oHzYaOn/TCeOKRU1n78FOx7z+9xweWOVdJk6vYuPs4cF+JmT5m9gsgPpcYJ/JVFZ15XAcrV28bNSCsc0EHkybmv5ZOmjghUeY68nhJI3FGS/BJqpLGMmlz0sB1zrnKSCtUS5IS/z8Bd0j6OfBibqGZfWGMx/ywpL8CNgCfMLOn860k6ULgQoBZs2aN8VDpiJaIiw0IeyYmnELc8mLHO2Lp7Ym2GTAbqv+LViX19PaNmtmrlMbtkQrFF3LOVdbuvel0A09S4v83YA/BtIsHRx5j8TXgSGA+sBP4fNyKZna1mS00s4XTpk0b4+HSV2hAGMSXpNvbxnaLVkrJvKe3j4tv2DQsZreAtomZoW6mGYljZ00edcdSKKxF9L09e/eV1CMgI3HBolmJxkI456ojSYl/qpmdUny14szsidxzSd8Abktjv9VUbEBYXD3/8y/so6u7p+RG5pOOmsa16x5LvL4B1657jOt/9TgDg0EaoqWEAbNh9fQ9vX0s+cFmsKA7aG5Z7i4Ghsf+L6UeX8Dnz5kHwPfXJ/8Mzrn8qjmA6yeSUsn4JU2PvHwPcF8a+62mYgPC4ur5c33sS7XmwV3FV8ojl+kn0T9gQ5l+Tu4uppxRxucvmkXngqA9pITkOOdiVHMA14eAH0vqk/SspOckPVtsI0nXA/cAcyT9XtLfAp+VtFXSFuAk4OKyUl8DSQaExdXnj6UrVrFxBJXU09s35u5j7a3ZoZmC0uqC5lyzS2PyKCiS8UtqAd5hZi1m1mpmh5jZwcX68AOY2XlmNt3Msmb2MjP7lpm918zmmtkxZna6me1M5VNUUZIBYamEiSiyTa6ffSWJsbdNRC9+Y/nczrnh0pxrW8V6aUq6x8xq2o9v4cKFtmHDhlomoSSXdG0tWC8/pS2LWZA55pvvNypfv34RVKNc3jmXV3/qv+grc+BXNqPYsBTtrVle3Dc4ahzDmcd18MN7ewr2MohenJbctHlUdZJzLrkTj5xacpdqSRvNbOHI5Umqeu6UdKaU4uWmwRWrl396Tz+9ff0YowO4jZQLuBY9+Qas2hj0xHkhYabfmm0ZukO5YNGsYXcsK8+aF7vdM339eccxrHlwF3v2DhScSCbaSLzy7Hke0sG5Mmz/U3pVpkl69XwcmAQMSOojYciGZlZqnXax+QFu37JzVPC33DZJ5wuYOumAvBPC5MSN9p0RBmmLG8ewp3+QbEZMmjghdp7gT9y4mc+fM49Nl+7vI3D0p3+cWp9k55pBmuNnipb4wzr9lrCuPnEdfzMbS5123MWiq7sntgvljt6+xAHfil2MkkYxzTsV5YAx6YD4MsSA2ajxBZ7pO1caQUnTxhaSaCyOpNMlfS58NMTMXJU0luibcReLQl1Ac6XxaFVMnGKNtEmjmBYax1Co8cmA69Y9ltoX17lmY1Q3OucK4HXAdeGij0l6o5ktTSUFDSI3h+6O3j5mhPXgt2/ZmWjAU6EQCoVK6tGQybkM+lX/cgd78zTU7n5xX8H05hqYoxl9bsRudJ24qqUkVU4GXHTDJlau3kZbtsXnG3auRGlV9yQp8b8TeLuZfdvMvg28I1zmQrl6757evqEG21Ube7j0tKO56tz5Q/3tcyXiKW1Z2luzieYHiA0B0ZrNu02+TH/k8nzpHdnAHLfOSUdNyzutY0+REn9UT29fwcltnHOVlaRxF6Cd/ZE2J1cmKeNXofg9a5eeXNagi7iw0OWM4EsyAX3cOmse3MUVZ8zNGwCulDj83rXTudpJUuK/AuiW9F1J1wAbw2UuVO6E7oWUO4NYVLE5f6PLC63TuaCDtUtPpqO9Ne9Uk2kONHHOpa9oid/Mrpf0M4J6fgH/bGZ/qHTCxpNC9d5pKGcGsahciT5Jeie3ZvN2z4xOBBF3cRg0Y/uKU5mdMKS0c666ipb4Jd1tZjvN7FYzu8XM/iDp7mokbrwod0L3NBUaJFVozt+R6Y0rtEeXFwtNUelYQi74f/t5bh5p/a9jM35JB0qaChwmaYqkqeFjNjAjlaM3iDSrY8pVqO4/GkG0WHp7Y3ojRZcXu4AsWTynYBdTV75n+vrH1H3YjU8nHZXO3CSFqnr+HriIIJPfCEO/4WeBr6Ry9AaSVnVMGunY8OhTXLfusYKzbhVLb5LqoJGTxue6fAJD3UDbJmZ8sFYF5cZyQPzoa9c4xhqmfaTYjN/Mvgh8UdJHzOxLqRzNVcXlnXNZePjUvP30k8o3oczICeNh9AVkZEiH3XsHCgaBc+WJjuUARvUAc40lrRDnsRm/pNcBj+cy/XCe3DOBR4HlZjbuJ1JvZKncgYzMqxPk3XEhHTJSSd09XXFif4bf1d3DJ27c7Oe4waXVYaRQVc/XgbcBSPpzYAXwEYL5cq8GzkolBa4urVy9bVRf++gsYnF3E3ElkgGzUZO+u/LkzmVXdw9LbvJMv9Gl2WGkUK+eTKRUfy5wtZmtMrNPAa9I5eiubsVl4LkRvNERvRfdsInZS29n9tLbYzP2jvZWzl80q2LpbWafvHlL3Q6I277i1IKhu11yx86aXJUZuDKScncEbwV+Gnkv6YhfN07F3VJmpDHVIe9+cR8LD5/qMflTNnvp7XUb8ygj0dXdwwHe4ygV//PwU1WJznk98HNJtwB9wC8BJL0CeCaVo7u6FddVc6zVCb19/Sy7eWveQWGuMeXCcScJVOiKq0p0TjP7t3Cg1nTgTts/R2MLQV2/SyAuCma9i+uqWU6Xwb7+ASTwqujaSNrAns2IgQEjjfsI/1enK63uugWrbMxsXZ5lv03lyE1gZNfG6FSE4yXzz5fOcroMeqZfO4e0TuDUY6azamPPqP/fpIkZ9uwdYEZ7KycdNY0bfv04g5EuuJkW0YIH12sU3upSQYWiYI5X0VG/hfiI3drKd/6f3tPPqo09HDtr8qj3Bw2uPHc+a5eezJoHd40adzEwaBx0oDftNQrP+CuoklE7aykXnXP7ilO5YNGsUdE4MxJvOHJqjVLnprRlY6tY+voHWPfI07FzOEP897N3T3/BC/6UIrO8ufKlFfnWM/4KKhbErBFc3jmXz58zb1hD8IAZ9z72jJf6a6CjvTU2zlJOXD1/LsMv9L2Na/S/6tz5dH/6FC5YNGvU/z2bEdkW/zak4bwTZqayH8/4K6ieonbmplE8YuntnLjip6O6hZXzflyVltcGV19uesxC4kqNue0KfW+LBfi7vHMuV4azzuXeX3nWPFaePW9oWdwlwOdxKOyCRbO4vHNuKvvySrsKiusZU+2G3WKNzOW+P96rrhrFlLZs0Zg9rdkMZx7XMaqBN1ogKfa9LRYOJO79aHiJfLPK5UtXVEZi0KxpCxRpZfrgGX/F1UPUzmJTLZb7flwkz/bWLC/uG/SgYSmb0pblhf7BURnnpacFIblHRuvMdePsiGTgxYL4VfJ7W+jCsvDwqXzmR/eP6vvfms0M3VkcueyOmoSnaFHQCF4rl3Rt9RK/S65YI3O57xebFzjfDzkf7+NfXDSDLyfjTpqxpzEOJW4fcftpmziBp/f0D7tgnXTUNFau3sbFN2yqSajv3IUn7ruckTjvhJnctnlnxQYpXrvuMSCdkr9n/E2gWGz9ct9PUjUQ/fFPbs2ye+++YV0GBZx/wiwWHj7Vo0zG6MhzXospJ+NOYxxKKfsYue6AGa3ZDCcdNW1YFdDuvQNkWsTgYFDtU2xgWmu2hb4wrMWUtmzsWIY40fN+8Q2b8q4zYFbSPsfq+vWPp5Lxe+NuE0gyU1Y578P+Lp6/W3Eqa5eePOpHHX1/06WncO7rZg5r5DNg1cagwXjQM/1hOtpb2R5zXgvJZaTRgHrLbt6aON5LGuNQStlH3LrXr3981PKBQWNGeF4evuKdsd1Mg8bnY4YaltsmTmDh4VNHNVBfsGjWqO94vqbmyTGxpiSqUqWZVoHIS/xNIEmJvJz3i8lX6lzz4K7YvuTtbdmmi+/SAmQntPDivtGBEnY808fspbePKvEXU6xtppg0xqGUso9CIb2L7SOuuvGko6blveO44oy5rF168rD95do9enr7hoUQj96lxHU8qlZZJa2eT57xN4ly63xLaeyLZvTtbVmef2Hf0FD/3I8ornSUqwpqJu2tWZaffvRQldjIeuRcplJqVUu5GXeS6Tfj5L4Dcflhvn3EHS+uKifJNKClXPxyr/NVNea2KTZGotLS6sfvGX+NjNfgbcWMrKfNV3Lv6x8o+GNuhu6h2YxYeda8vJnPytXbYu94Simxl5NxQ3wputg4lHzdNaPi9hF3vGNnTWbtw6Mn/Bs58Xi+wklcnXy+85JLd6E7jLhzWmm5xuO0evV4HX8NlFv3WgvFBnjl5Cth5ZNruIvKZQiNNLI5Tv+AxdaVF7vwJb0wljuAsNhgrTiFvgOF9hF3vO1/yv95k0w8HvddEoz6Dhf77saNXC7VlLZs4n0IhtoxvB//OFdu3Wu1ldIzI2mm1BG5Fc931zPeJw0X0FKkt0ncuSpWqkx6YUxjAOFY+vPHfS7BqHr1JMeLK7Un+a4tWTyHi2/YlHf66JG/t0L7i45cBlh+6/1j7rb5Yv8Aff2DiaYirVQhyDP+GhhvwdtKuVAluRWO/ogKjfDMZVjFMtB609HeytqlJxet8oj7Ueer8sgpNeRHLQYQllvFlOb+Ohd0cFHCC0ehNoboXUquOm6sGX9uxrShCU4KDAwbWZ2VlopV9Uj6tqQnJd0XWTZV0l2SHgr/TqnU8etZPQVvS1KFU8qFKt+tcDYj2luzJVUXRLt/jgwCV89Ghj644oy5eaebLJSBjwx9nevJkfTc1VraMarK3V9cV8+Rv7e443z+nNFtMWkW0gYtPn5Rkuqssahkif+7wJeB70WWLQXuNrMVkpaGr/+5gmmoS2NtNEtb0iqcUkpclYhPlG+fsw9tZd0jTzNgRkZi0cunsP1PfTVpeMvJ190yV+IutTG/HkJ9jFXa34Fy95f091bKcdJu5I27n63U91lWwVtoSbOB28zsteHrbcBbzGynpOnAz8ysaG63cOFC27BhQ8XSWQv10KvnxBU/zfvFylVV5MQF1arH0me+tCapSx2rKW1ZLj3t6Lo7D264tH9vxarx0tIieOSKU8e8vaSNZrZw5PJq1/G/1Mx2AoSZ/0viVpR0IXAhwKxZs6qUvOqpZIku6Zc8aRVOvUQZTSJfWkcO+S9H7iJS6mAqV1tp/95Gfs/yhSHJRRxd8+Cu2HWKqVRQuLpt3DWzq4GrISjx1zg540YpPXBKrcIZL5lcvrRGo1GO9cuUkfLW97rmNPJ7lqTA1dXdU1aPoLRUO+N/QtL0SFXPk1U+/rhUym1qKT1w6qWtoRqiP9LZS28veftsi1h5tmf6Ll6SwlFcm09cXX6l5qapdsZ/K/A+YEX495YqH3/cKTVCYik9cMZTFU4tRUMqOJeGkReJuMJIpZpgK5bxS7oeeAtwmKTfA5cSZPg3Svpb4DHg7Eodv1GUOtir1D7P46kKp1Y2XXpKrZPgGlxHzO+20OT25ahYP34zO8/MpptZ1sxeZmbfMrM/mdlbzeyV4d/RATgaXNLQBzmlDvaqp3l+G0G+PvjOpa3av9u6bdxtRGOZ2GIsJXjw6ps0ZFs0NIuYc5VU7d+tZ/xVNJYYPWNpgPXqm7HrCKOD+gXTVVs1f7ee8VfRWGL0eAk+fXEhoTNS0SBizjUCz/iraKzBprwEn664gG/jKRCcc+XwePxV5A2v9aHQ/KzONQPP+KtorBNbuHT5Bdg1O6/qqTKvtqk9bzdxzc4zfteU/ALsmplX9TjnXJPxjN8555qMZ/zOOddkPON3zrkm4xm/c841mYrOuZsWSbuAR2udjhiHAX+sdSIK8PSVx9NXHk9f+cpJ4+FmNm3kwnGR8dczSRvyTWZcLzx95fH0lcfTV75KpNGrepxzrsl4xu+cc03GM/7yXV3rBBTh6SuPp688nr7ypZ5Gr+N3zrkm4yV+55xrMp7xO+dck/GMvwBJMyWtkfSApPslfSzy3kckbQuXfzZcNltSn6RN4eP/1iJ9km6IpGG7pE2RbZZJ+t8w7YvrKX3VPn9F0jhf0rowHRskHR/Zph7OYd701dF3cJ6keyRtlfQjSYdEtqmH85c3fTU4fwdK+pWkzWH6PhMunyrpLkkPhX+nRLYp//yZmT9iHsB04Njw+cHAb4HXACcBPwEOCN97Sfh3NnBfrdM3Yp3PA58On78G2AwcABwBPAxk6ih9VT1/Rf7HdwJ/ES5/J/CzejqHBdJXF99B4NfAm8Pl7wf+tc7OX1z6qn3+BBwUPs8C64FFwGeBpeHypcB/pHn+vMRfgJntNLN7w+fPAQ8AHcA/ACvM7MXwvSfrLH0ASBJwDnB9uOjdwP8zsxfN7HfA/wLHUyFjSF/VFUijAblS6mRgR/i8Xs5hXPqqqkD65gC/CFe7CzgzfF4v5y8ufVVlgefDl9nwYQTn6Zpw+TVAZ/g8lfPnGX9CkmYDCwiuyK8C3iRpvaSfS3pdZNUjJHWHy99Uo/TlvAl4wsweCl93AI9H3v89kYy4DtIHNTp/edJ4EbBS0uPA54Bl4Wr1cg7j0gf18R28Dzg9fOtsYGb4vF7OX1z6oMrnT1ImrO58ErjLzNYDLzWznRBcvICXhKuncv48409A0kHAKuAiM3uWYOayKQS3ZEuAG8PS605glpktAD4OfD9at1nF9OWcx/DStPJsXvH+vCWkrybnLyaN/wBcbGYzgYuBb+VWzbN5Lc5hXPrq5Tv4fuBDkjYSVLHsza2aZ/NanL+49FX9/JnZgJnNB14GHC/ptQVWT+X8ecZfhKQswRfmOjO7OVz8e+Dm8DbtV8AgcFh4+/UnADPbSFD/9qoapA9JE4AzgBsiq/+e4SWbl1HhKoJS0leL81cgje8Dcs9vYv/tdL2cw7zpq5fvoJk9aGanmNlxBBf3h8PV6+L8xaWvVt/B8Hi9wM+AdwBPSJoepn86wd0ApHX+qtWIMR4fBFfX7wFXjVj+QeCy8PmrCG69BEwjbGgBXg70AFOrnb7wvXcAPx+x7GiGNww9QmUb1kpNX1XPX5H/8QPAW8LnbwU21tM5LJC+uvgOsr/DQ0v4/vvr7PzFpa/a528a0B4+bwV+CbwLWMnwxt3Ppnn+KvJhGuUBvJHgNmoLsCl8vBOYCFxLUE94L3ByuP6ZwP3hP+Ze4LRapC9877vAB/Ns8y8EpZhthL1C6iV91T5/Rf7HbwQ2hmlZDxxXT+cwLn318h0EPkbQg+a3wArCKAF1dP7ypq8G5+8YoDtM333s