|
| 1 | +{ |
| 2 | + "cells": [ |
| 3 | + { |
| 4 | + "cell_type": "markdown", |
| 5 | + "id": "01687b54", |
| 6 | + "metadata": {}, |
| 7 | + "source": [ |
| 8 | + "## Accessing NOAA HRRR data with the Planetary Computer STAC API\n", |
| 9 | + "\n", |
| 10 | + "The [NOAA High-Resolution Rapid Refresh (HRRR)](https://rapidrefresh.noaa.gov/hrrr/) is a real-time 3-km resolution, hourly updated, cloud-resolving, convection-allowing atmospheric model, initialized by 3km grids with 3km radar assimilation.\n", |
| 11 | + "Radar data is assimilated in the HRRR every 15 min over a 1-h period adding further detail to that provided by the hourly data assimilation from the 13km radar-enhanced Rapid Refresh . \n", |
| 12 | + "\n", |
| 13 | + "This notebook demonstrates use of the Planetary Computer STAC API to query for NOAA HRRR data." |
| 14 | + ] |
| 15 | + }, |
| 16 | + { |
| 17 | + "cell_type": "markdown", |
| 18 | + "id": "38a3b9f0", |
| 19 | + "metadata": {}, |
| 20 | + "source": [ |
| 21 | + "### Environment setup\n", |
| 22 | + "\n", |
| 23 | + "We import all classes, modules, and function at the top to be explicit about what packages you'll need." |
| 24 | + ] |
| 25 | + }, |
| 26 | + { |
| 27 | + "cell_type": "code", |
| 28 | + "execution_count": null, |
| 29 | + "id": "de8f1804", |
| 30 | + "metadata": {}, |
| 31 | + "outputs": [], |
| 32 | + "source": [ |
| 33 | + "from pystac_client import Client\n", |
| 34 | + "import planetary_computer" |
| 35 | + ] |
| 36 | + }, |
| 37 | + { |
| 38 | + "cell_type": "markdown", |
| 39 | + "id": "b447c2b2", |
| 40 | + "metadata": {}, |
| 41 | + "source": [ |
| 42 | + "### Data access\n", |
| 43 | + "\n", |
| 44 | + "The datasets hosted by the Planetary Computer are available from [Azure Blob Storage](https://docs.microsoft.com/en-us/azure/storage/blobs/).\n", |
| 45 | + "We'll use [pystac-client](https://pystac-client.readthedocs.io/) to search the Planetary Computer's [STAC API](https://planetarycomputer.microsoft.com/api/stac/v1/docs) for data in our date and time of interest, and then we'll load the data directly from Azure Blob Storage.\n", |
| 46 | + "We'll specify a `modifier` so that we can access the data stored in the Planetary Computer's private Blob Storage Containers.\n", |
| 47 | + "See [Reading from the STAC API](https://planetarycomputer.microsoft.com/docs/quickstarts/reading-stac/) and [Using tokens for data access](https://planetarycomputer.microsoft.com/docs/concepts/sas/) for more." |
| 48 | + ] |
| 49 | + }, |
| 50 | + { |
| 51 | + "cell_type": "code", |
| 52 | + "execution_count": null, |
| 53 | + "id": "f3cfb7a9", |
| 54 | + "metadata": {}, |
| 55 | + "outputs": [], |
| 56 | + "source": [ |
| 57 | + "client = Client.open(\n", |
| 58 | + " \"https://planetarycomputer.microsoft.com/api/stac/v1\",\n", |
| 59 | + " modifier=planetary_computer.sign_inplace,\n", |
| 60 | + ")" |
| 61 | + ] |
| 62 | + } |
| 63 | + ], |
| 64 | + "metadata": { |
| 65 | + "kernelspec": { |
| 66 | + "display_name": "PlanetaryComputerExamples", |
| 67 | + "language": "python", |
| 68 | + "name": "python3" |
| 69 | + }, |
| 70 | + "language_info": { |
| 71 | + "name": "python", |
| 72 | + "version": "3.13.2" |
| 73 | + } |
| 74 | + }, |
| 75 | + "nbformat": 4, |
| 76 | + "nbformat_minor": 5 |
| 77 | +} |
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