Esa-climate-toolbox

* Support numpy >= 2.0 and pydap >= 3.4
* Automatically publish packages on pypi at release
* Improved support of vector data cubes
* Support HR LC data
* Added user functions for regions:
* `get_land_mask`: Gets a land mask for a dataset.
* `get_regions_mask`: Gets a regions mask for a dataset.
* `make_regions_dataset`: Rasterize country and continent polygons into a
grid provided by a template dataset.
* `mask_dataset_by_land`: Masks out non-land-pixels of a dataset.
* `mask_dataset_by_regions`: Masks out pixels of a dataset which are not in
one of the specified regions.
* Added notebooks:
* `ESA CCI Toolbox Vector Data Cube Access`: Explaining the handling of
vector data cubes
* `Using the ESA CCI Toolbox with the xcube Viewer`: Explaining how to access
the xcube viewer from within a Jupyter Notebook
* Extended documentation by a section on how to configure an xcube server to
serve data from the ESA CCI Toolbox

* Updated list of dataset states
* Improved dependencies
* Adapted coregistration to work with latest version of xarray

* Pinned numpy to <2.0, as numpy 2.0 causes errors

* Added operations:
* `add_dataset_values_to_geodataframe`:
Adds values from a dataset to a geodataframe
* `as_geodataframe`: Ensures a dataframe is a geodataframe
* `to_dataframe`: Converts a dataset to a dataframe
* `to_dataset`: Converts a dataframe to a dataset
* `animate_map`: Creates a geographic map animation
* `plot`: Create a 1D/line or 2D/image plot
* `plot_contour`: Create a contour plot
* `plot_hist`: Creates a histogram of a variable
* `plot_line`: Creates a 1D/line plot
* `plot_map`: Creates a geographic map plot
* `plot_scatter`: Creates a scatter plot of two variables
* The ESA CCI Toolbox now also affords opening the following datasets:
* As xarray datasets:
* esacci.ICESHEETS.unspecified.L4.SEC.multi-sensor.multi-platform.UNSPECIFIED.0-1.greenland_sec_saral_altika
* esacci.ICESHEETS.yr.Unspecified.SEC.SIRAL.CryoSat-2.UNSPECIFIED.2-2.greenland_sec_cryosat_2yr
* esacci.ICESHEETS.yr.Unspecified.SEC.SIRAL.CryoSat-2.UNSPECIFIED.2-2.greenland_sec_cryosat_5yr
* esacci.SEALEVEL.mon.IND.MSL.multi-sensor.multi-platform.MERGED.2-0.r1
* esacci.SEALEVEL.mon.L4.MSLA.multi-sensor.multi-platform.MERGED.2-0.r1
* As geodataframes:
* esacci.AEROSOL.satellite-orbit-frequency.L2P.AER_PRODUCTS.AATSR.Envisat.AATSR-ENVISAT-ENS.v2-6.r1
* esacci.AEROSOL.satellite-orbit-frequency.L2P.AER_PRODUCTS.AATSR.Envisat.ADV.2-31.r1
* esacci.AEROSOL.satellite-orbit-frequency.L2P.AER_PRODUCTS.AATSR.Envisat.ORAC.04-01.r1
* esacci.AEROSOL.satellite-orbit-frequency.L2P.AER_PRODUCTS.AATSR.Envisat.SU.4-3.r1
* esacci.AEROSOL.satellite-orbit-frequency.L2P.AER_PRODUCTS.ATSR-2.ERS-2.ADV.2-31.r1
* esacci.AEROSOL.satellite-orbit-frequency.L2P.AER_PRODUCTS.ATSR-2.ERS-2.ORAC.04-01.r1
* esacci.AEROSOL.satellite-orbit-frequency.L2P.AER_PRODUCTS.ATSR-2.ERS-2.SU.4-3.r1
* esacci.AEROSOL.satellite-orbit-frequency.L2P.AER_PRODUCTS.multi-sensor.multi-platform.ATSR2-ENVISAT-ENS.v2-6.r1
* esacci.AEROSOL.satellite-orbit-frequency.L2P.AOD.MERIS.Envisat.MERIS_ENVISAT.2-2.r1
* esacci.ICESHEETS.unspecified.Unspecified.CFL.multi-sensor.multi-platform.UNSPECIFIED.v3-0.greenland
* esacci.ICESHEETS.unspecified.Unspecified.GLL.multi-sensor.multi-platform.UNSPECIFIED.v1-3.greenland
* As vector data cubes:
