CHELSA_v1.1 (http://chelsa-climate.org/) is a high resolution (30 arc sec, ~1 km) climate data set for the earth land surface areas. It includes monthly and annual mean temperature and precipitation patterns as well as derived bioclimatic and interannual parameters for the time period 1979-2013. CHELSA_v1.1 is based on a quasi-mechanistical statistical downscaling of the ERA interim global circulation model (http://www.ecmwf.int/en/research/climate-reanalysis/era-interim) with a GPCC (https://www.dwd.de/EN/ourservices/gpcc/gpcc.html) and GHCN (https://www.ncdc.noaa.gov/ghcnm/) bias correction.
CHELSA_v1.0 (http://chelsa-climate.org/) is a high resolution (30 arc sec, ~1 km) climate data set for the earth land surface areas. Version 1.0 is a first release. It includes monthly and annual mean temperature and precipitation patterns for the time period 1979-2013. CHELSA_v1 is based on a quasi-mechanistical statistical downscaling of the ERA interim global circulation model (http://www.ecmwf.int/en/research/climate-reanalysis/era-interim) with a GPCC (https://www.dwd.de/EN/ourservices/gpcc/gpcc.html) and GHCN (https://www.ncdc.noaa.gov/ghcnm/) bias correction. Specifications: High resolution (30 arcsec, ~1 km) Precipitation & Temperature Monthly coverage 1979 - 2013 Incorporation of topoclimate (e.g. orographic rainfall & wind fields). Downscaled ERA-interim model. Allows calculation of derived parameters based on monthly values such as length of dry periods etc.
The HEXC98 TTAAii Data Designators decode as: T1 (H): Grid point information (GRIB) T1T2 (HE): Precipitation A1 (X): Global Area (area not definable) A2 (C): 12 hours forecast T1ii (H98): Air priorities for the Earth's surface (Remarks from Volume-C: H+ 12 (GLOBAL MODEL) ACCUMULATED PRECIPITATION)
The HEXM98 TTAAii Data Designators decode as: T1 (H): Grid point information (GRIB) T1T2 (HE): Precipitation A1 (X): Global Area (area not definable) A2 (M): 96 hours forecast T1ii (H98): Air priorities for the Earth's surface (Remarks from Volume-C: H+ 96 (GLOBAL MODEL) ACCUMULATED PRECIPITATION)
The HEXO98 TTAAii Data Designators decode as: T1 (H): Grid point information (GRIB) T1T2 (HE): Precipitation A1 (X): Global Area (area not definable) A2 (O): 120 hours forecast (5 days) T1ii (H98): Air priorities for the Earth's surface (Remarks from Volume-C: H+ 120 (GLOBAL MODEL) ACCUMULATED PRECIPITATION)
The HEXJ98 TTAAii Data Designators decode as: T1 (H): Grid point information (GRIB) T1T2 (HE): Precipitation A1 (X): Global Area (area not definable) A2 (J): 60 hours forecast T1ii (H98): Air priorities for the Earth's surface (Remarks from Volume-C: H+ 60 (GLOBAL MODEL) ACCUMULATED PRECIPITATION)
The HEXP98 TTAAii Data Designators decode as: T1 (H): Grid point information (GRIB) T1T2 (HE): Precipitation A1 (X): Global Area (area not definable) A2 (P): 132 hours forecast T1ii (H98): Air priorities for the Earth's surface (Remarks from Volume-C: H+ 132 (GLOBAL MODEL) ACCUMULATED PRECIPITATION)
The HEXI98 TTAAii Data Designators decode as: T1 (H): Grid point information (GRIB) T1T2 (HE): Precipitation A1 (X): Global Area (area not definable) A2 (I): 48 hours forecast T1ii (H98): Air priorities for the Earth's surface (Remarks from Volume-C: H+ 48 (GLOBAL MODEL) ACCUMULATED PRECIPITATION)
The HEXK98 TTAAii Data Designators decode as: T1 (H): Grid point information (GRIB) T1T2 (HE): Precipitation A1 (X): Global Area (area not definable) A2 (K): 72 hours forecast T1ii (H98): Air priorities for the Earth's surface (Remarks from Volume-C: H+ 72 (GLOBAL MODEL) ACCUMULATED PRECIPITATION)