7+F2KHA38FD4d2pkm7LPn4dscM65JuN1/M4512Q843fOuSbjGb9zzjUZz/idc67JeMbvnHNNxjN+V5SkfwkjB24JIxaeEC6/SFJbFY4/W9J9FT7G/0SO9Zdj2P6vJX25xPV3Sfpm+Potkp4JQwVsk/QLSe8qNR3VJGm5pJ5IJMtNktolvUnSbyr9P3Nj5xm/K0jS6wkGlBxrZscAb2N/rJCLgJIyfkmZVBOYEjN7Q/h0NlByxj9GN5jZ30Ve/9LMFpjZHOCjwJclvbXcgyhQqd/6lWY2P/LoNbNfEvSVd3XKM35XzHTgj7Y/EukfzWyHpI8CM4A1ktYASDpPQXzz+yT9R24Hkp6XdJmk9cDrw9f/IWmjpJ9IOl7SzyQ9Iun0fInIR9JbwxLyVknflnRAuHy7pM9Iujd876hw+TQFsc3vlfR1SY9KOiyXxnC3KwgC8G2SdPHIkryk2yS9JXz+N5J+K+nnwImRdaZJWiXp1+Fj6L2kzGwTcBnw4UL7jPtM4Z3LA5K+SjAQaaakJeG2WxTGfQ/3cYGCmPCbwn1kwsd3w//lVkkXl/oZXB2r5Kg0f4z/B3AQwWjH3wJfJYxhHr63nSBGEQQXgccIhqBPAH4KdIbvGXBOZDtjfyz5HxLEls8C84BNedIwmxEx0oEDCe48XhW+/h5BAK5cuj4SPv9H4Jvh8y8Dy8Ln7wjTkUv/8+HftwC3RY7z18CXI69vC9eZHvm8E4G1ufWA7wNvDJ/PAh7I85lG7nfYccNl83Pbxu0z7jOF52wQWBS+dwrBpN0iKPDdBvw58GrgR0A2XO+rwF8BxxFEisylpT3PZ1hOENJgU/hYU+h/5o/6eUzAuQLM7HlJxxGEUD4JuEHSUjP77ohVX0cwGcguAEnXEWQsXcAAQZCsnL3Aj8PnW4EXzaxf0laCDCOJOcDvzOy34etrgA8BV4WvcwHMNhIEg4Ng+P57ws/1Y0lPJzxWPicw/PPewP5gXm8DXiMNBVI8RNLBFsSDL0U0EmPefVL4Mz1qZuvC56eEj+7w9UHAKwlCBhwH/DrcdytBQLAfAS+X9CXgdoKLcz5XmtnnSvxcrsY843dFmdkAQdTAn4WZ8/sIYu1E5QsXm/NCuI+cfguLhQSl0lw10qCCqJ1JFDoeuX0SXHRy+yy2TT77GF4lemDkeVy8kxbg9WbWN4bjRS0gCMYWu09FrgR57I6uClxhZl8fsf1HgGvMbBkjSJoHLCa4oJ5DEMrYNQCv43cFSZoj6ZWRRfOBR8PnzxHEMocgUNibw/rlDEGs/Z9XMGkPArMlvSJ8/d4Ex/tvggwMSacQzKkwUvQzQVBtNF9Si6SZ7A/PvB54i6RDFYT9PTuyzZ2EdfPhseYn+UBRko4BPgV8pcg+k3wmgNXA+xXEpUdSh6SXEAQAOyt8npvr9fCw7aPFzFaF6Ti21M/g6peX+F0xBwFfktROUPr9X+DC8L2rgf+StNPMTpK0DFhDULq8w8xuSTEdcyT9PvL6YuBvgJvCu4RfA8Umxv4McL2kcwkuEjsJMvqoLcA+SZsJ7mquAn5HUCWVi8aKme2UtBy4J9zPvUCux9JHga9I2kLwG/sFQSjvYt4kqZugp9STwEfN7O4i+4z7TAdFd2xmd0p6NXBPeJPwPHCBmf1G0iXAnQp6/vQTlPD7gO9of2+gUXcEoYslXRB53Wlm2xN8VldDHp3TNY2w18+Ame1T0E31axbMfFSLtPw1sNDMPlxs3SL7qZvPFKVgmsPbzKzQbFKuRrzE75rJLIJpMlsIGpg/UMO09AF/IembNrwvf6nq6TMBoGCe2q8Cf6x1Wlx+XuJ3zrkm4427zjnXZDzjd865JuMZv3PONRnP+J1zrsl4xu+cc03m/wNZkZTczTzFZQAAAABJRU5ErkJggg==\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "NA_tracks.where(L).plot.scatter(x='LON', y='LAT')" ] }, { "cell_type": "code", "execution_count": 163, "id": "multiple-irish", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 163, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "NA_tracks.plot.scatter(x='LON', y='LAT')" ] }, { "cell_type": "code", "execution_count": 130, "id": "grand-greek", "metadata": {}, "outputs": [], "source": [ "def RI_dates(yearnum):\n", " RI_first_day = []\n", " RI_second_day = []\n", " RI_first_month = []\n", " RI_second_month = []\n", " year = NA_tracks.YRT.values\n", " storm = NA_tracks.ZSTORM1.values\n", " i = np.where(np.isclose(year, yearnum))\n", "# j = np.where(np.isclose(storm, stormnum))\n", " # get arrays of day and month values in the year specified in the function argument\n", " index = np.asarray(i).item()\n", "# index_j = np.asarray(j).item()\n", " # go thru each storm in a year and determine whether it underwent RI, extract dates\n", " # for each storm, determine whether the wind speed at a track point is at least 56.0 km per hour = 15.555555 m/s more than \n", " # the wind speed at a track point <= than 4 away (4 track points = 1 day)\n", " day = NA_tracks.DAY.values[index, index_j, :]\n", " day = day[~np.isnan(day)]\n", " month = NA_tracks.MONTH.values[index, index_j, :]\n", " month = month[~np.isnan(month)]\n", " wind = NA_tracks.WIND.values[index, index_j, :]\n", " wind = wind[~np.isnan(wind)]\n", " for j in range(len())\n", " for k in range(len(wind) - 5):\n", " if ((wind[k + 4] - wind[k]) >= 15.555555555): \n", " RI_day2 = day[k + 4].tolist()\n", " RI_day1 = day[k].tolist()\n", " RI_month2 = month[k + 4].tolist()\n", " RI_month1 = month[k].tolist()\n", "\n", " if (RI_day2 == RI_day1):\n", " RI_first_day.append(RI_day1)\n", " else: \n", " RI_first_day.append(RI_day1)\n", " RI_second_day.append(RI_day2)\n", "\n", " if (RI_month2 == RI_month1): \n", " RI_first_month.append(RI_month1)\n", "\n", " else: \n", " RI_first_month.append(RI_month1)\n", " RI_second_month.append(RI_month2)\n", "\n", "\n", " return(RI_first_month, RI_first_day, RI_second_month, RI_second_day)\n" ] }, { "cell_type": "code", "execution_count": null, "id": "driven-order", "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": 149, "id": "streaming-adapter", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "([8.0, 8.0, 8.0, 8.0, 8.0, 8.0, 8.0],\n", " [2.0, 3.0, 3.0, 3.0, 3.0, 6.0, 6.0],\n", " [],\n", " [3.0, 4.0, 4.0, 4.0, 4.0, 7.0, 7.0])" ] }, "execution_count": 149, "metadata": {}, "output_type": "execute_result" } ], "source": [ "RI_dates(1980., 4.)" ] }, { "cell_type": "code", "execution_count": 22, "id": "corresponding-council", "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": 23, "id": "wrong-species", "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": 28, "id": "threaded-retirement", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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<xarray.DataArray 'MONTH' (YRT: 169, ZSTORM1: 35, XCOUNT: 120)>\n",
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       "       [[nan, nan, nan, ..., nan, nan, nan],\n",
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       "        [nan, nan, nan, ..., nan, nan, nan],\n",
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       "Coordinates:\n",
       "  * XCOUNT   (XCOUNT) float64 1.0 2.0 3.0 4.0 5.0 ... 117.0 118.0 119.0 120.0\n",
       "  * ZSTORM1  (ZSTORM1) float64 1.0 2.0 3.0 4.0 5.0 ... 31.0 32.0 33.0 34.0 35.0\n",
       "  * YRT      (YRT) float64 1.851e+03 1.852e+03 1.853e+03 ... 2.018e+03 2.019e+03\n",
       "Attributes:\n",
       "    long_name:  Month\n",
       "    units:      Month\n",
       "    history:    From hold
" ], "text/plain": [ "\n", "array([[[nan, nan, nan, ..., nan, nan, nan],\n", " [nan, nan, nan, ..., nan, nan, nan],\n", " [nan, nan, nan, ..., nan, nan, nan],\n", " ...,\n", " [nan, nan, nan, ..., nan, nan, nan],\n", " [nan, nan, nan, ..., nan, nan, nan],\n", " [nan, nan, nan, ..., nan, nan, nan]],\n", "\n", " [[nan, nan, nan, ..., nan, nan, nan],\n", " [nan, nan, nan, ..., nan, nan, nan],\n", " [nan, nan, nan, ..., nan, nan, nan],\n", " ...,\n", " [nan, nan, nan, ..., nan, nan, nan],\n", " [nan, nan, nan, ..., nan, nan, nan],\n", " [nan, nan, nan, ..., nan, nan, nan]],\n", "\n", " [[nan, nan, nan, ..., nan, nan, nan],\n", " [nan, nan, nan, ..., nan, nan, nan],\n", " [nan, nan, nan, ..., nan, nan, nan],\n", " ...,\n", "...\n", " ...,\n", " [nan, nan, nan, ..., nan, nan, nan],\n", " [nan, nan, nan, ..., nan, nan, nan],\n", " [nan, nan, nan, ..., nan, nan, nan]],\n", "\n", " [[nan, nan, nan, ..., nan, nan, nan],\n", " [nan, nan, nan, ..., nan, nan, nan],\n", " [nan, nan, nan, ..., nan, nan, nan],\n", " ...,\n", " [nan, nan, nan, ..., nan, nan, nan],\n", " [nan, nan, nan, ..., nan, nan, nan],\n", " [nan, nan, nan, ..., nan, nan, nan]],\n", "\n", " [[nan, nan, nan, ..., nan, nan, nan],\n", " [nan, nan, nan, ..., nan, nan, nan],\n", " [nan, nan, nan, ..., nan, nan, nan],\n", " ...,\n", " [nan, nan, nan, ..., nan, nan, nan],\n", " [nan, nan, nan, ..., nan, nan, nan],\n", " [nan, nan, nan, ..., nan, nan, nan]]])\n", "Coordinates:\n", " * XCOUNT (XCOUNT) float64 1.0 2.0 3.0 4.0 5.0 ... 117.0 118.0 119.0 120.0\n", " * ZSTORM1 (ZSTORM1) float64 1.0 2.0 3.0 4.0 5.0 ... 31.0 32.0 33.0 34.0 35.0\n", " * YRT (YRT) float64 1.851e+03 1.852e+03 1.853e+03 ... 2.018e+03 2.019e+03\n", "Attributes:\n", " long_name: Month\n", " units: Month\n", " history: From hold" ] }, "execution_count": 28, "metadata": {}, "output_type": "execute_result" } ], "source": [] }, { "cell_type": "code", "execution_count": 4, "id": "ethical-specific", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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level_0index\"yearmonthdayRMM1RMM2MJO phaseMJO amplitudemean have been removed in these RMMvalues; 20140101-: Only the 120-day has been removed.\",,,,,,,,,,,
