Comments (3)
Hi @SarahAlidoost, Freek shared the saptio-temporal data they would like to work with in #64. These data are more relevant than the KNMI dataset. I will copy his message here:
This is the link:
https://www.daggegevens.knmi.nl/klimatologie/uurgegevens
The idea would be to insert meteo data into the STM of the data (e.g. temperature, pressure) closest to the SAR satellite acquisition. (But maybe also: the sum of rainfall in the last 3 days, etc).
Furthermore, I attached:
- an example data file (just 1000 lines) knmi_stn280_example_file.txt
- two old Matlab scripts, handling the data. importMeteodata_knmi.zip
get_meteo.zip- .csv file with KNMI station locations knmistations.csv (see also https://github.com/MotionbyLearning/sandbox/tree/develop_vector_processing for an example implementation using these station locations made earlier (in the 'step 3' script).
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Might be useful to check:
https://github.com/Deltares/xugrid
https://xesmf.readthedocs.io/en/latest/
from stmtools.
this can be useful https://docs.xarray.dev/en/stable/generated/xarray.Dataset.interp_like.html#xarray-dataset-interp-like
example https://docs.xarray.dev/en/stable/generated/xarray.DataArray.interp_like.html#xarray.DataArray.interp_like
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Related Issues (20)
- software release HOT 3
- Extract time information in `from_csv` function
- From CSV to Zarr HOT 1
- Controlling output chunk size and type HOT 1
- Subset function: make thresholding lazy
- Doc: Add documentation for `get_order` and `re_order`
- Warnings in Unit Test
- Add performance test: should we add it? HOT 1
- A function to initiate an STM from scratch
- Investigate catalog method for contextual data archiving HOT 6
- Add API documentation
- How to handle the time reference system
- How to handle the Spatial Coordinate Reference system
- Github workflow in a pull request should only run on changed files
- Deprecation warning for Jupyter in mkdocs
- Performance warning in re-order
- Future warning `Dataset.dims`
- Unit test for duplicated points in an STM HOT 1
- Documentation for `enrich_from_dataset` function
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