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time-chunking implementation and various omps-nm pairing fixes
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Maggie Bruckner
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Jun 16, 2023
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examples/jupyter_notebooks/Monet-example-omps_nm_raqms-time_chunk.ipynb
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| { | ||
| "cells": [ | ||
| { | ||
| "cell_type": "markdown", | ||
| "id": "51def9a8-dcf7-489c-a9e6-bc78886a7917", | ||
| "metadata": {}, | ||
| "source": [ | ||
| "## Implementation of processing over time intervals\n", | ||
| "\n", | ||
| "Testing of Melodies-Monet OMPS Nadir Mapper L2 pairing with time interval chunking" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "id": "64e61a73-ace6-4041-a194-fe26e7a6b126", | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "from melodies_monet import driver" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "id": "17e4ebe7-7b5e-4628-919d-7275dd088478", | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "an = driver.analysis()\n", | ||
| "an.control = '../yaml/control_omps_nm-raqms.yaml'\n", | ||
| "an.read_control()" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "id": "2bc2dc2d-5297-4827-aa3e-90052ea4b64c", | ||
| "metadata": { | ||
| "tags": [] | ||
| }, | ||
| "outputs": [], | ||
| "source": [ | ||
| "base_prefix = an.save['paired']['prefix']#.copy()\n", | ||
| "for t in an.time_intervals:\n", | ||
| " an.open_models(time_interval=t)\n", | ||
| " an.open_obs(time_interval=t)\n", | ||
| " \n", | ||
| " an.pair_data()\n", | ||
| " \n", | ||
| " # adjust saved name for file to include time interval bounds\n", | ||
| " an.save['paired']['prefix'] = base_prefix+'_'+t[0].strftime('%Y%m%d')+'_'+t[1].strftime('%Y%m%d')\n", | ||
| " an.save_analysis()" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "markdown", | ||
| "id": "a6ba95ad-f73a-4b68-8ae5-7858eee6c970", | ||
| "metadata": {}, | ||
| "source": [ | ||
| "Notes regarding satellite pairing methods:\n", | ||
| "- some additional development needed to deal with time chuncking. Some OMPS NM orbit files cross the day. This doesn't cause issues if it is within the specified time_interval, but data past the time_interval in the file will be dropped and currently will not be read in during the next time_interval\n", | ||
| "\n", | ||
| "- Satellite pairing bilinearly interpolates model data in time to satellite observation times. When observations are before (after) the first (last) model file, time interpolation is nearest-neighbor and only the first (last) file is used. Right now the time-interpolation does not take into account if processing is being done over time chunks. Impact should be minimal, as observations have been filtered to be within time_intervals and the model file subsetter should be selecting all the necessary files." | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "markdown", | ||
| "id": "8ddb4e95-1db0-4f01-b433-2d279b1d25fe", | ||
| "metadata": {}, | ||
| "source": [ | ||
| "### Read in saved paired data" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "id": "ce25d669-166a-42a0-861e-ceef59b26d34", | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "an = driver.analysis()\n", | ||
| "an.control = 'control_omps_nm-raqms.yaml'\n", | ||
| "an.read_control()\n", | ||
| "an.read_analysis()" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "id": "f41b0217-c3cf-4cde-996e-d6149cea5aa5", | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "import numpy as np\n", | ||
| "#an.paired['omps_nm_raqms'].obj = an.paired['omps_nm_raqms'].obj.swap_dims({'time':'x'})\n", | ||
