diff --git a/docs/Service/Data_Portfolio.md b/docs/Service/Data_Portfolio.md index d9f001d0..5607ee08 100644 --- a/docs/Service/Data_Portfolio.md +++ b/docs/Service/Data_Portfolio.md @@ -125,3 +125,26 @@ If `levtype` is `pl`, a `levelist` must be provided: For `sfc`, most `params` are available. Currently, only data for `dates` between `2020` and `2050` is available. + +## Open Data + +The following key value pairs are available via Polytope: + +* `class` : `ai` +* `stream` : `oper` +* `type` : `fc` +* `model` : `aifs-single` +* `levtype` : `sfc` `pl` `ml` +* `expver` : `0001` +* `domain` : `g` +* `step` : `0/to/360` (All steps may not be available between `0` and `360`) + +If `levtype` is `pl` or `ml`, a `levelist` must be provided: + +* `levelist` : `1/to/1000` + +Only data that is contained in the open data FDB can be requested via Polytope feature extraction. The FDB usually only contains the last three-five days of forecasts. + +We sometimes limit the size of requests for area features such as bounding box and polygon to maintain quality of service. + +Access to open data is limited by our release schedule. diff --git a/docs/Service/Examples/OpenData/od_boundingbox.ipynb b/docs/Service/Examples/OpenData/od_boundingbox.ipynb new file mode 100644 index 00000000..e203e1b2 --- /dev/null +++ b/docs/Service/Examples/OpenData/od_boundingbox.ipynb @@ -0,0 +1,703 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Bounding Box Open Data Example" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "import earthkit.data\n", + "\n", + "request = {\n", + " \"class\": \"ai\",\n", + " \"stream\" : \"oper\",\n", + " \"type\" : \"fc\",\n", + " \"date\" : -1,\n", + " \"time\" : \"0000\",\n", + " \"levtype\" : \"sfc\",\n", + " \"expver\" : \"0001\", \n", + " \"model\": \"aifs-single\",\n", + " \"domain\" : \"g\",\n", + " \"param\" : \"166/167/169\",\n", + " \"step\" : \"0\",\n", + " \"feature\" : {\n", + " \"type\" : \"boundingbox\",\n", + " \"points\" : [[53.55, 2.76], [50.66, 7.86]],\n", + "\t},\n", + "}\n", + "\n", + "\n", + "ds = earthkit.data.from_source(\n", + " \"polytope\",\n", + " \"ecmwf-mars\",\n", + " request,\n", + " stream=False,\n", + " address='polytope.ecmwf.int',\n", + ")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Convert to xarray" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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+       "    domain:         g\n",
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+       "    levtype:        sfc\n",
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" + ], + "text/plain": [ + " Size: 7kB\n", + "Dimensions: (datetimes: 1, number: 1, steps: 1, points: 126)\n", + "Coordinates:\n", + " * datetimes (datetimes) " + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "da = ds.to_xarray()\n", + "import earthkit.plots\n", + "chart = earthkit.plots.Map(domain=\"Europe\")\n", + "chart.point_cloud(da['2t'], x=\"y\", y=\"x\")\n", + "\n", + "chart.coastlines()\n", + "chart.borders()\n", + "chart.gridlines()\n", + "\n", + "chart.title(\"{variable_name} (number={number})\")\n", + "\n", + "chart.legend()\n", + "\n", + "chart.show()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "polytope_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": "3.11.8" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/docs/Service/Examples/OpenData/od_country_example.ipynb b/docs/Service/Examples/OpenData/od_country_example.ipynb new file mode 100644 index 00000000..c2651be6 --- /dev/null +++ b/docs/Service/Examples/OpenData/od_country_example.ipynb @@ -0,0 +1,578 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Country Cutout Open Data Example" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "This example shows the users how to use earthkit-geo (https://earthkit-geo.readthedocs.io) to retrieve a country cutout using Polytope." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "import earthkit\n", + "import earthkit.plots\n", + "import earthkit.geo.cartography\n", + "\n", + "countries = [\"France\", \"Italy\", \"Spain\"] # List of countries\n", + "\n", + "shapes = earthkit.geo.cartography.country_polygons(countries, resolution=50e6)\n", + "\n", + "request = { \n", + " \"class\": \"ai\",\n", + " \"stream\" : \"oper\",\n", + " \"type\" : \"fc\",\n", + " \"date\" : -1,\n", + " \"time\" : \"0000\",\n", + " \"levtype\" : \"sfc\",\n", + " \"expver\" : \"0001\", \n", + " \"model\": \"aifs-single\",\n", + " \"domain\" : \"g\",\n", + " \"param\" : \"166/167/169\",\n", + " \"step\" : \"0\",\n", + " \"feature\": {\n", + " \"type\": \"polygon\",\n", + " \"shape\": shapes,\n", + " },\n", + "}\n", + "\n", + "ds = earthkit.data.from_source(\"polytope\", \"ecmwf-mars\", request, stream=False, address='polytope.ecmwf.int')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The collection being accessed is `ecmwf-mars`. The endpoint being accessed is `polytope.ecmwf.int`. Earthkit-geo is used to return the shape of the requested countries." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "A user can also convert the data to xarray in the following way:" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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+       "    levtype:        sfc\n",
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\n", + " Note: This notebook is rendered in many different ways depending on where you are viewing it (e.g. GitHub, Jupyter, readthedocs etc.). To maximise compatibility with many possible rendering methods, all interactive plots are rendered with chart.show(renderer=\"png\"), which removes all interactivity and only shows a PNG image render.

