Stomatal and in-canopy resistances (assmililated data)

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Data type
Horizontal coverage
Europe (west=25.0° W, east=45.0° E, south=30.0° N, north=70.0° N)
Horizontal resolution
0.1° x 0.1°
Temporal resolution
Temporal coverage
SURFEX land surface model
File format

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Stomatal resistance (spatially averaged)
In-canopy resistance (spatially averaged)


Dry deposition of gases to the land surface is an important sink for reactive trace gases in the troposphere. Understanding dry deposition is of importance for understanding air quality and its impacts on human health and vegetation. SURFEX calculates dry deposition using a software scheme that was recently developed in the SEEDS project (deliverable D3.4). The dry deposition software scheme calculates dry deposition velocities, which can be used as an input to calculate dry deposition fluxes in an air quality model. The dry deposition velocities are provided for ozone, sulphur dioxide, and reactive nitrogen compounds (NOx, ammonia, nitric acid, organic nitrates, and per-nitric acid). In addition to the dry deposition velocities, SURFEX calculates various diagnostics to help understand the deposition of pollutants into the vegetation leaf canopy (in-canopy resistance) and into their stomata (stomatal resistance). All of the dry deposition data are output on an hourly time resolution.

Download instructions


This sample Python code shows how to download this dataset, create subsets of it and save them as NetCDF, using the Xarray library.

import xarray as xr import fsspec # Open remote dataset ds = xr.open_zarr( store=fsspec.get_mapper("") ) # Subset a time range, save as NetCDF time_subset = ds.r_stom_isba.sel(time=slice('2019-06-01', '2019-07-01')) time_subset.to_netcdf('./') # Subset a time and geographical range, save as NetCDF time_geo_subset = ds.r_stom_isba.sel(time=slice('2019-06-01', '2019-07-01'), latitude=slice(40, 43), longitude=slice(0,3.5)) time_geo_subset.to_netcdf('./')