# edh-docs > Earth Data Hub (EDH) is a Destination Earth (DestinE) service, operated by B-Open, that provides petabytes of analysis-ready, cloud-optimised (ARCO) Earth data, including ERA5, ERA5-Land, CMIP6, the Climate Adaptation Digital Twin (Climate DT), Copernicus DEM and Sentinel-1 ARD. EDH is built entirely on open standards: datasets are Zarr v3 stores streamed over HTTPS and discovered through a STAC catalogue, so any Zarr-capable tool works without a bespoke SDK. Python with Xarray (zarr-python 3 or later) is recommended. > > Main features and endpoints: > > - STAC catalogue: https://earthdatahub.destine.eu/api/stac/v1 (public, no API key). Each dataset is a STAC item whose `data` asset holds the dataset URL and the arguments to open it with Xarray. Interactive API reference: https://earthdatahub.destine.eu/api/stac/v1/api.html > - Zarr over HTTPS: datasets are served from https://data.earthdatahub.destine.eu as `/-v.zarr`, where a higher version number is newer. Take dataset URLs from STAC or the EDH website rather than guessing them. > - Authentication: a free API key from a DestinE Platform account (https://earthdatahub.destine.eu/quota-api-keys), sent as HTTP basic auth (user `edh`), a bearer token, or through a .netrc file. A public test dataset needs no key. https://api.earthdatahub.destine.eu is an alternative data host. > - Upgraded access: restricted datasets, such as the Climate DT collection, also require DestinE upgraded access. > - Quotas: 500,000 HTTP requests per user per month, where each Zarr chunk read counts as one request. Local caching with fsspec reduces repeated requests. > - Chunking: datasets are map-optimised or time series-optimised, and some are published in both layouts. > - Notebooks: Jupyter notebooks with examples, use cases and best practices, some of which run in the browser in Insula Code Lab. > > The Data Access page covers setup, authentication, quotas, caching and the full STAC and Zarr API reference. Troubleshooting covers common errors (401, 403, 426, 429 and Zarr v3 incompatibilities). Every page is available as Markdown, and llms-full.txt contains the complete documentation in one file. 2026, European Union ## Pages - [Discover EDH](https://earthdatahub.destine.eu/docs/discover-edh.md): Overview of Earth Data Hub (EDH): petabytes of analysis-ready, cloud-optimised Earth data in Zarr format, organised into collections and streamed over HTTP into standard tools with no bespoke software. - [Data Access](https://earthdatahub.destine.eu/docs/data-access.md): How to access Earth Data Hub datasets with any Zarr-capable tool, with examples in Python using Xarray (recommended): environment setup, a public test dataset, API keys, authenticating to protected datasets (key in URL or .netrc), upgraded access for restricted datasets such as Climate DT, the 500,000 requests/month quota, local chunk caching with fsspec simplecache, and the STAC catalogue and Zarr-over-HTTPS APIs. - [Core Concepts](https://earthdatahub.destine.eu/docs/core-concepts.md): Concepts behind Earth Data Hub: ARCO (analysis-ready, cloud-optimised) data on DestinE object storage with Zarr and a STAC catalogue, streaming only the chunks you need instead of downloading files, access with an API key and a dataset URL, and map-optimised versus time series-optimised chunking. - [Notebooks](https://earthdatahub.destine.eu/docs/notebooks.md): Index of Earth Data Hub example notebooks: EDH Learning (notebooks to run locally) and Insula Code Lab (tutorials that run in the browser). - [EDH Learning](https://earthdatahub.destine.eu/docs/notebooks/edh-learning.md): Gallery of EDH Learning Jupyter notebooks: getting started with Earth Data Hub, use cases with its datasets, and best practices for efficient data access. - [Getting started with the Earth Data Hub](https://earthdatahub.destine.eu/docs/notebooks/edh-learning/00-getting-started.md): This notebook explains the very first steps to get started with accessing data from the Earth Data Hub (EDH). - [Use case: ERA5-Land monthly averages over Europe](https://earthdatahub.destine.eu/docs/notebooks/edh-learning/05-era5-land-europe.md): Earth Data Hub offers an innovative and super-efficient way to access data. - [Use case: ERA5 on a small area](https://earthdatahub.destine.eu/docs/notebooks/edh-learning/10-use-case-era5-small-area.md): This notebook provides an example of how to compute various climatological averages of one ERA5 variable over a long period of time, e.g. the surface temperature over 30 years. - [Use case: CMIP6 temperature timeseries extraction](https://earthdatahub.destine.eu/docs/notebooks/edh-learning/20-use-case-cmip6-rome.md): This notebook provides an example of how to compare and visualise near-surface air temperature simulated by six different CMIP6 models. - [Use case: Copernicus DEM on a small area](https://earthdatahub.destine.eu/docs/notebooks/edh-learning/30-use-case-copernicus-dem-small-area.md): This notebook provides an example of how to access the Copernicus DEM on a small area, e.g. the surroundings of Rome, with Python and Xarray, and with the GDAL command line tools to crop and reproject it to GeoTIFF files. - [Use case: Sentinel-1 ARD on a small area](https://earthdatahub.destine.eu/docs/notebooks/edh-learning/50-use-case-sentinel-1-small-area.md): This