* esacci.ICESHEETS.yr.Unspecified.GMB.GRACE-instrument.GRACE.UNSPECIFIED.1-2.greenland_gmb_mass_trends
* esacci.ICESHEETS.yr.Unspecified.GMB.GRACE-instrument.GRACE.UNSPECIFIED.1-3.greenland_gmb_mass_trends
* esacci.ICESHEETS.yr.Unspecified.GMB.GRACE-instrument.GRACE.UNSPECIFIED.1-4.greenland_gmb_mass_trends
* esacci.ICESHEETS.yr.Unspecified.GMB.GRACE-instrument.GRACE.UNSPECIFIED.1-5.greenland_gmb_mass_trends
* esacci.SEALEVEL.mon.IND.MSLTR.multi-sensor.multi-platform.MERGED.2-0.r1
* esacci.SEALEVEL.mon.IND.MSLTR.multi-sensor.multi-platform.MERGED.2-2.ASA
* esacci.SEALEVEL.mon.IND.MSLTR.multi-sensor.multi-platform.MERGED.2-2.BENGUELA
* esacci.SEALEVEL.mon.IND.MSLTR.multi-sensor.multi-platform.MERGED.2-2.CARIBBEAN
* esacci.SEALEVEL.mon.IND.MSLTR.multi-sensor.multi-platform.MERGED.2-2.GULFSTREAM
* esacci.SEALEVEL.mon.IND.MSLTR.multi-sensor.multi-platform.MERGED.2-2.HUMBOLDT
* esacci.SEALEVEL.mon.IND.MSLTR.multi-sensor.multi-platform.MERGED.2-2.MED_SEA
* esacci.SEALEVEL.mon.IND.MSLTR.multi-sensor.multi-platform.MERGED.2-2.NE_ATL
* esacci.SEALEVEL.mon.IND.MSLTR.multi-sensor.multi-platform.MERGED.2-2.N_INDIAN
* esacci.SEALEVEL.mon.IND.MSLTR.multi-sensor.multi-platform.MERGED.2-2.SE_AFRICA
* esacci.SEALEVEL.mon.IND.MSLTR.multi-sensor.multi-platform.MERGED.2-2.SE_ASIA
* esacci.SEALEVEL.mon.IND.MSLTR.multi-sensor.multi-platform.MERGED.2-2.S_AUSTRALIA
* esacci.SEALEVEL.mon.IND.MSLTR.multi-sensor.multi-platform.MERGED.2-2.WAFRICA
* esacci.SEALEVEL.mon.IND.MSLTR.multi-sensor.multi-platform.MERGED.2-2.r1
* In addition, the FIRE pixel datasets can be read. However, as they are
subdivided by regions, they do not appear in the toolbox as single datasets,
but as one dataset per region:
* esacci.FIRE.mon.L3S.BA.MODIS.Terra.MODIS_TERRA.v5-1.pixel~AREA_1
* esacci.FIRE.mon.L3S.BA.MODIS.Terra.MODIS_TERRA.v5-1.pixel~AREA_2
* esacci.FIRE.mon.L3S.BA.MODIS.Terra.MODIS_TERRA.v5-1.pixel~AREA_3
* esacci.FIRE.mon.L3S.BA.MODIS.Terra.MODIS_TERRA.v5-1.pixel~AREA_4
* esacci.FIRE.mon.L3S.BA.MODIS.Terra.MODIS_TERRA.v5-1.pixel~AREA_5
* esacci.FIRE.mon.L3S.BA.MODIS.Terra.MODIS_TERRA.v5-1.pixel~AREA_6
* esacci.FIRE.mon.L3S.BA.multi-sensor.multi-platform.SYN.v1-1.pixel~AREA_1
* esacci.FIRE.mon.L3S.BA.multi-sensor.multi-platform.SYN.v1-1.pixel~AREA_2
* esacci.FIRE.mon.L3S.BA.multi-sensor.multi-platform.SYN.v1-1.pixel~AREA_3
* esacci.FIRE.mon.L3S.BA.multi-sensor.multi-platform.SYN.v1-1.pixel~AREA_4
* esacci.FIRE.mon.L3S.BA.multi-sensor.multi-platform.SYN.v1-1.pixel~AREA_5
* esacci.FIRE.mon.L3S.BA.multi-sensor.multi-platform.SYN.v1-1.pixel~AREA_6
As for the Sentinel-2 FIRE pixel dataset
esacci.FIRE.mon.L3S.BA.MSI-(Sentinel-2).Sentinel-2A.MSI.v1-1.pixel, it is
split into one dataset per region, e.g.,
esacci.FIRE.mon.L3S.BA.MSI-(Sentinel-2).Sentinel-2A.MSI.v1-1.pixel~h45v23
As for esacci.FIRE.mon.L3S.BA.MSI-(Sentinel-2).Sentinel-2A.MSI.2-0.pixel,
it is additionally split per variable:
* esacci.FIRE.mon.L3S.BA.MSI-(Sentinel-2).Sentinel-2A.MSI.2-0.pixel~h32v14-fv2.0-CL
* esacci.FIRE.mon.L3S.BA.MSI-(Sentinel-2).Sentinel-2A.MSI.2-0.pixel~h32v14-fv2.0-JD
* esacci.FIRE.mon.L3S.BA.MSI-(Sentinel-2).Sentinel-2A.MSI.2-0.pixel~h32v14-fv2.0-LC

* Updated list of dataset states
* Fixed internal build process

* Added store aliases `esa-cci` and `esa-cci-zarr` and renamed default stores to have
the same names.

