# How to build a STAC out of ERA5-land data?

**URL:** <https://discourse.pangeo.io/t/how-to-build-a-stac-out-of-era5-land-data/5167>\
**Category:** Data\
**Created:** [May 27, 2025, 10:04am UTC](https://discourse.pangeo.io/t/how-to-build-a-stac-out-of-era5-land-data/5167 "2025-05-27T10:04:11Z")\
**Posts on this page:** 4\
**Page:** 1

<div class="post-metadata">

**Author:** ![Martina](https://avatars.discourse-cdn.com/v4/letter/m/85f322/32.png) [@Martina](https://discourse.pangeo.io/u/Martina)\
**Post date:** [May 27, 2025, 10:04am UTC](https://discourse.pangeo.io/t/how-to-build-a-stac-out-of-era5-land-data/5167/1 "2025-05-27T10:04:11Z")

</div>

Hello everybody,

i’m trying to build a STAC catalog based on some data variables from the ERA5 land collection. The downloaded data (via the Climate Data Store) stores the time variable in the different bands of the NetCDF file, e.g. one file contains all the hourly time steps of a month for said variable.

Now, my understanding of the STAC nomenclature is that every item refers to a specific location and time. Therefore, i would like to reference the different bands to different items, with every item containing the data variables of that specific time step.

So my main question is: How can i formulate a “href” to point to a specific band within one file?

I found a pystac tutorial for multi-spectral data sets ([Create a STAC Item that Implements the EO Extension Using PySTAC | STAC Tutorials](https://stacspec.org/en/tutorials/3-create-stac-item-with-extension/)) which however would break the logic of one item referencing one specific location and time.

Another work-around i could think of is to export all the bands via gdal\_translate to single files and than build my STAC based on those files.

Any ideas and advise is very much appreciated!

Cheers,  
Martina

---

<div class="post-metadata">

**Author:** ![clausmichele](https://yyz2.discourse-cdn.com/flex030/user_avatar/discourse.pangeo.io/clausmichele/32/2665_2.png) [@clausmichele](https://discourse.pangeo.io/u/clausmichele)\
**Post date:** [May 27, 2025, 1:56pm UTC](https://discourse.pangeo.io/t/how-to-build-a-stac-out-of-era5-land-data/5167/2 "2025-05-27T13:56:03Z")

</div>

Hi Martina,

are you aware that B-Open, within the Destination Earth project, produced already a Zarr store with the ERA5 Land data, available as a STAC Item here [https://earthdatahub.destine.eu/api/stac/v1/collections/era5/items/reanalysis-era5-land](https://earthdatahub.destine.eu/api/stac/v1/collections/era5/items/reanalysis-era5-land) ? There’s an example on how to use it here: [https://earthdatahub.destine.eu/tutorials/tutorial-era5-land-floods-precipitation-anomaly-in-greece](https://earthdatahub.destine.eu/tutorials/tutorial-era5-land-floods-precipitation-anomaly-in-greece)

Let me know if you would still want to proceed in building your own STAC Collection, I’ll help you if needed.

---

<div class="post-metadata">

**Author:** ![Martina](https://avatars.discourse-cdn.com/v4/letter/m/85f322/32.png) [@Martina](https://discourse.pangeo.io/u/Martina)\
**Post date:** [May 28, 2025, 6:59am UTC](https://discourse.pangeo.io/t/how-to-build-a-stac-out-of-era5-land-data/5167/3 "2025-05-28T06:59:54Z")

</div>

Hi,

i did not know about the project and the Zarr store, that is very cool. I will test the STAC item but it seems like it is exactly what i was looking for!

Thanks a lot for sharing the information!

Best,  
Martina

---

<div class="post-metadata">

**Author:** ![rabernat](https://yyz2.discourse-cdn.com/flex030/user_avatar/discourse.pangeo.io/rabernat/32/22_2.png) [@rabernat](https://discourse.pangeo.io/u/rabernat)\
**Post date:** [May 28, 2025, 1:28pm UTC](https://discourse.pangeo.io/t/how-to-build-a-stac-out-of-era5-land-data/5167/4 "2025-05-28T13:28:19Z")

</div>

This thread highlights something quite interesting and important about how we think about STAC and Zarr.

The OP imagined she was going to download thousands of NetCDF files and treat each one as a STAC item.

@clausmichele pointed her at a _single STAC item representing the entire ERA5 dataset_.

These are extremely different ways of representing ERA5!