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Add Met Office example notebooks #311

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ac5d8de
add Met Office example notebooks
mo-jeff Jan 15, 2026
e16b6db
fix: variable names and lint
gadomski Jan 22, 2026
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173 changes: 173 additions & 0 deletions datasets/met-office/met-office-global-deterministic-height.ipynb
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167 changes: 167 additions & 0 deletions datasets/met-office/met-office-global-deterministic-near-surface.ipynb
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173 changes: 173 additions & 0 deletions datasets/met-office/met-office-global-deterministic-pressure.ipynb
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168 changes: 168 additions & 0 deletions datasets/met-office/met-office-global-deterministic-whole-atmosphere.ipynb
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171 changes: 171 additions & 0 deletions datasets/met-office/met-office-uk-deterministic-height.ipynb
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149 changes: 149 additions & 0 deletions datasets/met-office/met-office-uk-deterministic-near-surface.ipynb
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{
"cells": [
{
"cell_type": "markdown",
"id": "fbf471b1",
"metadata": {},
"source": [
"# Accessing UK Model Surface data from Microsoft Planetary Computer"
]
},
{
"cell_type": "markdown",
"id": "941120d0",
"metadata": {},
"source": [
"Set-up the pystac client to access the Microsoft Planetary Computer catalog"
]
},
{
"cell_type": "code",
"execution_count": 1,
"id": "4bafd899",
"metadata": {},
"outputs": [],
"source": [
"from pystac_client import Client\n",
"import planetary_computer\n",
"\n",
"catalog = Client.open(\n",
" \"https://planetarycomputer.microsoft.com/api/stac/v1\",\n",
" modifier=planetary_computer.sign_inplace,\n",
")"
]
},
{
"cell_type": "markdown",
"id": "2cab8be1",
"metadata": {},
"source": [
"Define collection and assets to retrieve and construct [STAC API filters](https://github.com/stac-api-extensions/filter) for efficient query performance against Planetary Computer API"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "8f95ecac",
"metadata": {},
"outputs": [],
"source": [
"collections = [\"met-office-uk-deterministic-near-surface\"]\n",
"asset_id = \"temperature_at_surface\"\n",
"forecast_extension_filters = {\n",
" \"op\": \"and\",\n",
" \"args\": [\n",
" {\n",
" \"op\": \"=\",\n",
" \"args\": [\n",
" {\"property\": \"forecast:reference_datetime\"},\n",
" \"2026-01-21T09:00:00Z\",\n",
" ],\n",
" },\n",
" {\"op\": \"=\", \"args\": [{\"property\": \"forecast:horizon\"}, \"PT0054H00M\"]},\n",
" ],\n",
"}"
]
},
{
"cell_type": "markdown",
"id": "b5a6a858",
"metadata": {},
"source": [
"Search Planetary Computer catalog for STAC items and retrieve STAC Asset URL"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "edb71afa",
"metadata": {},
"outputs": [
{
"ename": "StopIteration",
"evalue": "",
"output_type": "error",
"traceback": [
"\u001b[31m---------------------------------------------------------------------------\u001b[39m",
"\u001b[31mStopIteration\u001b[39m Traceback (most recent call last)",
"\u001b[36mCell\u001b[39m\u001b[36m \u001b[39m\u001b[32mIn[19]\u001b[39m\u001b[32m, line 6\u001b[39m\n\u001b[32m 1\u001b[39m search = catalog.search(\n\u001b[32m 2\u001b[39m collections=collections,\n\u001b[32m 3\u001b[39m datetime=\u001b[33m\"\u001b[39m\u001b[33m2026-01-21T09:00:00Z\u001b[39m\u001b[33m\"\u001b[39m,\n\u001b[32m 4\u001b[39m )\n\u001b[32m----> \u001b[39m\u001b[32m6\u001b[39m asset_url = \u001b[38;5;28;43mnext\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43mitem\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43;01mfor\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43mitem\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;129;43;01min\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43msearch\u001b[49m\u001b[43m.\u001b[49m\u001b[43mitems\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43;01mif\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43mitem\u001b[49m\u001b[43m.\u001b[49m\u001b[43mproperties\u001b[49m\u001b[43m[\u001b[49m\u001b[33;43m\"\u001b[39;49m\u001b[33;43mforecast:horizon\u001b[39;49m\u001b[33;43m\"\u001b[39;49m\u001b[43m]\u001b[49m\u001b[43m \u001b[49m\u001b[43m==\u001b[49m\u001b[43m \u001b[49m\u001b[33;43m\"\u001b[39;49m\u001b[33;43mPT0054H00M\u001b[39;49m\u001b[33;43m\"\u001b[39;49m\u001b[43m)\u001b[49m.assets[asset_id].href\n",