09151827NaN197961-1.92933-0.1806800111.93778WH04_method:_OLR_&_NCEP_wind,,,,,,,,,,,
19161828NaN197962-2.23457-0.2995899912.25456WH04_method:_OLR_&_NCEP_wind,,,,,,,,,,,
29171829NaN197963-2.28882-0.5416399812.35203WH04_method:_OLR_&_NCEP_wind,,,,,,,,,,,
39181830NaN197964-2.3154299-0.9369999812.49784WH04_method:_OLR_&_NCEP_wind,,,,,,,,,,,
49191831NaN197965-1.91313-1.1538712.23416WH04_method:_OLR_&_NCEP_wind,,,,,,,,,,,
.......................................
7681859616981NaN202011260.99807048-0.7031673841.220897Gottschalk10_method:_OLR_&_ACCESS_wind ,,,,,,,,,,,
7682859716982NaN202011270.80585057-0.6660394741.045468Gottschalk10_method:_OLR_&_ACCESS_wind ,,,,,,,,,,,
7683859816983NaN202011280.87093019-0.3938512240.955844Gottschalk10_method:_OLR_&_ACCESS_wind ,,,,,,,,,,,
7684859916984NaN202011290.8611328-0.2514693440.897099Gottschalk10_method:_OLR_&_ACCESS_wind ,,,,,,,,,,,
7685860016985NaN202011300.92605019-0.295010640.971905Gottschalk10_method:_OLR_&_ACCESS_wind ,,,,,,,,,,,
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7686 rows × 12 columns

\n", "
" ], "text/plain": [ " level_0 index \" year month day RMM1 RMM2 \\\n", "0 915 1827 NaN 1979 6 1 -1.92933 -0.18068001 \n", "1 916 1828 NaN 1979 6 2 -2.23457 -0.29958999 \n", "2 917 1829 NaN 1979 6 3 -2.28882 -0.54163998 \n", "3 918 1830 NaN 1979 6 4 -2.3154299 -0.93699998 \n", "4 919 1831 NaN 1979 6 5 -1.91313 -1.15387 \n", "... ... ... ... ... ... ... ... ... \n", "7681 8596 16981 NaN 2020 11 26 0.99807048 -0.70316738 \n", "7682 8597 16982 NaN 2020 11 27 0.80585057 -0.66603947 \n", "7683 8598 16983 NaN 2020 11 28 0.87093019 -0.39385122 \n", "7684 8599 16984 NaN 2020 11 29 0.8611328 -0.25146934 \n", "7685 8600 16985 NaN 2020 11 30 0.92605019 -0.2950106 \n", "\n", " MJO phase MJO amplitude mean have been removed in these RMM \\\n", "0 1 1.93778 WH04_method:_OLR_&_NCEP_wind \n", "1 1 2.25456 WH04_method:_OLR_&_NCEP_wind \n", "2 1 2.35203 WH04_method:_OLR_&_NCEP_wind \n", "3 1 2.49784 WH04_method:_OLR_&_NCEP_wind \n", "4 1 2.23416 WH04_method:_OLR_&_NCEP_wind \n", "... ... ... ... \n", "7681 4 1.220897 Gottschalk10_method:_OLR_&_ACCE \n", "7682 4 1.045468 Gottschalk10_method:_OLR_&_ACCE \n", "7683 4 0.955844 Gottschalk10_method:_OLR_&_ACCE \n", "7684 4 0.897099 Gottschalk10_method:_OLR_&_ACCE \n", "7685 4 0.971905 Gottschalk10_method:_OLR_&_ACCE \n", "\n", " values; 20140101-: Only the 120-day has been removed.\",,,,,,,,,,, \n", "0 ,,,,,,,,,,, \n", "1 ,,,,,,,,,,, \n", "2 ,,,,,,,,,,, \n", "3 ,,,,,,,,,,, \n", "4 ,,,,,,,,,,, \n", "... ... \n", "7681 SS_wind ,,,,,,,,,,, \n", "7682 SS_wind ,,,,,,,,,,, \n", "7683 SS_wind ,,,,,,,,,,, \n", "7684 SS_wind ,,,,,,,,,,, \n", "7685 SS_wind ,,,,,,,,,,, \n", "\n", "[7686 rows x 12 columns]" ] }, "execution_count": 4, "metadata": {}, "output_type": "execute_result" } ], "source": [ "import os\n", "os.chdir('/scratch/gpfs/GEOCLIM/cc2705/')\n", "import pandas as pd \n", "import numpy as np\n", "# df = pd.read_excel(r'https://jupyter.rc.princeton.edu/user/cc2705/edit/home/cc2705/MJO%20Phase%20Data.xlsx')\n", "df = pd.read_csv(r'MJO Phase Data.csv')\n", "# columns: year, month, day, RMM1, RMM2, phase, amplitude\n", "#month = df.iloc[:, 2]\n", "day = df.iloc[:, 3]\n", "RMM1 = df.iloc[:, 4]\n", "RMM2 = df.iloc[:, 5]\n", "phase = df.iloc[:, 6]\n", "amplitude = df.iloc[:, 7]\n", "\n", "df.columns\n", "\n", "# month = month.drop(index = 0)\n", "# month \n", "\n", "# rename columns \n", "df.rename(columns = {'p to \"\"real': 'month', 'time\"\". 19': 'day', 'RMM values u': 'year', '740601-20131231:': 'RMM1', 'Both SST1 variability': 'RMM2', '(ENSO)': 'MJO phase', 'and 120-day': 'MJO amplitude'}, inplace = True) \n", "df\n", "\n", "\n", "df['month'] = df['month'].convert_dtypes()\n", "df['month'] \n", "df['month'] = pd.to_numeric(df['month'], errors = 'coerce').convert_dtypes()\n", "df['month']\n", "\n", "# start in June each year (for North Atlantic hurricane season)\n", "North_Atlantic_hurricane = df[(df['month'] >= 6) & (df['month'] < 12)]\n", "North_Atlantic_hurricane = North_Atlantic_hurricane.reset_index()\n", "\n", "North_Atlantic_hurricane['year'] = North_Atlantic_hurricane['year'].convert_dtypes()\n", "North_Atlantic_hurricane['year'] = pd.to_numeric(North_Atlantic_hurricane['year'], errors = 'coerce').convert_dtypes()\n", "\n", "North_Atlantic_hurricane['day'] = North_Atlantic_hurricane['day'].convert_dtypes()\n", "North_Atlantic_hurricane['day'] = pd.to_numeric(North_Atlantic_hurricane['day'], errors = 'coerce').convert_dtypes()\n", "\n", "# remove all data before 1979 and after 2020\n", "post_1979 = North_Atlantic_hurricane[(North_Atlantic_hurricane['year'] >= 1979) & (North_Atlantic_hurricane['year'] < 2021)]\n", "post_1979 = post_1979.reset_index()\n", "post_1979\n", "\n", "post_1979['MJO phase'] = post_1979['MJO phase'].convert_dtypes()\n", "post_1979['MJO phase'] = pd.to_numeric(post_1979['MJO phase'], errors = 'coerce').convert_dtypes()\n", "\n", "post_1979['MJO amplitude'] = post_1979['MJO amplitude'].convert_dtypes()\n", "post_1979['MJO amplitude'] = pd.to_numeric(post_1979['MJO amplitude'], errors = 'coerce').convert_dtypes()\n", "\n", "post_1979" ] }, { "cell_type": "code", "execution_count": 5, "id": "wanted-showcase", "metadata": {}, "outputs": [], "source": [ "large_MJO = post_1979.drop(post_1979[post_1979['MJO amplitude'] < 1].index)\n", "\n", "MJO_phase0 = post_1979[post_1979['MJO amplitude'] < 1]\n", "MJO_phase0\n", "\n", "#easterly_phase = post_1980[post_1980['MJO amplitude'] < -1]\n", "# westerly_phase = post_1980[post_1980['MJO amplitude'] > 1]\n", "\n", "# change post_1980 back to large_MJO after finishing this analysis\n", "\n", "MJO_phase12 = large_MJO[(large_MJO['MJO phase'] == 1) | (large_MJO['MJO phase'] == 2)]\n", "MJO_phase12\n", "\n", "MJO_phase1 = large_MJO[large_MJO['MJO phase'] == 1]\n", "MJO_phase2 = large_MJO[large_MJO['MJO phase'] == 2]\n", "MJO_phase2\n", "\n", "MJO_phase34 = large_MJO[(large_MJO['MJO phase'] == 3) | (large_MJO['MJO phase'] == 4)]\n", "MJO_phase34\n", "\n", "MJO_phase3 = large_MJO[large_MJO['MJO phase'] == 3]\n", "MJO_phase4 = large_MJO[large_MJO['MJO phase'] == 4]\n", "# MJO_phase4\n", "\n", "MJO_phase56 = large_MJO[(large_MJO['MJO phase'] == 5) | (large_MJO['MJO phase'] == 6)]\n", "MJO_phase56\n", "\n", "MJO_phase5 = large_MJO[large_MJO['MJO phase'] == 5]\n", "MJO_phase6 = large_MJO[large_MJO['MJO phase'] == 6]\n", "# MJO_phase6\n", "\n", "MJO_phase78 = large_MJO[(large_MJO['MJO phase'] == 7) | (large_MJO['MJO phase'] == 8)]\n", "MJO_phase78\n", "\n", "MJO_phase7 = large_MJO[large_MJO['MJO phase'] == 7]\n", "MJO_phase8 = large_MJO[large_MJO['MJO phase'] == 8]\n", "# MJO_phase8\n", "\n", "# august_2 = large_MJO.loc[(large_MJO['year'] == 2019) & (large_MJO['month'] == 10) & (large_MJO['day'] == 28)]\n", "# august_2\n", "\n", "phase0 = len(MJO_phase0) \n", "phase12 = len(MJO_phase12) \n", "phase2 = len(MJO_phase2)\n", "phase34 = len(MJO_phase34) \n", "phase4 = len(MJO_phase4) \n", "phase56 = len(MJO_phase56) \n", "phase6 = len(MJO_phase6) \n", "phase78 = len(MJO_phase78) \n", "phase8 = len(MJO_phase8) \n", "\n", "phase1 = len(MJO_phase1)\n", "phase3 = len(MJO_phase3)\n", "phase5 = len(MJO_phase5)\n", "phase7 = len(MJO_phase7)" ] }, { "cell_type": "code", "execution_count": 29, "id": "cheap-professional", "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "/tmp/ipykernel_1856631/2682035900.py:1: SettingWithCopyWarning: \n", "A value is trying to be set on a copy of a slice from a DataFrame.