ERA5-Land monthly: Total precipitation, monthly time series for Mauritania at 30 arc seconds (ca. 1000 meter) resolution (2019 - 2023)

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.

Simple

Date ( Publication )
2024-06-21
Identifier
10.5281/zenodo.12189668
Status
On going
Point of contact
mundialis GmbH & Co. KG - ( )

Maintenance and update frequency
As needed
Keywords ( Theme )
  • MOOD-H2020
  • Precipitation
  • Rift Valley fever
  • RVF
Keywords ( Place )
  • Mauritania
GEMET - INSPIRE themes, version 1.0 ( Theme )
  • Human health and safety
Use limitation
Licence to Use Copernicus Products
Access constraints
Other restrictions
Use constraints
Intellectual property rights
Other constraints
no limitations to public access
Other constraints
Licence to Use Copernicus Products (Version 1.2, Nov. 2019): "All users of Copernicus Products must provide clear and visible attribution to the Copernicus programme. The Licensee will communicate to the public the source of the Copernicus Products by crediting the Copernicus Climate Change and Atmosphere Monitoring Services" (full licence available here: https://cds.climate.copernicus.eu/api/v2/terms/static/licence-to-use-copernicus-products.pdf
Other constraints
{ "id": "other-open", "name": "Licence to Use Copernicus Products", "url": "https://ads.atmosphere.copernicus.eu/api/v2/terms/static/licence-to-use-copernicus-products.pdf", "quelle": "Source: Copernicus Programme" }
Spatial representation type
Grid
Distance
30 arc-seconds
Metadata language
en
Character set
UTF8
Topic category
  • Geoscientific information
  • Health
Description
Mauritania
Begin date
2019-01-01
End date
2023-12-31
N
S
E
W
thumbnail


Reference system identifier
EPSG / WGS 84 (EPSG:4326) / 8.6
Distribution format
  • GeoTIFF ( )

OnLine resource
ERA5-Land total precipitation 2019 ( WWW:DOWNLOAD-1.0-http--download )

ERA5-Land total precipitation 2019

OnLine resource
ERA5-Land total precipitation 2020 ( WWW:DOWNLOAD-1.0-http--download )

ERA5-Land total precipitation 2020

OnLine resource
ERA5-Land total precipitation 2021 ( WWW:DOWNLOAD-1.0-http--download )

ERA5-Land total precipitation 2021

OnLine resource
ERA5-Land total precipitation 2022 ( WWW:DOWNLOAD-1.0-http--download )

ERA5-Land total precipitation 2022

OnLine resource
ERA5-Land total precipitation 2023 ( WWW:DOWNLOAD-1.0-http--download )

ERA5-Land total precipitation 2023

Hierarchy level
Dataset

Conformance result

Date ( Publication )
2010-12-08
Other citation details
http://data.europa.eu/eli/reg/2010/1089/2014-12-31
Explanation
See specified reference
Pass
Yes
Statement
Dataset has been processed from original Copernicus Climate Data Store (ERA5-Land) data sources. As auxiliary data CHELSA climate data has been used.

gmd:MD_Metadata

File identifier
6e9f4ea1-7111-4505-8165-a5857e486584 XML
Metadata language
en
Character set
UTF8
Hierarchy level
Dataset
Date stamp
2024-07-02T15:36:26
Metadata standard name
ISO 19115:2003/19139
Metadata standard version
1.0
Point of contact
mundialis GmbH & Co. KG - ( )

Citation proposal


(2024) . ERA5-Land monthly: Total precipitation, monthly time series for Mauritania at 30 arc seconds (ca. 1000 meter) resolution (2019 - 2023).
https://data.opendatascience.eu/geonetwork/srv/api/records/6e9f4ea1-7111-4505-8165-a5857e486584

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