notebook provides an example of how to compute various statistics of Sentinel-1 radiometrically corrected images over a period of time, e.g. over 1 year or 31 acquisition dates, using the Sentinel-1 ARD datasets over Rome, Italy. - [Best practice: transparently cache files on the local filesystem](https://earthdatahub.destine.eu/docs/notebooks/edh-learning/60-best-practice-local-cache-era5-small-area.md): This notebook demonstrates how to use transparent caching of the data chunks on the local file system by leveraging the simplecache directive of fsspec. This is especially useful on slow connections or to save on your EDH request quota. - [Insula Code Lab](https://earthdatahub.destine.eu/docs/notebooks/insula-code-lab.md): Gallery of Earth Data Hub tutorial notebooks that run in the browser in Insula Code Lab with no local installation, showing analyses with Earth Data Hub datasets. - [Climate Adaptation Digital Twin: climatological analysis of temperature in Germany](https://earthdatahub.destine.eu/docs/notebooks/insula-code-lab/tutorial-climate-dt-climatological-analysis-of-temperature-in-germany.md): This notebook demonstrates how to perform a climatological analysis of surface temperature in Germany using the EarthDataHub climate data. It includes steps for loading the data, calculating monthly means and standard deviations, and visualizing the results. - [Climate Adaptation Digital Twin: average temperature in Germany and Heating Degree Days in Darmstadt](https://earthdatahub.destine.eu/docs/notebooks/insula-code-lab/tutorial-climate-dt-heating-degree-days-in-darmstadt.md): This notebook demonstrates how to compute Heating Degree Days (HDD) for Darmstadt using ERA5-Land. - [How to work with the Copernicus DEM data on Earth Data Hub](https://earthdatahub.destine.eu/docs/notebooks/insula-code-lab/tutorial-copernicus-dem-europe.md): This notebook demonstrates how to visualize Copernicus DEM data for Europe using Python libraries such as Matplotlib and Cartopy. It includes steps for loading the data, reducing its resolution, and creating a contour plot with appropriate map features. - [How to work with the ‘Essential Climate Variables for assessment of climate variability from 1979 to present’on Earth Data Hub: analysis of worldwide temperature change from pre-industrial period](https://earthdatahub.destine.eu/docs/notebooks/insula-code-lab/tutorial-ecv-for-climate-change-global-temperature-change.md): This notebook demonstrates how to use the ECV for Climate Change dataset to analyze global temperature change. - [How to work with ERA5-Land on Earth Data Hub: storm Daniel flood, Greece 2023](https://earthdatahub.destine.eu/docs/notebooks/insula-code-lab/tutorial-era5-land-floods-precipitation-anomaly-in-greece.md): This notebook demonstrates how to use ERA5-Land data to analyze precipitation anomalies in Greece, particularly focusing on the year 2023 compared to historical data from 1993 to 2022. It includes data retrieval, processing, and visualization steps. - [How to work with ERA5 single levels on Earth Data Hub: climatological analysis of temperature in Germany](https://earthdatahub.destine.eu/docs/notebooks/insula-code-lab/tutorial-era5-single-levels-climatological-analysis-of-temperature-in-germany.md): This notebook demonstrates how to perform a climatological analysis of surface temperature in Germany using ERA5 single-level data. It includes steps for data retrieval, processing, and visualization. - [How to work with Hybrid gridded demographic data for the world, 1950-2020, on Earth Data Hub](https://earthdatahub.destine.eu/docs/notebooks/insula-code-lab/tutorial-hybrid-world-population.md): This notebook demonstrates how to use the EarthDataHub to access and visualize hybrid world population data. - [Multisource datasets integration: population weighted temperature from ERA5 and](https://earthdatahub.destine.eu/docs/notebooks/insula-code-lab/tutorial-population-weighted-temperature.md): This notebook demonstrates how to calculate population-weighted average temperature using ERA5-Land data and population data. - [Help](https://earthdatahub.destine.eu/docs/help.md): Index of Earth Data Hub help resources: FAQs and a troubleshooting guide for common errors. - [FAQs](https://earthdatahub.destine.eu/docs/help/faqs.md): Earth Data Hub FAQs: what the version number (v0, v1, …) in a dataset URL means, which version to use, and how often datasets are updated (monthly datasets by the third week of each month). - [Troubleshooting](https://earthdatahub.destine.eu/docs/help/troubleshooting.md): Fixes for common Earth Data Hub errors when opening datasets: Zarr v3 incompatibilities, 401 Unauthorized, 403 Forbidden (restricted datasets), 426 Upgrade Required (API key/domain mismatch), 429 Too Many Requests (exhausted quota), and misleading errors such as GroupNotFoundError when using the local cache. - [What’s new](https://earthdatahub.destine.eu/docs/whats-new.md): Changelog of Earth Data Hub dataset changes, with dates, breaking changes and migration guides for new dataset versions, format upgrades (e.g. Zarr v3) and discontinued datasets. ## Optional - [llms-full.txt](https://earthdatahub.destine.eu/docs/llms-full.txt): Complete documentation in a single file.