\n", "Try using .loc[row_indexer,col_indexer] = value instead\n", "\n", "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", " MJO_phase1['month'] = MJO_phase1['month'].convert_dtypes()\n", "/tmp/ipykernel_1856631/2682035900.py:2: SettingWithCopyWarning: \n", "A value is trying to be set on a copy of a slice from a DataFrame.\n", "Try using .loc[row_indexer,col_indexer] = value instead\n", "\n", "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", " MJO_phase1['month'] = pd.to_numeric(MJO_phase1['month'], errors = 'coerce').convert_dtypes()\n" ] }, { "data": { "text/plain": [ "0 6\n", "1 6\n", "2 6\n", "3 6\n", "4 6\n", " ..\n", "7588 8\n", "7589 8\n", "7590 8\n", "7667 11\n", "7669 11\n", "Name: month, Length: 780, dtype: Int64" ] }, "execution_count": 29, "metadata": {}, "output_type": "execute_result" } ], "source": [ "MJO_phase1['month'] = MJO_phase1['month'].convert_dtypes()\n", "MJO_phase1['month'] = pd.to_numeric(MJO_phase1['month'], errors = 'coerce').convert_dtypes()\n", "MJO_phase1['month']\n", "# MJO_phase1_jan = MJO_phase1[MJO_phase1['month'] == 01]\n", "# MJO_phase1_jan" ] }, { "cell_type": "code", "execution_count": 4, "id": "ecological-dispatch", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "Text(0.5, 1.0, 'Frequency of Each MJO Index During Hurricane Season, 1980-2019')" ] }, "execution_count": 4, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "import matplotlib.pyplot as plt\n", "MJO = np.empty([3438, ])\n", "MJO.fill(0)\n", "\n", "MJO1 = np.empty([820, ])\n", "MJO1.fill(1)\n", "\n", "MJO2 = np.empty([761, ])\n", "MJO2.fill(2)\n", "\n", "MJO3 = np.empty([480, ])\n", "MJO3.fill(3)\n", "\n", "MJO4 = np.empty([555, ])\n", "MJO4.fill(4)\n", "\n", "MJO5 = np.empty([702, ])\n", "MJO5.fill(5)\n", "\n", "MJO6 = np.empty([599, ])\n", "MJO6.fill(6)\n", "\n", "MJO7 = np.empty([379, ])\n", "MJO7.fill(7)\n", "\n", "MJO8 = np.empty([459, ])\n", "MJO8.fill(8)\n", "\n", "MJO_12 = np.concatenate((MJO1, MJO2), axis = 0)\n", "MJO_34 = np.concatenate((MJO3, MJO4), axis = 0)\n", "MJO_56 = np.concatenate((MJO5, MJO6), axis = 0)\n", "MJO_78 = np.concatenate((MJO7, MJO8), axis = 0)\n", "MJO_1234 = np.concatenate((MJO_12, MJO_34), axis = 0)\n", "MJO_5678 = np.concatenate((MJO_56, MJO_78), axis = 0)\n", "MJO_01234 = np.concatenate((MJO, MJO_1234), axis = 0)\n", "MJO_all = np.concatenate((MJO_01234, MJO_5678), axis = 0)\n", "MJO_all\n", "# plt.hist(MJO1, MJO2, MJO3, MJO4, MJO5, MJO6, MJO7, MJO8, bins = 15)\n", "plt.hist(MJO_all, bins = 20)\n", "plt.xlabel('MJO Index')\n", "plt.ylabel('Frequency')\n", "plt.title('Frequency of Each MJO Index During Hurricane Season, 1980-2019')\n" ] }, { "cell_type": "code", "execution_count": 46, "id": "developing-hindu", "metadata": {}, "outputs": [ { "ename": "NameError", "evalue": "name 'MJO_phase_amp' is not defined", "output_type": "error", "traceback": [ "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", "\u001b[0;31mNameError\u001b[0m Traceback (most recent call last)", "Cell \u001b[0;32mIn[46], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m val, count \u001b[38;5;241m=\u001b[39m np\u001b[38;5;241m.\u001b[39munique(\u001b[43mMJO_phase_amp\u001b[49m, return_counts\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mTrue\u001b[39;00m)\n\u001b[1;32m 2\u001b[0m val, count \n\u001b[1;32m 4\u001b[0m freq_0 \u001b[38;5;241m=\u001b[39m \u001b[38;5;241m106\u001b[39m\n", "\u001b[0;31mNameError\u001b[0m: name 'MJO_phase_amp' is not defined" ] } ], "source": [ "val, count = np.unique(MJO_phase_amp, return_counts=True)\n", "val, count \n", "\n", "freq_0 = 106\n", "freq_1 = 30\n", "freq_2 = 41\n", "freq_3 = 19\n", "freq_4 = 13\n", "freq_5 = 19\n", "freq_6 = 12\n", "freq_7 = 10\n", "freq_8 = 20\n", "\n", "# prob of RI occurring given a certain phase of the MJO = number of days when RI occurred and MJO was in phase x / number of days when MJO was in phase x \n", "RI_given_phase0 = freq_0 / len(MJO_phase0)\n", "RI_given_phase1 = freq_1 / len(MJO_phase1)\n", "RI_given_phase2 = freq_2 / len(MJO_phase2)\n", "RI_given_phase3 = freq_3 / len(MJO_phase3)\n", "RI_given_phase4 = freq_4 / len(MJO_phase4)\n", "RI_given_phase5 = freq_5 / len(MJO_phase5)\n", "RI_given_phase6 = freq_6 / len(MJO_phase6)\n", "RI_given_phase7 = freq_7 / len(MJO_phase7)\n", "RI_given_phase8 = freq_8 / len(MJO_phase8)\n", "RI_given_phase8\n", "\n", "nonzero_MJO_RI = freq_1 + freq_2 + freq_3 + freq_4 + freq_5 + freq_6 + freq_7 + freq_8\n", "nonzero_MJO_days = phase1 + phase2 + phase3 + phase4 + phase5 + phase6 + phase7 + phase8\n", "RI_given_nonzero = nonzero_MJO_RI / (nonzero_MJO_days)\n", "RI_given_nonzero\n", "\n", "RI_given_phase0 = freq_0 / phase0\n", "RI_given_nonzero\n", "\n", "RI_days_NA = nonzero_MJO_RI + freq_0\n", "MJO_days_NA = nonzero_MJO_days + phase0\n", "prob_RI_NA = RI_days_NA / MJO_days_NA\n", "prob_RI_NA" ] }, { "cell_type": "code", "execution_count": 10, "id": "hourly-boring", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "Text(0.5, 1.0, 'Number of North Atlantic RI Events by MJO Index, 1980-2019')" ] }, "execution_count": 10, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "import matplotlib.pyplot as plt\n", "plt.hist(MJO_phase_amp, bins = 20)\n", "plt.xlabel('MJO Index')\n", "plt.ylabel('Number of RI Events')\n", "plt.title('Number of North Atlantic RI Events by MJO Index, 1980-2019')" ] }, { "cell_type": "code", "execution_count": 19, "id": "surgical-drawing", "metadata": {}, "outputs": [], "source": [ "MJO_phase_amp = [1, 1, 0, 1, 0, 0, 5, 5, 2, 2, 2, 2, 2, 2, 4, 0, 4, 4, 0, 0, 0, 0, 2, 2, 8, 8, 0, 0, 0, 0, 8, 8, 5, 5, 4, 4, \n", " 7, 7, 2, 2, 3, 2, 1, 1, 0, 0, 0, 0, 6, 7, 0, 0, 0, 0, 0, 0, 5, 5, 0, 0, 8, 8, 0, 0, 0, 0, 6, 6, 1, 1, 1, 1, \n", " 0, 0, 4, 4, 0, 0, 7, 7, 0, 3, 7, 7, 4, 0, 2, 2, 1, 1, 8, 8, 3, 3, 0, 0, 1, 1, 3, 0, 0, 0, 0, 0, 0, 0, 7, 8, \n", " 8, 7, 5, 5, 8, 0, 2, 2, 1, 1, 2, 2, 3, 3, 1, 1, 2, 2, 5, 5, 3, 0, 0, 0, 0, 0, 0, 0, 4, 0, 6, 6, 6, 6, 8, 0, \n", " 1, 2, 2, 2, 2, 2, 2, 2, 0, 1, 1, 1, 0, 0, 0, 0, 7, 8, 5, 5, 3, 3, 2, 2, 2, 2, 5, 5, 6, 0, 1, 1, 2, 2, 2, 2, \n", " 3, 3, 3, 3, 0, 0, 4, 5, 2, 2, 3, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 6, 6, 6, 2, 2, 2, 2, 3, 0, 4, 4, 2, 0, \n", " 8, 1, 0, 0, 0, 0, 0, 8, 6, 0, 5, 5, 5, 0, 0, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, \n", " 0, 0, 0, 8, 8, 8, 1, 1, 4, 0, 8, 8, 1, 1, 1, 1, 3, 0]\n", "\n" ] }, { "cell_type": "raw", "id": "formed-carter", "metadata": {}, "source": [ "Days of RI: check 1980-1983 for