ERA5-Land total precipitation monthly time series for Mauritania at 30 arc seconds (ca. 1000 meter) resolution (2019 - 2023) Source data: ERA5-Land is a reanalysis dataset providing a consistent view of the evolution of land variables over several decades at an enhanced resolution compared to ERA5. ERA5-Land has been produced by replaying the land component of the ECMWF ERA5 climate reanalysis. Reanalysis combines model data with observations from across the world into a globally complete and consistent dataset using the laws of physics. Reanalysis produces data that goes several decades back in time, providing an accurate description of the climate of the past. Total precipitation: Accumulated liquid and frozen water, including rain and snow, that falls to the Earth's surface. It is the sum of large-scale precipitation (that precipitation which is generated by large-scale weather patterns, such as troughs and cold fronts) and convective precipitation (generated by convection which occurs when air at lower levels in the atmosphere is warmer and less dense than the air above, so it rises). Precipitation variables do not include fog, dew or the precipitation that evaporates in the atmosphere before it lands at the surface of the Earth. This variable is accumulated from the beginning of the forecast time to the end of the forecast step. The units of precipitation are depth in metres. It is the depth the water would have if it were spread evenly over the grid box. Care should be taken when comparing model variables with observations, because observations are often local to a particular point in space and time, rather than representing averages over a model grid box and model time step. Processing steps: The original hourly ERA5-Land data has been spatially enhanced from 0.1 degree to 30 arc seconds (approx. 1000 m) spatial resolution by image fusion with CHELSA data (V1.2) (https://chelsa-climate.org/). For each day we used the corresponding monthly long-term average of CHELSA. The aim was to use the fine spatial detail of CHELSA and at the same time preserve the general regional pattern and fine temporal detail of ERA5-Land. The steps included aggregation and enhancement, specifically: 1. spatially aggregate CHELSA to the resolution of ERA5-Land 2. calculate proportion of ERA5-Land / aggregated CHELSA 3. interpolate proportion with a Gaussian filter to 30 arc seconds 4. multiply the interpolated proportions with CHELSA Using proportions ensures that areas without precipitation remain areas without precipitation. Only if there was actual precipitation in a given area, precipitation was redistributed according to the spatial detail of CHELSA. The spatially enhanced daily ERA5-Land data has been aggregated to monthly resolution, by calculating the sum of the precipitation per pixel over each month. File naming: ERA5_land_monthly_prectot_sum_30sec_YYYY_MM_01T00_00_00_int.tif e.g.:ERA5_land_monthly_prectot_sum_30sec_2023_12_01T00_00_00_int.tif The date within the filename is year and month of aggregated timestamp. Pixel values: mm * 10 Scaled to Integer, example: value 218 = 21.8 mm Projection + EPSG code: Latitude-Longitude/WGS84 (EPSG: 4326) Spatial extent: north: 28:18N south: 14:42N west: 17:05W east: 4:49W Temporal extent: January 2019 - December 2023 Spatial resolution: 30 arc seconds (approx. 1000 m) Temporal resolution: monthly Lineage: Dataset has been processed from original Copernicus Climate Data Store (ERA5-Land) data sources. As auxiliary data CHELSA climate data has been used. Software used: GRASS GIS 8.3.2 Format: GeoTIFF Original ERA5-Land dataset license: https://cds.climate.copernicus.eu/api/v2/terms/static/licence-to-use-copernicus-products.pdf CHELSA climatologies (V1.2): Data used: Karger D.N., Conrad, O., Böhner, J., Kawohl, T., Kreft, H., Soria-Auza, R.W., Zimmermann, N.E, Linder, H.P., Kessler, M. (2018): Data from: Climatologies at high resolution for the earth's land surface areas. Dryad digital repository. http://dx.doi.org/doi:10.5061/dryad.kd1d4 Original peer-reviewed publication: Karger, D.N., Conrad, O., Böhner, J., Kawohl, T., Kreft, H., Soria-Auza, R.W., Zimmermann, N.E., Linder, P., Kessler, M. (2017): Climatologies at high resolution for the Earth land surface areas. Scientific Data. 4 170122. https://doi.org/10.1038/sdata.2017.122 Representation type: Grid Processed by: mundialis GmbH & Co. KG, Germany (https://www.mundialis.de/) Contact: mundialis GmbH & Co. KG, info@mundialis.de Acknowledgements: This study was partially funded by EU grant 874850 MOOD. The contents of this publication are the sole responsibility of the authors and don't necessarily reflect the views of the European Commission.