| "an.paired['omps_nm_raqms'].obj['o3vmr'].values[np.isnan(an.paired['omps_nm_raqms'].obj['ozone_column'].values)] = np.nan\n", | ||
| "an.paired['omps_nm_raqms'].obj['o3vmr'].values[an.paired['omps_nm_raqms'].obj['o3vmr'].values < 50] = np.nan\n", | ||
| "an.paired['omps_nm_raqms'].obj['ozone_column'].values[np.isnan(an.paired['omps_nm_raqms'].obj['o3vmr'].values)] = np.nan\n", | ||
| "an.plotting()" | ||
| ] | ||
| } | ||
| ], | ||
| "metadata": { | ||
| "kernelspec": { | ||
| "display_name": "dev_monet", | ||
| "language": "python", | ||
| "name": "develop_monet" | ||
| }, | ||
| "language_info": { | ||
| "codemirror_mode": { | ||
| "name": "ipython", | ||
| "version": 3 | ||
| }, | ||
| "file_extension": ".py", | ||
| "mimetype": "text/x-python", | ||
| "name": "python", | ||
| "nbconvert_exporter": "python", | ||
| "pygments_lexer": "ipython3", | ||
| "version": "3.9.12" | ||
| } | ||
| }, | ||
| "nbformat": 4, | ||
| "nbformat_minor": 5 | ||
| } |
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| /ships19/aqda/lenzen/CalNex/UW-Hybrid/Mission_1X1/Netcdf4/190826/uwhyb_08_26_2019_18Z.chem.assim.nc | ||
| /ships19/aqda/lenzen/CalNex/UW-Hybrid/Mission_1X1/Netcdf4/190826/uwhyb_08_27_2019_00Z.chem.assim.nc | ||
| /ships19/aqda/lenzen/CalNex/UW-Hybrid/Mission_1X1/Netcdf4/190826/uwhyb_08_27_2019_06Z.chem.assim.nc | ||
| /ships19/aqda/lenzen/CalNex/UW-Hybrid/Mission_1X1/Netcdf4/190826/uwhyb_08_27_2019_12Z.chem.assim.nc | ||
| /ships19/aqda/lenzen/CalNex/UW-Hybrid/Mission_1X1/Netcdf4/190827/uwhyb_08_27_2019_18Z.chem.assim.nc | ||
| /ships19/aqda/lenzen/CalNex/UW-Hybrid/Mission_1X1/Netcdf4/190827/uwhyb_08_28_2019_00Z.chem.assim.nc | ||
| /ships19/aqda/lenzen/CalNex/UW-Hybrid/Mission_1X1/Netcdf4/190827/uwhyb_08_28_2019_06Z.chem.assim.nc | ||
| /ships19/aqda/lenzen/CalNex/UW-Hybrid/Mission_1X1/Netcdf4/190827/uwhyb_08_28_2019_12Z.chem.assim.nc | ||
| /ships19/aqda/lenzen/CalNex/UW-Hybrid/Mission_1X1/Netcdf4/190828/uwhyb_08_28_2019_18Z.chem.assim.nc | ||
| /ships19/aqda/lenzen/CalNex/UW-Hybrid/Mission_1X1/Netcdf4/190828/uwhyb_08_29_2019_00Z.chem.assim.nc | ||
| /ships19/aqda/lenzen/CalNex/UW-Hybrid/Mission_1X1/Netcdf4/190828/uwhyb_08_29_2019_06Z.chem.assim.nc | ||
| /ships19/aqda/lenzen/CalNex/UW-Hybrid/Mission_1X1/Netcdf4/190828/uwhyb_08_29_2019_12Z.chem.assim.nc | ||
| /ships19/aqda/lenzen/CalNex/UW-Hybrid/Mission_1X1/Netcdf4/190829/uwhyb_08_29_2019_18Z.chem.assim.nc | ||
| /ships19/aqda/lenzen/CalNex/UW-Hybrid/Mission_1X1/Netcdf4/190829/uwhyb_08_30_2019_00Z.chem.assim.nc | ||
| /ships19/aqda/lenzen/CalNex/UW-Hybrid/Mission_1X1/Netcdf4/190829/uwhyb_08_30_2019_06Z.chem.assim.nc | ||
| /ships19/aqda/lenzen/CalNex/UW-Hybrid/Mission_1X1/Netcdf4/190829/uwhyb_08_30_2019_12Z.chem.assim.nc | ||
| /ships19/aqda/lenzen/CalNex/UW-Hybrid/Mission_1X1/Netcdf4/190830/uwhyb_08_30_2019_18Z.chem.assim.nc | ||
| /ships19/aqda/lenzen/CalNex/UW-Hybrid/Mission_1X1/Netcdf4/190830/uwhyb_08_31_2019_00Z.chem.assim.nc | ||
| /ships19/aqda/lenzen/CalNex/UW-Hybrid/Mission_1X1/Netcdf4/190830/uwhyb_08_31_2019_06Z.chem.assim.nc | ||
| /ships19/aqda/lenzen/CalNex/UW-Hybrid/Mission_1X1/Netcdf4/190830/uwhyb_08_31_2019_12Z.chem.assim.nc | ||
| /ships19/aqda/lenzen/CalNex/UW-Hybrid/Mission_1X1/Netcdf4/190831/uwhyb_08_31_2019_18Z.chem.assim.nc | ||
| /ships19/aqda/lenzen/CalNex/UW-Hybrid/Mission_1X1/Netcdf4/190831/uwhyb_09_01_2019_00Z.chem.assim.nc | ||
| /ships19/aqda/lenzen/CalNex/UW-Hybrid/Mission_1X1/Netcdf4/190831/uwhyb_09_01_2019_06Z.chem.assim.nc | ||
| /ships19/aqda/lenzen/CalNex/UW-Hybrid/Mission_1X1/Netcdf4/190831/uwhyb_09_01_2019_12Z.chem.assim.nc |
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