potential missed extra dates\n", "\n", "1980 \n", "08/02 to 08/03\n", "08/06 to 08/07\n", "08/15 to 08/16\n", "09/08 to 09/09\n", "\n", "1981\n", "09/04 to 09/05\n", "09/09 to 09/10\n", "09/12 to 09/13\n", "11/04 to 11/05\n", "\n", "1982\n", "06/02 to 06/03\n", "06/18 to 06/19\n", "09/14 to 09/15\n", "\n", "1983\n", "09/10 to 09/11\n", "\n", "1984\n", "09/10 to 09/11 \n", "\n", "1985\n", "08/14 to 08/15\n", "08/28 to 08/29\n", "09/23 to 09/24\n", "11/15 to 11/16\n", "\n", "1986\n", "09/10 to 09/11\n", "11/19 to 11/20\n", "\n", "1987\n", "09/21 to 09/22\n", "09/24 to 09/25\n", "\n", "1988 \n", "09/01 to 09/02 \n", "09/10 to 09/11\n", "09/13 to 09/14\n", "10/20 to 10/21\n", "\n", "1989\n", "07/31 to 08/01\n", "09/14 to 09/15\n", "\n", "1990\n", "08/06 to 08/07\n", "\n", "1991 \n", "09/05 to 09/06 \n", "\n", "1992 \n", "08/21 to 08/22\n", "09/17 to 09/18\n", "\n", "1993\n", "09/19 to 09/20\n", "09/19 to 09/20 \n", "\n", "1994\n", "09/09 to 09/10\n", "11/03 to 11/04\n", "\n", "1995 \n", "08/11 to 08/12\n", "08/22 to 08/23\n", "08/30 to 08/31 \n", "10/03 to 10/04\n", "10/09 to 10/10\n", "\n", "1996\n", "08/23 to 08/24\n", "09/25 to 09/26\n", "\n", "1997\n", "07/17 to 07/18\n", "\n", "1998 \n", "08/21 to 08/22\n", "08/24 to 08/25\n", "09/01 to 09/02\n", "09/18 to 09/19 \n", "10/23 to 10/24\n", "\n", "1999\n", "08/20 to 08/21 \n", "08/27 to 08/28\n", "09/10 to 09/11\n", "09/12 to 09/13\n", "10/13 to 10/14\n", "11/14 to 11/15 \n", "11/16 to 11/17\n", "\n", "2000 \n", "08/20 to 08/21 \n", "09/10 to 09/11\n", "09/20 to 09/21\n", "09/22 to 09/23\n", "09/29 to 09/30\n", "10/04 to 10/05\n", "\n", "2001\n", "09/08 to 09/09\n", "09/12 to 09/13 \n", "10/07 to 10/08 \n", "11/02 to 11/03\n", "\n", "2002\n", "09/19 to 09/20 \n", "*check 09/21 to 09/22 \n", "10/02\n", "\n", "2003 \n", "08/29 to 08/30 \n", "*check 08/30 to 08/31\n", "09/07 to 09/08 \n", "*check 09/08 to 09/09\n", "\n", "2004\n", "08/02 to 08/03\n", "08/13\n", "08/14 to 08/15\n", "08/26 to 08/27\n", "09/04 to 09/05\n", "*check 09/05 to 09/06\n", "09/17 to 09/18\n", "\n", "2005 \n", "07/05 to 07/06\n", "07/06 to 07/07 \n", "*check 07/07 to 07/08 \n", "07/09 to 07/10\n", "07/14 to 07/15\n", "*check 07/15 to 07/16 \n", "07/19 to 07/20\n", "08/27 to 08/28\n", "*check 08/28 to 08/29\n", "09/20 to 09/21 \n", "*check 09/21 to 09/22\n", "10/18 to 10/19\n", "\n", "2006\n", "09/12 to 09/13 \n", "*check 09/13 to 09/14\n", "\n", "2007 \n", "08/17 to 08/18\n", "09/01 to 09/02 \n", "*check 09/02 to 09/03\n", "09/12 to 09/13\n", "09/27 to 09/28\n", "\n", "2008\n", "07/06 to 07/07 \n", "*check 07/07 to 07/08\n", "08/25 to 08/26 \n", "08/29 to 08/30 \n", "*check 08/30 to 08/31\n", "09/03 to 09/04\n", "10/15 to 10/16\n", "11/06 to 11/07\n", "*check 11/07 to 11/08\n", "\n", "2009\n", "09/08 to 09/09\n", "11/04 to 11/05\n", "11/07 to 11/08\n", "\n", "2010 \n", "08/29 to 08/30\n", "09/11 to 09/12 \n", "*check 09/12 to 09/13\n", "09/13 to 09/14\n", "*check 09/14 to 09/15\n", "09/16 to 09/17\n", "09/24 to 09/25\n", "10/11 to 10/12\n", "\n", "2011\n", "09/29 to 09/30\n", "*check 09/30 to 10/01\n", "10/23 to 10/24\n", "*check 10/24 to 10/25\n", "\n", "2012\n", "08/17 to 08/18 \n", "*check 08/18 to 08/19\n", "08/30 to 08/31\n", "09/05 to 09/06\n", "10/24 to 10/25\n", "\n", "2013\n", "none...\n", "\n", "2014\n", "10/14 to 10/15\n", "\n", "2015\n", "08/20 to 08/21\n", "08/30 to 08/31\n", "09/30 to 10/01\n", "\n", "2016\n", "08/27 to 08/28\n", "09/29 to 09/30 \n", "*check 09/30 to 10/01\n", "10/06 to 10/07\n", "10/11 to 10/12\n", "*check 10/12 to 10/13\n", "11/23 to 11/24\n", "\n", "2017\n", "08/09 to 08/10\n", "08/23 to 08/24 \n", "*check 08/24 to 08/25\n", "*check 08/25 to 08/26\n", "08/30 to 08/31 \n", "*check 08/31 to 09/01\n", "09/04 to 09/05\n", "09/06 to 09/07 \n", "*check 09/07 to 09/08\n", "09/05 to 09/06 \n", "*check 09/06 to 09/07\n", "09/23 to 09/24 \n", "*check 09/24 to 09/25\n", "09/17 to 09/18 \n", "*check 09/18 to 09/19\n", "10/06 to 10/07\n", "\n", "2018\n", "07/05 to 07/06\n", "09/04 to 09/05 \n", "09/10 to 09/11\n", "10/08 to 10/09\n", "*check 10/09 to 10/10\n", "\n", "2019\n", "08/30 to 08/31\n", "09/19 to 09/20\n", "09/25 to 09/26 \n", "*check 09/26 to 09/27 \n", "09/28 to 09/29\n", "10/27 to 10/28" ] }, { "cell_type": "code", "execution_count": 422, "id": "liked-liberal", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "(array([12.8611, 12.8611, 12.8611, 12.8611, 12.8611, 10.2889, 10.2889,\n", " 10.2889, 10.2889, 12.8611, 12.8611, 15.4333, 15.4333, 15.4333,\n", " 18.0055, 20.5778, 23.15 , 25.7222, 25.7222, 30.8666, 33.4389,\n", " 38.5833, 46.3 , 43.7277, 38.5833, 38.5833, 38.5833, 43.7277,\n", " 51.4444, 56.5888, 56.5888, 56.5888, 56.5888, 56.5888, 56.5888,\n", " 51.4444, 36.0111, 30.8666, 25.7222, 18.0055, 23.15 , 25.7222,\n", " 25.7222, 25.7222, 25.7222, 25.7222, 28.2944, 28.2944, 28.2944,\n", " 28.2944, 20.5778, 10.2889, 10.2889, 10.2889, 10.2889]),\n", " array([9., 9., 9., 9., 9., 9., 9., 9., 9., 9., 9., 9., 9., 9., 9., 9., 9.,\n", " 9., 9., 9., 9., 9., 9., 9., 9., 9., 9., 9., 9., 9., 9., 9., 9., 9.,\n", " 9., 9., 9., 9., 9., 9., 9., 9., 9., 9., 9., 9., 9., 9., 9., 9., 9.,\n", " 9., 9., 9., 9.]),\n", " array([14., 15., 15., 15., 15., 16., 16., 16., 16., 17., 17., 17., 17.,\n", " 18., 18., 18., 18., 19., 19., 19., 19., 20., 20., 20., 20., 20.,\n", " 21., 21., 21., 21., 22., 22., 22., 22., 22., 23., 23., 23., 23.,\n", " 24., 24., 24., 24., 25., 25., 25., 25., 26., 26., 26., 26., 27.,\n", " 27., 27., 27.]))" ] }, "execution_count": 422, "metadata": {}, "output_type": "execute_result" } ], "source": [ "rapid_intensification_date(2002., 10.)" ] }, { "cell_type": "code", "execution_count": 18, "id": "orange-attendance", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "0.07371704459679239" ] }, "execution_count": 18, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# starting from 1980 \n", "MJO_phase_RI = [1, 1, 1, 1, 1, 2, 5, 5, 2, 2, 2, 2, 2, 2, 4, 4, 4, 4, 6, 6, 7, 7, 2, 2, 8, 8, 4, 4, 3, 3, 8, 8, 5, \n", " 5, 4, 4, 7, 7, 2, 2, 3, 2, 1, 1, 2, 1, 5, 5, 6, 7, 8, 8, 2, 2, 7, 1, 5, 5, 5, 5, 8, 8, 1, 1, 8, 8, \n", " 6, 6, 1, 1, 1, 1, 3, 3, 4, 4, 5, 6, 7, 7, 3, 3, 7, 7, 4, 4, 2, 2, 1, 1, 8, 8, 3, 3, 8, 3, 1, 1, 3, \n", " 3, 7, 8, 1, 8, 2, 3, 7, 8, 8, 7, 5, 5, 8, 8, 2, 2, 1, 1, 2, 2, 3, 3, 1, 1, 2, 2, 5, 5, 3, 3, 7, 8, \n", " 2, 1, 1, 4, 4, 6, 6, 6, 6, 6, 8, 8, 1, 2, 2, 2, 2, 2, 2, 2, 1, 1, 1, 1, 2, 5, 1, 1, 7, 8, 5, 5, 3, \n", " 3, 2, 2, 2, 2, 5, 5, 6, 6, 1, 1, 2, 2, 2, 2, 3, 3, 3, 3, 3, 4, 4, 5, 2, 2, 3, 3, 6, 8, 4, 4, 4, 3, \n", " 2, 1, 1, 1, 5, 6, 6, 6, 2, 2, 2, 2, 3, 3, 4, 4, 2, 2, 8, 1, 7, 8, 8, 8, 8, 8, 6, 6, 5, 5, 5, 5, 6, \n", " 6, 3, 3, 1, 8, 2, 2, 3, 4, 4, 4, 2, 1, 4, 2, 7, 7, 4, 4, 3, 4, 6, 6, 8, 8, 8, 8, 1, 1, 4, 4, 8, 8, \n", " 1, 1, 1, 1, 3, 3]\n", "\n", "import matplotlib.pyplot as plt\n", "plt.hist(MJO_phase_RI, bins = 15)\n", "plt.xlabel('MJO Index')\n", "plt.ylabel('Number of RI Events')\n", "plt.title('Number of North Atlantic RI Events by MJO Index, 1980-2019')\n", "\n", "\n", "val, count = np.unique(MJO_phase_RI, return_counts=True)\n", "val, count\n", "# total number of MJO data points is 270\n", "\n", "\n", "# probability of RI given a specific MJO phase\n", "# probability of RI occurring given that the MJO phase is 1\n", "# equals the probability of RI