\n", + " If you are running this notebook in an interactive session yourself and would like to interact with the plots, remove the renderer=\"png\" argument from each call to chart.show().\n", + "
" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [], + "source": [ + "def location_to_string(location):\n", + " \"\"\"\n", + " Converts latitude and longitude to a string representation with degrees\n", + " and N/S/E/W.\n", + " \"\"\"\n", + " (lat, lon) = location[0]\n", + " lat_dir = \"N\" if lat >= 0 else \"S\"\n", + " lon_dir = \"E\" if lon >= 0 else \"W\"\n", + " return f\"{abs(lat):.2f}°{lat_dir}, {abs(lon):.2f}°{lon_dir}\"" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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" + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "from earthkit.plots.interactive import Chart\n", + "\n", + "TIME_FREQUENCY = \"6h\"\n", + "QUANTILES = [0, 0.1, 0.25, 0.5, 0.75, 0.9, 1]\n", + "\n", + "chart = Chart()\n", + "chart.title(f\"ECMWF ensemble meteogram at {location_to_string(LOCATION)}\")\n", + "#chart.box(ds, time_frequency=TIME_FREQUENCY, quantiles=QUANTILES)\n", + "chart.line(ds, line_color='grey', time_frequency=TIME_FREQUENCY)\n", + "chart.show(renderer=\"png\") # Replace with chart.show() in an interactive session!" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Convert to Xarray" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + " Size: 2kB\n", + "Dimensions: (x: 1, y: 1, z: 1, number: 1, datetime: 1, t: 61)\n", + "Coordinates:\n", + " * x (x) float64 8B 0.9836\n", + " * y (y) float64 8B 2.812\n", + " * z (z) int64 8B 0\n", + " * number (number) int64 8B 0\n", + " * datetime (datetime) \n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "
<xarray.Dataset> Size: 80kB\n",
+       "Dimensions:    (datetimes: 1, number: 1, steps: 1, points: 1254)\n",
+       "Coordinates:\n",
+       "  * datetimes  (datetimes) <U20 80B '2025-02-24T00:00:00Z'\n",
+       "  * number     (number) int64 8B 0\n",
+       "  * steps      (steps) int64 8B 0\n",
+       "  * points     (points) int64 10kB 0 1 2 3 4 5 ... 1248 1249 1250 1251 1252 1253\n",
+       "    x          (points) float64 10kB -0.4215 -0.4215 -0.4215 ... 50.16 50.44\n",
+       "    y          (points) float64 10kB 0.0 0.2812 359.7 0.0 ... 10.0 10.42 10.0\n",
+       "    level      (points) float64 10kB 0.0 0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0 0.0\n",
+       "    time       (points) int64 10kB 0 0 0 0 0 0 0 0 0 0 0 ... 0 0 0 0 0 0 0 0 0 0\n",
+       "Data variables:\n",
+       "    10v        (datetimes, number, steps, points) float64 10kB 0.4052 ... 1.475\n",
+       "    2t         (datetimes, number, steps, points) float64 10kB 298.6 ... 277.1\n",
+       "    ssrd       (datetimes, number, steps, points) float64 10kB 0.0 0.0 ... 0.0\n",
+       "Attributes:\n",
+       "    class:          ai\n",
+       "    Forecast date:  2025-02-24T00:00:00Z\n",
+       "    domain:         g\n",
+       "    expver:         0102\n",
+       "    levtype:        sfc\n",
+       "    model:          aifs-single\n",
+       "    step:           0\n",
+       "    stream:         oper\n",
+       "    type:           fc\n",
+       "    number:         0
