Introduction
The Copernicus European Regional ReAnalysis Land (CERRA-Land) dataset provides spatially and temporally consistent historical reconstructions of climate, Earth surface and soil variables. This post describes how to access CERRA-Land data.
Prerequisite
You must have a python environment with the package cdsapi installed and you must have a Copernicus user. See the Copernicus page on How to use the CDS API.
CERRA-Land
The CERRA system is a comparatively high resolution (5.5 km) dataset of climate history forced by the global ERA5 reanalysis and refined using both in-situ observations and satellite information. CERRA-Land is an open dataset available for download under the European Copernicus program (Copernicus Climate Change Service). For details see the page Copernicus regional reanalysis for Europe (CERRA).
CERRA-Land contains more than 30 thematic layers of climate, Earth surface conditions and soil variables, with several of the latter at different depths.
Access CERRA data
CERRA datasets are accessible via Copernicus Climate Data Store (CDS). To get directly to the search page click HERE. The data that we are using for this project is the CERRA-Land sub-daily regional reanalysis data for Europe from 1984 to present. The CERRA-Land datasets were developed to allow addressing hydrological modelling, water resource management issues and to carry out climate change impact studies.
CERRA-Land sub-daily regional reanalysis data for Europe from 1984 to present
The following table is a summary of the available data for CERRA-Land.
| Variable | Unit | Description |
| Albedo | % | Reflectance of downward solar radiation |
| Evaporation | kg m^-2 | The amount of evaporated water from the Earth surface |
| Snow cover | fraction | The fraction of the surface covered by snow |
| Lake bottom temperature | K | Temperature of water at the bottom of lakes |
| Lake depth | m | Depth of lakes |
| Lake ice depth | m | Thickness of ice layer on lakes |
| Lake ice temperature | K | Skin temperature of ice on lakes |
| Lake mix-layer depth | m | Thickness of upper water layer in lakes |
| Lake mix-layer temperature | K | Temperature of upper water layer in lakes |
| Lake shape factor | dimensionless | Temperature changes with depth in lakes |
| Lake total layer temperature | K | Lake total water column mean temperature |
| Land-sea mask | dimensionless | Proportion of land/sea in each cell |
| Liquid volumetric soil moisture | m^3 m^-3 | Liquid water fraction at 14 soil depths |
| Orography | m | Elevation above sea level |
| Percolation | kg m^-2 | Water drained out of upper soil layers |
| Skin temperature | K | Temperature at the Earth’s surface |
| Snow albedo | % | Reflectance of downward solar radiation from snow |
| Snow density | kg m^-3 | Snow thickness on the ground |
| Snow depth water equivalent | kg m^-2 | The mass of liquid water of the snow column |
| Snow melt | kg m^-2 | Melting of snow |
| Soil heat flux | W m^-2 | energy received by the soil converted to heat |
| Soil temperature | K | Temperature at 14 soil depths |
| Surface latent heat flux | J m^-2 | energy received by the soil converted to evaporation |
| Surface net solar radiation | J m^-2 | accumulated solar short-wave radiation that is absorbed at the surface |
| Surface net thermal radiation | J m^-2 | Difference between incoming and outgoing thermal radiation at the surface |
| Surface roughness | m | aerodynamic roughness length |
| Surface runoff | kg m^-2 | Excess water at full soil saturation |
| Surface sensible heat flux | J m^-2 | Energy emitted from the surface as heat |
| Surface solar radiation downwards | J m^-2 | Total solar short-wave radiation at the surface |
| Surface thermal radiation downwards | J m^-2 | Total thermal radiation at the surface |
| Temperature of snow layer | K | Mean temperature of 12 snow layers |
| Total precipitation | kg m^-2 | Total daily precipitation |
| Volumetric soil moisture | m^3 m^-3 | Liquid + frozen water fraction at 14 soil depths |
| Volumetric transpiration stress-onset | m^3 m^-3 | Soil water content after gravitational drainage at 14 depths |
| Volumetric wilting point | m^3 m^-3 | Plant inaccessible soil water content at 14 depths |
Download dataset
From the CERRA-Land sub-daily regional reanalysis data for Europe from 1984 to present, select the tab , as illustrated to the right.
Select datasets to download
Select the Variable you want to retrieve; Total precipitation in the example below.
The variable Total precipitation only has one Level type, Surface, that should be selected.
The options for Soil layer are all faded out as there is no such option for Total precipitation.
As we are retrieving historical data, select Analysis from the Product type options.
Set the Year, Month and Day to retrieve.
You also have to set Time, which for Total precipitation is 06:00; while Leadtime hour is not applicable and thus have no options.
Available Format options for downloading are GRIB2 and NetCDF (experimental). In the example below GRIB2 is selected.
Accept the Terms of use if you agree to them.
API
With all the required fields selected, the button should turn green. Click on it to see the API python code:
import cdsapi
c = cdsapi.Client()
c.retrieve(
'reanalysis-cerra-land',
{
'format': 'grib',
'variable': 'total_precipitation',
'level_type': 'surface',
'product_type': 'analysis',
'year': '2020',
'month': '01',
'day': [
'01', '02', '03',
'04', '05', '06',
'07', '08', '09',
'10', '11', '12',
'13', '14', '15',
'16', '17', '18',
'19', '20', '21',
'22', '23', '24',
'25', '26', '27',
'28', '29', '30',
'31',
],
'time': '06:00',
},
'download.grib')
If you are using Karttur’s GeoImagine Framework, with the package cdsapi installed, you can run the script above from within the Framework. The instructions for how to setup a non-Framework embedded retrieval using cdsapi, see the Copernicus page on How to use the CDS API.