"\u001b[31mStopIteration\u001b[39m: "
]
}
],
"source": [
"search = catalog.search(\n",
" collections=collections,\n",
" filter_lang=\"cql2-json\",\n",
" filter=forecast_extension_filters,\n",
")\n",
"\n",
"asset_url = next(search.items()).assets[asset_id].href"
]
},
{
"cell_type": "markdown",
"id": "56d27e19",
"metadata": {},
"source": [
"Example usage: Plot NetCDF data on a map"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "45613dda",
"metadata": {},
"outputs": [],
"source": [
"import fsspec\n",
"import xarray as xr\n",
"import matplotlib.pyplot as plt\n",
"\n",
"example_netcdf = xr.open_dataset(fsspec.open(asset_url, expand=True).open())\n",
"plt.figure(figsize=(10, 5))\n",
"example_netcdf[\"surface_temperature\"].plot()"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "PlanetaryComputerExamples",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.13.2"
}
},
"nbformat": 4,
"nbformat_minor": 5
}
136 changes: 136 additions & 0 deletions datasets/met-office/met-office-uk-deterministic-pressure.ipynb
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{
"cells": [
{
"cell_type": "markdown",
"id": "fbf471b1",
"metadata": {},
"source": [
"# Accessing UK Model Pressure Level data from Microsoft Planetary Computer"
]
},
{
"cell_type": "markdown",
"id": "941120d0",
"metadata": {},
"source": [
"Set-up the pystac client to access the Microsoft Planetary Computer catalog"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "4bafd899",
"metadata": {},
"outputs": [],
"source": [
"from pystac_client import Client\n",
"import planetary_computer\n",
"\n",
"catalog = Client.open(\n",
" \"https://planetarycomputer.microsoft.com/api/stac/v1\",\n",
" modifier=planetary_computer.sign_inplace,\n",
")"
]
},
{
"cell_type": "markdown",
"id": "2cab8be1",
"metadata": {},
"source": [
"Define collection and assets to retrieve and construct [STAC API filters](https://github.com/stac-api-extensions/filter) for efficient query performance against Planetary Computer API"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "8f95ecac",
"metadata": {},
"outputs": [],
"source": [
"collections = [\"met-office-uk-deterministic-pressure\"]\n",
"asset_id = \"wet_bulb_potential_temperature_on_pressure_levels\"\n",
"forecast_extension_filters = {\n",
" \"op\": \"and\",\n",
" \"args\": [\n",
" {\n",
" \"op\": \"=\",\n",
" \"args\": [\n",
" {\"property\": \"forecast:reference_datetime\"},\n",
" \"2026-01-14T12:00:00Z\",\n",
" ],\n",
" },\n",
" {\"op\": \"=\", \"args\": [{\"property\": \"forecast:horizon\"}, \"PT0052H00M\"]},\n",
" ],\n",
"}"
]
},
{
"cell_type": "markdown",
"id": "b5a6a858",
"metadata": {},
"source": [
"Search Planetary Computer catalog for STAC items and retrieve STAC Asset URL"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "edb71afa",
"metadata": {},
"outputs": [],
"source": [
"search = catalog.search(\n",
" collections=collections, filter_lang=\"cql2-json\", filter=forecast_extension_filters\n",
")\n",
"\n",
"items = search.item_collection()\n",
"asset_url = items.items[0].assets[asset_id].href"
]
},
{
"cell_type": "markdown",
"id": "56d27e19",
"metadata": {},
"source": [
"Example usage: Plot NetCDF data on a map"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "45613dda",
"metadata": {},
"outputs": [],
"source": [
"import fsspec\n",
"import xarray as xr\n",
"import matplotlib.pyplot as plt\n",
"\n",
"example_netcdf = xr.open_dataset(fsspec.open(asset_url, expand=True).open())\n",
"plt.figure(figsize=(10, 5))\n",
"example_netcdf[\"wet_bulb_potential_temperature\"].plot()"
]
}
],
"metadata": {
"kernelspec": {
"display_name": ".venv",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.13.11"
}
},
"nbformat": 4,
"nbformat_minor": 5
}
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