happening and the MJO phase being 1 divided by the probability of the MJO phase being 1\n", "\n", "# probability of the MJO phase being 1 during NA hurricane season (June 1 - Nov 30) from 1980-2024\n", "prob_MJO1 = 1293/8193\n", "prob_MJO2 = 1297/8193\n", "prob_MJO3 = 922/8193\n", "prob_MJO4 = 1030/8193\n", "prob_MJO5 = 1075/8193\n", "prob_MJO6 = 964/8193\n", "prob_MJO7 = 756/8193\n", "prob_MJO8 = 856/8193\n", "# prob that MJO phase is 1 given RI is 47/270 \n", "\n", "phase1_given_RI = 47/270\n", "# prob_RI = number of RI days / total number of storm days\n", "prob_RI = 270 / 4804\n", "\n", "# phase 1 given RI = prob phase 1 and RI / prob RI \n", "# phase 1 given RI * prob RI = prob phase 1 and RI \n", "prob_phase1_and_RI = phase1_given_RI * prob_RI\n", "prob_RI_given_phase1 = prob_phase1_and_RI / prob_MJO1\n", "prob_RI_given_phase1\n", "\n", "phase2_given_RI = 54/270\n", "prob_phase2_and_RI = phase2_given_RI * prob_RI\n", "prob_RI_given_phase2 = prob_phase2_and_RI / prob_MJO2\n", "\n", "phase3_given_RI = 35/270 \n", "prob_phase3_and_RI = phase3_given_RI * prob_RI\n", "prob_RI_given_phase3 = prob_phase3_and_RI / prob_MJO3\n", "prob_RI_given_phase3\n", "\n", "phase4_given_RI = 30/270\n", "prob_phase4_and_RI = phase4_given_RI * prob_RI\n", "prob_RI_given_phase4 = prob_phase4_and_RI / prob_MJO4\n", "prob_RI_given_phase4\n", "\n", "phase5_given_RI = 26/270\n", "prob_phase5_and_RI = phase5_given_RI * prob_RI\n", "prob_RI_given_phase5 = prob_phase5_and_RI / prob_MJO5\n", "prob_RI_given_phase5\n", "\n", "phase6_given_RI = 23/270 \n", "prob_phase6_and_RI = phase6_given_RI * prob_RI\n", "prob_RI_given_phase6 = prob_phase6_and_RI / prob_MJO6\n", "prob_RI_given_phase6\n", "\n", "phase7_given_RI = 18/270\n", "prob_phase7_and_RI = phase7_given_RI * prob_RI\n", "prob_RI_given_phase7 = prob_phase7_and_RI / prob_MJO7 \n", "prob_RI_given_phase7\n", "\n", "phase8_given_RI = 37/270\n", "prob_phase8_and_RI = phase8_given_RI * prob_RI\n", "prob_RI_given_phase8 = prob_phase8_and_RI / prob_MJO8 \n", "prob_RI_given_phase8" ] }, { "cell_type": "code", "execution_count": 2053, "id": "packed-guinea", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "Text(0.5, 1.0, 'Frequency of Each MJO Index During Hurricane Season, 1980-2019')" ] }, "execution_count": 2053, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "MJO1 = np.empty([1293, ])\n", "MJO1.fill(1)\n", "\n", "MJO2 = np.empty([1297, ])\n", "MJO2.fill(2)\n", "\n", "MJO3 = np.empty([922, ])\n", "MJO3.fill(3)\n", "\n", "MJO4 = np.empty([1030, ])\n", "MJO4.fill(4)\n", "\n", "MJO5 = np.empty([1075, ])\n", "MJO5.fill(5)\n", "\n", "MJO6 = np.empty([964, ])\n", "MJO6.fill(6)\n", "\n", "MJO7 = np.empty([756, ])\n", "MJO7.fill(7)\n", "\n", "MJO8 = np.empty([856, ])\n", "MJO8.fill(8)\n", "\n", "MJO_12 = np.concatenate((MJO1, MJO2), axis = 0)\n", "MJO_34 = np.concatenate((MJO3, MJO4), axis = 0)\n", "MJO_56 = np.concatenate((MJO5, MJO6), axis = 0)\n", "MJO_78 = np.concatenate((MJO7, MJO8), axis = 0)\n", "MJO_1234 = np.concatenate((MJO_12, MJO_34), axis = 0)\n", "MJO_5678 = np.concatenate((MJO_56, MJO_78), axis = 0)\n", "MJO_all = np.concatenate((MJO_1234, MJO_5678), axis = 0)\n", "MJO_all\n", "# plt.hist(MJO1, MJO2, MJO3, MJO4, MJO5, MJO6, MJO7, MJO8, bins = 15)\n", "plt.hist(MJO_all, bins = 15)\n", "plt.xlabel('MJO Index')\n", "plt.ylabel('Frequency')\n", "plt.title('Frequency of Each MJO Index During Hurricane Season, 1980-2019')\n" ] }, { "cell_type": "code", "execution_count": 93, "id": "satisfactory-jurisdiction", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "([], [], [], [])" ] }, "execution_count": 93, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# find dates of genesis for all TCs from 1980 onward\n", "\n", "# find all date in a given year when storms underwent RI\n", "\n", "# want a function that loops thru all storms in a given year and finds dates of RI based on their track points\n", "# first: make this function which returns the wind speeds from all 120 track points of each storm of a given year\n", "def track_points(yearnum):\n", " year = NA_tracks.YRT.values\n", " i = np.where(np.isclose(year, yearnum))\n", " index = np.asarray(i).item()\n", " wind = NA_tracks.WIND.values[index]\n", " day = NA_tracks.DAY.values[index]\n", " month = NA_tracks.MONTH.values[index]\n", "\n", "\n", " \n", "# wind speed function returns a 120 by 35 array of wind speeds at 120 track points for each of 35 storms for a given year\n", "track_pts = track_points(1980.) \n", "# storms = get_storms(1980.)\n", "\n", "def RI_dates(track_pts):\n", " RI_first_day = []\n", " RI_second_day = []\n", " RI_first_month = []\n", " RI_second_month = []\n", " for k in range(track_pts.shape[0]):\n", " for j in range(((track_pts.shape[1]- 5))): \n", " if ((track_pts[k, j + 4] - track_pts[k, j]) >= 15.555555555): \n", " RI_day2 = day[k, j + 4].tolist()\n", " RI_day1 = day[k, j].tolist()\n", " RI_month2 = month[k ,j + 4].tolist()\n", " RI_month1 = month[k, j].tolist()\n", " \n", "\n", " if (RI_day2 == RI_day1):\n", " RI_first_day.append(RI_day1)\n", " else: \n", " RI_first_day.append(RI_day1)\n", " RI_second_day.append(RI_day2)\n", "\n", " if (RI_month2 == RI_month1): \n", " RI_first_month.append(RI_month1)\n", "\n", " else: \n", " RI_first_month.append(RI_month1)\n", " RI_second_month.append(RI_month2)\n", "\n", " \n", " return(RI_first_month, RI_first_day, RI_second_month, RI_second_day)\n", " \n", "# pass in (track points, number of storms) as 2dim array (wind)\n", "#all_RI = np.vectorize(RI_dates)\n", "\n", "RI_dates(track_pts)\n" ] }, { "cell_type": "code", "execution_count": 2025, "id": "equivalent-airplane", "metadata": { "scrolled": true }, "outputs": [ { "data": { "text/plain": [ "4804" ] }, "execution_count": 2025, "metadata": {}, "output_type": "execute_result" } ], "source": [] }, { "cell_type": "code", "execution_count": 4007, "id": "electrical-utilization", "metadata": {}, "outputs": [], "source": [ "storm_dates(2019., 35.)" ] }, { "cell_type": "code", "execution_count": 4025, "id": "national-trout", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "Text(0.5, 1.0, 'Frequency of Each MJO Index When Storms Reached 17 m/s')" ] }, "execution_count": 4025, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "TC_gen = post_1980[(post_1980['month'] == 11) & (post_1980['day'] == 19) & (post_1980['year'] == 2019)]\n", "TC_gen\n", "MJO_phase_TC_gen = [1, 1, 4, 5, 5, 5, 5, 1, 2, 8, 6, 3, 6, 6, 2, 2, 2, 2, 5, 3, 4, 4, 4, 6, 6, 5, 7, 1, 4, 4, 2, 5, 5, 7, \n", " 1, 1, 8, 7, 7, 8, 1, 4, 4, 1, 1, 1, 4, 4, 3, 7, 8, 8, 2, 8, 5, 2, 6, 6, 3, 4, 4, 2, 2, 3, 6, 4, 2, 3, \n", " 2, 2, 1, 1, 1, 8, 8, 1, 4, 5, 6, 4, 1, 3, 8, 8, 7, 1, 2, 7, 2, 4, 8, 3, 6, 7, 7, 6, 5, 6, 6, 2, 2, 5, \n", " 6, 1, 1, 2, 5, 5, 6, 6, 3, 5, 5, 5, 8, 1, 1, 2, 5, 3, 8, 6, 8, 1, 1, 2, 6, 8, 1, 8, 8, 6, 7, 1, 2, 2, \n", " 3, 7, 2, 2, 2, 1, 3, 3, 3, 3, 4, 8, 5, 3, 6, 7, 5, 3, 5, 2, 6, 3, 3, 3, 3, 5, 7, 1, 8, 1, 1, 7, 3, 4, \n", " 3, 4, 2, 7, 1, 4, 2, 2, 1, 8, 8, 3, 3, 4, 4, 4, 5, 8, 6, 8, 1, 1, 2, 2, 8, 1, 1, 2, 3, 4, 7, 1, 4, 5, \n", " 5, 8, 8, 2, 2, 1, 1, 2, 3, 5, 5, 6, 2, 3, 6, 7, 7, 1, 2, 2, 4, 5, 6, 2, 3, 3, 6, 8, 3, 3, 8, 8, 1, 2, \n", " 4, 7, 7, 1, 2, 2, 2, 3, 2, 2, 1, 3, 4, 7, 5, 4, 4, 5, 6, 6, 6, 6, 6, 8, 8, 8, 1, 2, 2, 2, 5, 5, 3, 2, \n", " 2, 2, 2, 1, 3, 