* Ensure default stores will always be included in store registry.

* Updated documentation

* Added opener `"datafame:geojson:esa-cdc"` to `esa-cci` data store.
The following datasets can now be opened:
* esacci.GHG.satellite-orbit-frequency.L2.CH4.SCIAMACHY.Envisat.IMAP.v7-2.r1
* esacci.GHG.satellite-orbit-frequency.L2.CH4.TANSO-FTS.GOSAT.EMMA.ch4_v1-2.r1
* esacci.GHG.satellite-orbit-frequency.L2.CH4.TANSO-FTS.GOSAT.OCFP.v2-1.r1
* esacci.GHG.satellite-orbit-frequency.L2.CH4.TANSO-FTS.GOSAT.OCPR.v7-0.r1
* esacci.GHG.satellite-orbit-frequency.L2.CH4.TANSO-FTS.GOSAT.SRFP.v2-3-8.r1
* esacci.GHG.satellite-orbit-frequency.L2.CO2.SCIAMACHY.Envisat.BESD.v02-01-02.r1
* esacci.GHG.satellite-orbit-frequency.L2.CO2.SCIAMACHY.Envisat.WFMD.v4-0.r1
* esacci.GHG.satellite-orbit-frequency.L2.CO2.TANSO-FTS.GOSAT.EMMA.v2-2c.r1
* esacci.GHG.satellite-orbit-frequency.L2.CO2.TANSO-FTS.GOSAT.SRFP.v2-3-8.r1
* esacci.SEAICE.satellite-orbit-frequency.L2P.SITHICK.RA-2.Envisat.NH.2-0.r1
* esacci.SEAICE.satellite-orbit-frequency.L2P.SITHICK.RA-2.Envisat.SH.2-0.r1
* esacci.SEAICE.satellite-orbit-frequency.L2P.SITHICK.SIRAL.CryoSat-2.NH.2-0.r1
* esacci.SEAICE.satellite-orbit-frequency.L2P.SITHICK.SIRAL.CryoSat-2.SH.2-0.r1
* esacci.SEALEVEL.satellite-orbit-frequency.L1.UNSPECIFIED.AltiKa.SARAL.UNSPECIFIED.v2-0.r1
* esacci.SEALEVEL.satellite-orbit-frequency.L1.UNSPECIFIED.GFO-RA.GFO.UNSPECIFIED.v2-0.r1
* esacci.SEALEVEL.satellite-orbit-frequency.L1.UNSPECIFIED.Poseidon-2.Jason-1.UNSPECIFIED.v2-0.r1
* esacci.SEALEVEL.satellite-orbit-frequency.L1.UNSPECIFIED.Poseidon-3.Jason-2.UNSPECIFIED.v2-0.r1
* esacci.SEALEVEL.satellite-orbit-frequency.L1.UNSPECIFIED.RA-2.Envisat.UNSPECIFIED.v2-0.r1
* esacci.SEALEVEL.satellite-orbit-frequency.L1.UNSPECIFIED.RA.ERS-1.UNSPECIFIED.v2-0.r1
* esacci.SEALEVEL.satellite-orbit-frequency.L1.UNSPECIFIED.RA.ERS-2.UNSPECIFIED.v2-0.r1
* esacci.SEALEVEL.satellite-orbit-frequency.L1.UNSPECIFIED.SIRAL.CryoSat-2.UNSPECIFIED.v2-0.r1
* esacci.SEALEVEL.satellite-orbit-frequency.L1.UNSPECIFIED.SSALT.Topex-Poseidon.UNSPECIFIED.v2-0.r1
Also added notebook that opens one of these datasets.

* Added new data store `esa-cci-kc`
(and corresponding xcube data store `esa-cci-kc`) that allows performant
accessing of selected datasets of the ESA Climate Data Centre using a
Zarr view of the original NetCDF files. This approach is made possible by
using the [kerchunk](https://fsspec.github.io/kerchunk/) package. Also
added new Notebook that demonstrates usage of the new data store.

* Added operations:
* `aggregate_statistics`:
Aggregates data frame columns into statistical measures
* `anomaly_external`: Calculates anomaly with external reference data
* `anomaly_internal`: Calculates anomaly using a dataset's mean
* `arithmetics`: Applies arithmetic operations
* `climatology`: Creates a 'mean over years' dataset
* `data_frame_max`: Selects a data frame's maximum record
* `data_frame_min`: Selects a data frame's minimum record
* `data_frame_subset`: Creates a variable or spatial subset of a dataframe
* `diff`: Calculates the difference of two datasets
* `find_closest`: Find data frame records closest to a given location
* `query`: Query records from a dataframe
* `reduce`: Reduces a dataset's variables
* `temporal_aggregation`: Aggregates a dataset