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ADD: Gridding with fasr-barnes-py #55 from syedhamidali/gridding-test
ADD: Gridding and AWS tools
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@@ -30,3 +30,4 @@ repos: | |
| hooks: | ||
| - id: black | ||
| - id: black-jupyter | ||
| args: ["--line-length", "88"] | ||
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,180 @@ | ||
| { | ||
| "cells": [ | ||
| { | ||
| "cell_type": "markdown", | ||
| "metadata": {}, | ||
| "source": [ | ||
| "# Grid Radar -> Plot Max-CAPPI" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "markdown", | ||
| "metadata": {}, | ||
| "source": [ | ||
| "We are using [fast-barnes-py](https://github.com/MeteoSwiss/fast-barnes-py.git) to grid the radar data. Please cite if you use it in your research." | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "import fsspec\n", | ||
| "import radarx as rx\n", | ||
| "import xradar as xd\n", | ||
| "import cmweather # noqa\n", | ||
| "import matplotlib.pyplot as plt" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "file = \"s3://noaa-nexrad-level2/2022/03/30/KGWX/KGWX20220330_234639_V06\"\n", | ||
| "local_file = fsspec.open_local(\n", | ||
| " f\"simplecache::s3://{file}\",\n", | ||
| " s3={\"anon\": True},\n", | ||
| " filecache={\"cache_storage\": \".\"},\n", | ||
| ")\n", | ||
| "dtree = xd.io.open_nexradlevel2_datatree(local_file)\n", | ||
| "dtree = rx.combine_nexrad_sweeps(dtree)\n", | ||
| "dtree = dtree.xradar.georeference()" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "dtree.groups" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "def filter_radar(ds):\n", | ||
| " ds = ds.where((ds.DBZH > -10) & (ds.DBZH < 75))\n", | ||
| " return ds" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "dtree = dtree.xradar.map_over_sweeps(filter_radar)" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "# Create a figure and axis\n", | ||
| "fig, ax = plt.subplots(figsize=(7, 5))\n", | ||
| "dtree[\"sweep_2\"][\"DBZH\"].plot.contourf(\n", | ||
| " x=\"x\",\n", | ||
| " y=\"y\",\n", | ||
| " levels=range(-10, 75),\n", | ||
| " cmap=\"NWSRef\",\n", | ||
| " ylim=(-200e3, 300e3), # Adjust y-axis limits\n", | ||
| " xlim=(-200e3, 300e3), # Adjust x-axis limits\n", | ||
| " ax=ax, # Use the created axis\n", | ||
| ")\n", | ||
| "# Set the title\n", | ||
| "ax.set_title(\n", | ||
| " f\"{dtree.attrs['instrument_name']} {dtree['sweep_0']['time'].min().values}\"\n", | ||
| ")\n", | ||
| "# Show the plot\n", | ||
| "plt.show()" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "%%time\n", | ||
| "ds = dtree.radarx.to_grid(\n", | ||
| " data_vars=[\"DBZH\"],\n", | ||
| " pseudo_cappi=True,\n", | ||
| " x_lim=(-100000.0, 100000.0),\n", | ||
| " y_lim=(-100000.0, 100000.0),\n", | ||
| " z_lim=(0, 10000.0),\n", | ||
| " x_step=1000,\n", | ||
| " y_step=1000,\n", | ||
| " z_step=250,\n", | ||
| " x_smth=0.2,\n", | ||
| " y_smth=0.2,\n", | ||
| " z_smth=1,\n", | ||
| ")" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "ds.radarx.plot_max_cappi(\"DBZH\", cmap=\"ChaseSpectral\", add_slogan=True)" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "%%time\n", | ||
| "ds2 = dtree.radarx.to_grid(\n", | ||
| " data_vars=[\"DBZH\"],\n", | ||
| " pseudo_cappi=False,\n", | ||
| " x_lim=(-200000.0, 200000.0),\n", | ||
| " y_lim=(-200000.0, 200000.0),\n", | ||
| " z_lim=(0, 15000.0),\n", | ||
| " x_step=1000,\n", | ||
| " y_step=1000,\n", | ||
| " z_step=250,\n", | ||
| " x_smth=0.2,\n", | ||
| " y_smth=0.2,\n", | ||
| " z_smth=1,\n", | ||
| ")" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "ds2.radarx.plot_max_cappi(\"DBZH\", cmap=\"ChaseSpectral\", add_slogan=True)" | ||
| ] | ||
| } | ||
| ], | ||
| "metadata": { | ||
| "language_info": { | ||
| "codemirror_mode": { | ||
| "name": "ipython", | ||
| "version": 3 | ||
| }, | ||
| "file_extension": ".py", | ||
| "mimetype": "text/x-python", | ||
| "name": "python", | ||
| "nbconvert_exporter": "python", | ||
| "pygments_lexer": "ipython3", | ||
| "version": "3.12.7" | ||
| } | ||
| }, | ||
| "nbformat": 4, | ||
| "nbformat_minor": 2 | ||
| } |
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