" + ], + "text/plain": [ + " Size: 80kB\n", + "Dimensions: (datetimes: 1, number: 1, steps: 1, points: 1254)\n", + "Coordinates:\n", + " * datetimes (datetimes) " + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "import earthkit.plots\n", + "\n", + "chart = earthkit.plots.Map()\n", + "chart.point_cloud(da['2t'], x=\"y\", y=\"x\")\n", + "chart.coastlines()\n", + "chart.borders()\n", + "chart.title(\"{variable_name}\")\n", + "chart.legend()\n", + "chart.show()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "polytope_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": "3.11.8" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/docs/Service/Examples/OpenData/od_vertical_profile_example.ipynb b/docs/Service/Examples/OpenData/od_vertical_profile_example.ipynb new file mode 100644 index 00000000..f048f51a --- /dev/null +++ b/docs/Service/Examples/OpenData/od_vertical_profile_example.ipynb @@ -0,0 +1,152 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Vertical Profile Open Data Example" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "import earthkit.data\n", + "\n", + "request = {\n", + " \"class\": \"ai\",\n", + " \"stream\" : \"oper\",\n", + " \"type\" : \"fc\",\n", + " \"date\" : -1,\n", + " \"time\" : \"0000\",\n", + " \"levtype\" : \"pl\",\n", + " \"expver\" : \"0001\", \n", + " \"model\": \"aifs-single\",\n", + " \"domain\" : \"g\",\n", + " \"param\" : \"130\",\n", + " \"step\" : \"0\",\n", + " \"levelist\" : \"0/to/1000\",\n", + " \"feature\": {\n", + " \"type\": \"verticalprofile\",\n", + " \"points\": [[38.9, -9.1]],\n", + " },\n", + "}\n", + "\n", + "ds = earthkit.data.from_source(\"polytope\", \"ecmwf-mars\", request, stream=False, address='polytope.ecmwf.int')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Visualise \n", + "\n", + "The following visualisation uses [earthkit-plots](https://earthkit-plots.readthedocs.io/en/latest/).\n", + "\n", + "
\n", + " Note: This notebook is rendered in many different ways depending on where you are viewing it (e.g. GitHub, Jupyter, readthedocs etc.). To maximise compatibility with many possible rendering methods, all interactive plots are rendered with chart.show(renderer=\"png\"), which removes all interactivity and only shows a PNG image render.

\n", + " If you are running this notebook in an interactive session yourself and would like to interact with the plots, remove the renderer=\"png\" argument from each call to chart.show().\n", + "
" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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" + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "from earthkit.plots.interactive import Chart\n", + "\n", + "chart = Chart()\n", + "chart.line(ds, y=\"level\")\n", + "chart.fig.update_layout(yaxis1={\"title\": \"hPa\"})\n", + "chart.fig.update_layout(yaxis2={\"title\": \"hPa\"})\n", + "chart.show(renderer=\"png\") # Replace with chart.show() in an interactive session!" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Convert to Xarray" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + " Size: 320B\n", + "Dimensions: (x: 1, y: 1, number: 1, datetime: 1, time: 1, level: 13)\n", + "Coordinates:\n", + " * x (x) float64 8B 38.92\n", + " * y (y) float64 8B 350.9\n", + " * number (number) int64 8B 0\n", + " * datetime (datetime) Timeseries * Polygon * Vertical Profile @@ -7,6 +9,15 @@ * Trajectory * Country Cut-Out +## Open Data + +* Timeseries +* Timeseries +* Timeseries +* Timeseries +* Timeseries +* Timeseries + For examples of Polytope Feature Extraction on Destination Earth Digital Twin Data please visit the following Github Repo: https://github.com/destination-earth-digital-twins/polytope-examples It contains examples for both the Climate DT and the Extremes DT. \ No newline at end of file