4, 6, 6, 2, 2, 3, 3, 4, 4, 5, 6, 8, 1, 1, 2, 1, 5, 5, 4, 6, 8, 6, 1, 8, 8, 2, 1, 1, 1, \n", " 3, 3, 4, 1, 5, 2, 2, 2, 4, 5, 5, 5, 5, 6, 6, 8, 5, 1, 3, 3, 4, 2, 2, 2, 2, 2, 6, 6, 1, 2, 3, 3, 1, 2, \n", " 2, 1, 4, 4, 5, 4, 2, 2, 3, 1, 4, 5, 8, 2, 2, 3, 4, 3, 1, 1, 1, 4, 5, 6, 5, 5, 2, 3, 4, 7, 2, 2, 2, 2, \n", " 1, 3, 3, 3, 3, 3, 3, 5, 5, 2, 5, 1, 1, 6, 7, 2, 1, 2, 3, 3, 3, 3, 5, 6, 5, 2, 2, 2, 2, 6, 1, 7, 8, 8, \n", " 3, 2, 4, 5, 5, 4, 2, 8, 8, 2, 4, 8, 7, 8, 2, 4, 8, 7, 1, 8, 1, 1, 2, 8, 3, 7, 4, 5, 6, 6, 8, 4, 4, 4, \n", " 5, 5, 5, 2, 1, 1, 3, 7, 8, 3, 7, 3, 4, 2, 3, 3, 2, 4, 7, 3, 6, 4, 7, 6, 6, 7, 8, 8, 8, 8, 8, 1, 1, 7, \n", " 1, 2, 3, 4, 5, 5, 7, 8, 8, 1, 1, 1, 1, 3, 2, 3, 8]\n", "\n", "plt.hist(MJO_phase_TC_gen, bins = 15)\n", "plt.xlabel('MJO Index at TC Genesis')\n", "plt.ylabel('Frequency'\n", "plt.title('Frequency of Each MJO Index When Storms Reached 17 m/s')\n" ] }, { "cell_type": "code", "execution_count": 12, "id": "protective-momentum", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "493" ] }, "execution_count": 12, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# find out what phase the MJO was on the day the storm's wind speed reached 17 m/s (call this TC genesis)\n", "# this is for entire NA (not just GoM / Caribbean) \n", "import matplotlib.pyplot as plt\n", "\n", "amp_phase_genesis = [1, 0, 4, 5, 5, 5, 5, 1, 0, 0, 0, 0, 6, 6, 2, 2, 2, 2, 5, 3, 4, 0, 4, 0, 0, 0, 0, 0, 4, 0, 2, 5, 5, 0, 0, \n", " 0, 8, 7, 7, 8, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 8, 0, 8, 5, 2, 6, 6, 3, 4, 4, 2, 2, 3, 0, 4, 2, 0, 0, 0, \n", " 1, 1, 0, 0, 0, 0, 4, 5, 6, 0, 0, 0, 0, 0, 7, 0, 0, 0, 2, 4, 8, 0, 0, 0, 0, 0, 0, 6, 0, 0, 2, 0, 0, 1, 1, \n", " 0, 5, 5, 6, 6, 3, 0, 0, 5, 8, 1, 1, 0, 5, 3, 8, 6, 0, 0, 0, 0, 0, 0, 0, 0, 0, 6, 7, 1, 2, 0, 3, 0, 2, 2, \n", " 0, 1, 0, 0, 0, 3, 4, 0, 0, 0, 0, 7, 0, 0, 5, 2, 6, 3, 0, 3, 0, 0, 7, 1, 0, 0, 1, 7, 3, 4, 3, 4, 0, 0, 1, \n", " 0, 2, 2, 2, 1, 8, 8, 0, 3, 4, 4, 4, 5, 0, 6, 0, 1, 1, 2, 2, 8, 0, 1, 0, 3, 4, 7, 1, 0, 5, 5, 8, 0, 2, 2, \n", " 1, 0, 2, 3, 5, 5, 6, 2, 0, 6, 7, 0, 1, 2, 2, 4, 5, 6, 2, 3, 0, 0, 8, 3, 3, 8, 0, 0, 0, 0, 0, 0, 0, 2, 0,\n", " 2, 0, 0, 0, 0, 0, 0, 0, 0, 4, 4, 5, 0, 6, 6, 6, 6, 8, 8, 0, 1, 2, 2, 2, 5, 5, 0, 0, 0, 2, 2, 1, 0, 0, 6, \n", " 6, 0, 0, 0, 3, 4, 4, 5, 0, 0, 0, 1, 2, 1, 5, 0, 4, 0, 8, 0, 1, 8, 8, 2, 1, 1, 0, 3, 3, 4, 1, 0, 0, 0, 2, \n", " 4, 5, 5, 5, 0, 6, 0, 8, 5, 1, 3, 0, 2, 2, 2, 2, 2, 6, 0, 0, 0, 0, 0, 1, 2, 2, 0, 4, 4, 5, 4, 2, 2, 3, 0, \n", " 0, 5, 0, 0, 2, 0, 0, 0, 1, 0, 0, 4, 5, 0, 0, 0, 0, 0, 4, 0, 0, 2, 2, 2, 1, 3, 3, 0, 0, 0, 0, 0, 0, 2, 5, \n", " 1, 1, 6, 0, 2, 1, 2, 3, 3, 3, 3, 5, 6, 0, 0, 2, 2, 0, 6, 1, 7, 0, 8, 0, 0, 0, 5, 5, 0, 0, 0, 0, 2, 4, 0, \n", " 0, 0, 0, 4, 8, 0, 1, 0, 1, 0, 0, 0, 3, 0, 4, 0, 6, 6, 0, 4, 4, 4, 5, 5, 5, 2, 1, 1, 3, 0, 0, 0, 0, 0, 0, \n", " 0, 3, 3, 0, 4, 7, 0, 0, 4, 7, 6, 0, 0, 8, 8, 0, 8, 8, 1, 1, 7, 1, 0, 3, 4, 5, 5, 0, 8, 8, 1, 1, 1, 1, 3, \n", " 2, 3, 8]\n", "\n", "plt.hist(amp_phase_genesis, bins = 20)\n", "plt.xlabel('MJO Index at TC Genesis')\n", "plt.ylabel('Frequency')\n", "plt.title('Frequency of Each MJO Index When Storms Reached 17 m/s')\n", "\n", "len(amp_phase_genesis)" ] }, { "cell_type": "code", "execution_count": 146, "id": "concerned-adjustment", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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level_0index\"yearmonthdayRMM1RMM2MJO phaseMJO amplitudemean have been removed in these RMMvalues; 20140101-: Only the 120-day has been removed.\",,,,,,,,,,,
7308840616608NaN20191119-1.56140450.1404856781.567712Gottschalk10_method:_OLR_&_ACCESS_wind ,,,,,,,,,,,
\n", "
" ], "text/plain": [ " level_0 index \" year month day RMM1 RMM2 \\\n", "7308 8406 16608 NaN 2019 11 19 -1.5614045 0.14048567 \n", "\n", " MJO phase MJO amplitude mean have been removed in these RMM \\\n", "7308 8 1.567712 Gottschalk10_method:_OLR_&_ACCE \n", "\n", " values; 20140101-: Only the 120-day has been removed.\",,,,,,,,,,, \n", "7308 SS_wind ,,,,,,,,,,, " ] }, "execution_count": 146, "metadata": {}, "output_type": "execute_result" } ], "source": [ "august_2 = large_MJO.loc[(large_MJO['year'] == 2019) & (large_MJO['month'] == 11) & (large_MJO['day'] == 19)]\n", "august_2" ] }, { "cell_type": "raw", "id": "spare-sussex", "metadata": {}, "source": [ "2019\n", "07/11\n", "08/21\n", "08/24\n", "08/27\n", "09/03\n", "09/04\n", "09/14\n", "09/18\n", "09/17\n", "09/22\n", "09/23\n", "10/08\n", "10/17\n", "10/25\n", "10/23\n", "10/27\n", "11/19\n", "\n", "2018\n", "07/05\n", "07/08\n", "08/03\n", "08/15\n", "09/01\n", "09/03\n", "09/08\n", "09/08 (again)\n", "09/12\n", "09/22\n", "09/22 (again)\n", "10/07\n", "10/09\n", "10/26\n", "\n", "2017\n", "06/19\n", "06/19 (again)\n", "07/17\n", "07/31\n", "08/07\n", "08/13\n", "08/17\n", "08/30\n", "09/05\n", "09/06\n", "09/16\n", "09/16 (again)\n", "10/05\n", "10/08\n", "10/28\n", "11/07\n", "\n", "2016\n", "06/05\n", "06/20\n", "08/02\n", "08/17\n", "08/22\n", "08/31\n", "09/12\n", "09/13\n", "09/15\n", "09/20\n", "09/28\n", "10/04\n", "11/21\n", "\n", "2015\n", "06/16\n", "07/13\n", "08/18\n", "08/24\n", "08/30\n", "09/05\n", "09/09\n", "09/19\n", "09/29\n", "11/09\n", "\n", "2014\n", "07/01\n", "07/31\n", "08/24\n", "09/02\n", "09/12\n", "10/10\n", "10/12\n", "10/27\n", "\n", "2013\n", "06/05\n", "06/19\n", "07/07\n", "07/24\n", "08/15\n", "08/25\n", "09/10\n", "09/09\n", "09/13\n", "09/30\n", "10/03\n", "10/21\n", "11/17\n", "\n", "2012\n", "06/17\n", "06/23\n", "08/02\n", "08/04\n", "08/17\n", "08/16\n", "08/21\n", "08/23\n", "08/29\n", "08/30\n", "09/04\n", "09/12\n", "10/03\n", "10/11\n", "10/12\n", "10/22\n", "10/24\n", "\n", "2011\n", "06/28\n", "07/18\n", "07/20\n", "07/27\n", "08/02\n", "08/13\n", "08/14\n", "08/19\n", "08/21\n", "08/27\n", "08/30\n", "09/01\n", "09/02\n", "09/07\n", "09/07 (again)\n", "09/21\n", "09/24\n", "10/24\n", "11/06\n", "\n", "2010\n", "06/26\n", "07/22\n", "08/03\n", "08/22\n", "08/25\n", "08/30\n", "09/01\n", "09/06\n", "09/08\n", "09/12\n", "09/14\n", "09/21\n", "09/23\n", "09/28\n", "10/06\n", "10/11\n", "10/21\n", "10/29\n", "10/29 (again)\n", "\n", "2009\n", "08/12\n", "08/15\n", "08/16\n", "08/26\n", "09/01\n", "09/08\n", "09/27\n", "10/06\n", "11/04\n", "\n", "2008\n", "07/03\n", "07/19\n", "07/20\n", "08/04\n", "08/15\n", "08/25\n", "08/28\n", "09/01\n", "09/02\n", "09/25\n", "09/26\n", "10/06\n", "10/12\n", "10/14\n", "11/06\n", "\n", "2007\n", "06/01\n", "07/31\n", "08/14\n", "08/15\n", "09/01\n", "09/08\n", "09/13\n", "09/12\n", "09/23\n", "09/25\n", "09/27\n", "09/29\n", "10/16\n", "10/28\n", "\n", "2006\n", "06/11\n", "07/17\n", "07/18\n", "08/01\n", "08/23\n", "08/25\n", "09/05\n", "09/11\n", "09/14\n", "09/28\n", "\n", "2005\n", "06/09\n", "06/28\n", "07/05\n", "07/05 (again)\n", "07/12\n", "07/22\n", "07/24\n", "08/03\n", "08/07\n", "08/22\n", "08/24\n", "08/31\n", "09/02\n", "09/06\n", "09/07\n", "09/17\n", "09/18\n", "10/02\n", "10/04\n", "10/05\n", "10/12\n", "10/08\n", "10/17\n", "10/22\n", "10/27\n", "11/15\n", "11/20\n", "11/29\n", "\n", "2004\n", "08/01\n", "08/09\n", "08/10\n", "08/14\n", "08/14 (again)\n", "08/25\n", "08/28\n", "08/29\n", "09/03\n", "09/14\n", "09/16\n", "09/20\n", "10/08\n", "10/10\n", "11/26\n", "\n", "2003\n", "06/29\n", "07/07\n", "07/17\n", "08/14\n", "08/28\n", "08/30\n", "09/05\n", "09/06\n", "09/25\n", "09/27\n", "09/30\n", "10/10\n", "10/14\n", "\n", "2002\n", "07/15\n", "08/05\n", "08/06\n", "08/29\n", "09/02\n", "09/06\n", "09/08\n", "09/12\n", "09/18\n", "09/18 (again)\n", "09/21\n", "09/23\n", "\n", "2001\n", "06/05\n", "08/02\n", "08/17\n", "08/22\n", "09/02\n", "09/11\n", "09/13\n", "09/22\n", "10/05\n", "10/07\n", "10/11\n", "10/30\n", "11/01\n", "11/04\n", "11/24\n", "\n", "2000\n", "08/04\n", "08/14\n", "08/18\n", "08/20\n", "09/02\n", "09/11\n", "09/16\n", "09/21\n", "09/22\n", "09/26\n", "09/29\n", "10/05\n", "10/16\n", "10/20\n", "10/25\n", "\n", "1999\n", "06/12\n", "08/19\n", "08/20\n", "08/24\n", "08/24 (again)\n", "09/08\n", "09/12\n", "09/20\n", "10/13\n", "10/18\n", "10/29\n", "11/14\n", "\n", "1998\n", "07/29\n", "08/20\n", "08/21\n", "08/24\n", "08/31\n", "09/09\n", "09/16\n", "09/19\n", "09/20\n", "09/21\n", "09/24\n", "10/05\n", "10/22\n", "11/24\n", "\n", "1997\n", "06/01\n", "07/01\n", "07/11\n", "07/13\n", "07/17\n", "09/03\n", "10/05\n", "10/15\n", "\n", "1996\n", "06/19\n", "07/05\n", "07/25\n", "08/19\n", "08/22\n", "08/27\n", "08/28\n", "09/07\n", "09/25\n", "10/06\n", "10/11\n", "10/16\n", "11/19\n", "\n", "1995\n", "06/03\n", "07/07\n", "07/14\n", "07/30\n", "07/31\n", "08/08\n", "08/10\n", "08/22\n", "08/22 (again)\n", "08/23\n", "08/28\n", "08/29\n", "09/13\n", "09/27\n", "09/30\n", "10/05\n", "10/09\n", "10/21\n", "10/27\n", "\n", "1994\n", "07/02\n", "08/15\n", "08/17\n", "09/10\n", "09/22\n", "11/02\n", "11/10\n", "\n", "1993 \n", "06/02\n", "06/19\n", "08/05\n", "08/14\n", "08/25\n", "08/24\n", "09/07\n", "09/15\n", "09/20\n", "\n", "1992\n", "08/17\n", "09/18\n", "09/22\n", "09/22 (again)\n", "09/29\n", "10/22\n", "\n", "1991\n", "07/04\n", "08/16\n", "09/05\n", "09/08\n", "09/09\n", "10/15\n", "10/26\n", "10/29\n", "\n", "1990\n", "07/24\n", "07/28\n", "08/02\n", "08/03\n", "08/05\n", "08/13\n", "08/25\n", "08/26\n", "09/05\n", "09/24\n", "10/03\n", "10/06\n", "10/10\n", "10/16\n", "\n", "1989\n", "06/26\n", "07/11\n", "07/31\n", "08/01\n", "08/19\n", "08/26\n", "08/31\n", "09/11\n", "09/18\n", "10/13\n", "11/30\n", "\n", "1988\n", "08/07\n", "08/08\n", "08/28\n", "09/02\n", "09/03\n", "09/07\n", "09/07 (again)\n", "09/09\n", "09/20\n", "09/30\n", "10/11\n", "11/20\n", "\n", "1987\n", "08/09\n", "08/11\n", "08/18\n", "09/07\n", "09/10\n", "09/20\n", "10/10\n", "\n", "1986\n", "06/06\n", "06/24\n", "08/15\n", "09/07\n", "09/11\n", "11/09\n", "\n", "1985 \n", "07/16\n", "07/22\n", "08/11\n", "08/14\n", "08/28\n", "09/16\n", "09/17\n", "09/23\n", "10/07\n", "10/26\n", "11/15" ] }, { "cell_type": "raw", "id": "clean-pitch", "metadata": {}, "source": [ "First day when storms reached 17 m/s (TC genesis) - only including dates within NA hurricane season (06/01 - 11/30)\n", "1980\n", "\n", "08/02\n", "08/14\n", "08/21\n", "09/07\n", "09/05\n", "09/05\n", "09/06\n", "09/21\n", "10/04\n", "11/09\n", "11/25\n", "\n", "1981\n", "06/29\n", "08/03\n", "08/08\n", "09/01\n", "09/04\n", "09/08\n", "09/12\n", "09/23\n", "10/30\n", "11/04\n", "11/12\n", "\n", "1982\n", "06/03\n", "06/18\n", "08/28\n", "09/10\n", "09/14\n", "10/01\n", "\n", "1983 \n", "08/15\n", "08/24\n", "09/11\n", "09/26\n", "\n", "1984\n", "08/19\n", "08/29\n", "08/31\n", "08/31 (again)\n", "09/08\n", "09/14\n", "09/16\n", "09/18 \n", "09/23\n", "09/26 \n", "10/08\n", "11/06" ] }, { "cell_type": "code", "execution_count": 579, "id": "excessive-brook", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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level_0index\"yearmonthdayRMM1RMM2MJO phaseMJO amplitudemean have been removed in these RMMvalues; 20140101-: Only the 120-day has been removed.\",,,,,,,,,,,
315742558448NaN19977170.97950202-0.5132600141.10583WH04_method:_OLR_&_NCEP_wind,,,,,,,,,,,
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" ], "text/plain": [ " level_0 index \" year month day RMM1 RMM2 \\\n", "3157 4255 8448 NaN 1997 7 17 0.97950202 -0.51326001 \n", "\n", " MJO phase MJO amplitude mean have been removed in these RMM \\\n", "3157 4 1.10583 WH04_method:_OLR_&_NCEP_wind \n", "\n", " values; 20140101-: Only the 120-day has been removed.\",,,,,,,,,,, \n", "3157 ,,,,,,,,,,, " ] }, "execution_count": 579, "metadata": {}, "output_type": "execute_result" } ], "source": [] }, { "cell_type": "code", "execution_count": 24, "id": "integral-syntax", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "[8.0] [14.0] 6\n" ] } ], "source": [ "storm_dates(1980, 6)" ] }, { "cell_type": "code", "execution_count": 4, "id": "neutral-source", "metadata": { "scrolled": true }, "outputs": [], "source": [ "import numpy as np\n", "\n", "year = NA_tracks.YRT.values\n", "storm = NA_tracks.ZSTORM1.values\n", "\n", "# each year has 35 possible storm dates - day and month ?\n", "\n", "# find all date in a given year when storms underwent RI \n", "def storm_dates(yearnum, stormnum):\n", " RI_first_day = []\n", " RI_second_day = []\n", " RI_first_month = []\n", " RI_second_month = []\n", " # analyze all storms in a given year\n", " # find which index that yearnum is in year array to get wind speed data for just the year you want\n", " i = np.where(np.isclose(year, yearnum))\n", " j = np.where(np.isclose(storm, stormnum))\n", " # get arrays of day and month values in the year specified in the function argument\n", " index = np.asarray(i).item()\n", " index_j = np.asarray(j).item()\n", " # go thru each storm in a year and determine whether it underwent RI, extract dates\n", " # for each storm, determine whether the wind speed at a track point is at least 56.0 km per hour = 15.555555 m/s more than \n", " # the wind speed at a track point <= than 4 away (4 track points = 1 day)\n", " day = NA_tracks.DAY.values[index, index_j, :]\n", " day = day[~np.isnan(day)]\n", " month = NA_tracks.MONTH.values[index, index_j, :]\n", " month = month[~np.isnan(month)]\n", " wind = NA_tracks.WIND.values[index, index_j, :]\n", " wind = wind[~np.isnan(wind)] \n", " first_month = []\n", " first_day = []\n", " # https://realpython.com/python-first-match/\n", " for k in range(len(wind)):\n", " if (wind[k] >= 17):\n", " month_TS = month[k].tolist()\n", " day_TS = day[k].tolist()\n", " first_month.append(month_TS)\n", " first_day.append(day_TS)\n", " print(first_month, first_day)\n", " break\n", " \n", " " ] }, { "cell_type": "code", "execution_count": 45, "id": "western-trace", "metadata": {}, "outputs": [], "source": [ "storm_dates(1979, 35)" ] }, { "cell_type": "markdown", "id": "0cefe9e4-ca8d-461c-9510-542f800ff7f3", "metadata": {}, "source": [] }, { "cell_type": "markdown", "id": "white-donna", "metadata": {}, "source": [ "\n" ] }, { "cell_type": "code", "execution_count": null, "id": "touched-objective", "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": 125, "id": "included-pregnancy", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "35" ] }, "execution_count": 125, "metadata": {}, "output_type": "execute_result" } ], "source": [] } ], "metadata": { "kernelspec": { "display_name": "geoclim [~/home/GEOCLIM/software/anaconda3/2024.10/envs/geoclim/]", "language": "python", "name": "conda_geoclim" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.10.13" } }, "nbformat": 4, "nbformat_minor": 5 }