Monthly precipitation in mm at 1 km resolution (multisource average) based on SM2RAIN-ASCAT 2007-2021, CHELSA Climate and WorldClim
Monthly precipitation in mm at 1 km resolution based on SM2RAIN-ASCAT 2007-2021 (https://doi.org/10.5281/zenodo.2615278). Downscaled to 1 km resolution using gdalwarp (cubic splines) and combined with WorldClim (https://worldclim.org/data/worldclim21.html) and CHELSA Climate (https://chelsa-climate....
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ftzenodo:oai:zenodo.org:6458580 2023-05-15T13:51:48+02:00 Monthly precipitation in mm at 1 km resolution (multisource average) based on SM2RAIN-ASCAT 2007-2021, CHELSA Climate and WorldClim Hengl, T. Parente, L. 2022-04-13 https://zenodo.org/record/6458580 https://doi.org/10.5281/zenodo.6458580 eng eng info:eu-repo/grantAgreement/EC/H2020/874850/ doi:10.5281/zenodo.2615278 doi:10.5281/zenodo.1420114 doi:10.5281/zenodo.1435912 https://zenodo.org/record/6458580 https://doi.org/10.5281/zenodo.6458580 oai:zenodo.org:6458580 info:eu-repo/semantics/openAccess https://creativecommons.org/licenses/by-sa/4.0/legalcode precipitation global OpenLandMap info:eu-repo/semantics/other dataset 2022 ftzenodo https://doi.org/10.5281/zenodo.645858010.5281/zenodo.261527810.5281/zenodo.142011410.5281/zenodo.1435912 2023-03-11T04:16:22Z Monthly precipitation in mm at 1 km resolution based on SM2RAIN-ASCAT 2007-2021 (https://doi.org/10.5281/zenodo.2615278). Downscaled to 1 km resolution using gdalwarp (cubic splines) and combined with WorldClim (https://worldclim.org/data/worldclim21.html) and CHELSA Climate (https://chelsa-climate.org/downloads/) monthly values. Final values are estimated as a simple average between the three precipitation data sources; a more objective approach would be to use training points e.g. meteo-station monthly values, then train an ensemble model using the 3 data sources as independent variables. Another global data source of precipitation images is the monthly IMERGE dataset, however this requires transformation and is available only for limited span of years. Processing steps are available here. Antarctica is not included. Standard deviation (sd) indicates a difference between the 3 data sources. To access and visualize maps use: https://openlandmap.org. If you discover a bug, artifact or inconsistency in the maps, or if you have a question please use some of the following channels: Technical issues and questions about the code: https://gitlab.com/openlandmap/global-layers/issues General questions and comments: https://disqus.com/home/forums/landgis/ All files internally compressed using "COMPRESS=DEFLATE" creation option in GDAL. File naming convention: clm = theme: climate, precipitation = variable: precipitation, wc.v2.1.chelsa.v2.1.sm2rain.oct = determination method: long-term average values for October, m = mean value, 1km = spatial resolution / block support: 1 km, s0.0cm = vertical reference: land surface, 1980.2020 = time reference: from 1980 to 2020, v0.3 = version number: 0.3 Dataset Antarc* Antarctica Zenodo |
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Open Polar |
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language |
English |
topic |
precipitation global OpenLandMap |
spellingShingle |
precipitation global OpenLandMap Hengl, T. Parente, L. Monthly precipitation in mm at 1 km resolution (multisource average) based on SM2RAIN-ASCAT 2007-2021, CHELSA Climate and WorldClim |
topic_facet |
precipitation global OpenLandMap |
description |
Monthly precipitation in mm at 1 km resolution based on SM2RAIN-ASCAT 2007-2021 (https://doi.org/10.5281/zenodo.2615278). Downscaled to 1 km resolution using gdalwarp (cubic splines) and combined with WorldClim (https://worldclim.org/data/worldclim21.html) and CHELSA Climate (https://chelsa-climate.org/downloads/) monthly values. Final values are estimated as a simple average between the three precipitation data sources; a more objective approach would be to use training points e.g. meteo-station monthly values, then train an ensemble model using the 3 data sources as independent variables. Another global data source of precipitation images is the monthly IMERGE dataset, however this requires transformation and is available only for limited span of years. Processing steps are available here. Antarctica is not included. Standard deviation (sd) indicates a difference between the 3 data sources. To access and visualize maps use: https://openlandmap.org. If you discover a bug, artifact or inconsistency in the maps, or if you have a question please use some of the following channels: Technical issues and questions about the code: https://gitlab.com/openlandmap/global-layers/issues General questions and comments: https://disqus.com/home/forums/landgis/ All files internally compressed using "COMPRESS=DEFLATE" creation option in GDAL. File naming convention: clm = theme: climate, precipitation = variable: precipitation, wc.v2.1.chelsa.v2.1.sm2rain.oct = determination method: long-term average values for October, m = mean value, 1km = spatial resolution / block support: 1 km, s0.0cm = vertical reference: land surface, 1980.2020 = time reference: from 1980 to 2020, v0.3 = version number: 0.3 |
format |
Dataset |
author |
Hengl, T. Parente, L. |
author_facet |
Hengl, T. Parente, L. |
author_sort |
Hengl, T. |
title |
Monthly precipitation in mm at 1 km resolution (multisource average) based on SM2RAIN-ASCAT 2007-2021, CHELSA Climate and WorldClim |
title_short |
Monthly precipitation in mm at 1 km resolution (multisource average) based on SM2RAIN-ASCAT 2007-2021, CHELSA Climate and WorldClim |
title_full |
Monthly precipitation in mm at 1 km resolution (multisource average) based on SM2RAIN-ASCAT 2007-2021, CHELSA Climate and WorldClim |
title_fullStr |
Monthly precipitation in mm at 1 km resolution (multisource average) based on SM2RAIN-ASCAT 2007-2021, CHELSA Climate and WorldClim |
title_full_unstemmed |
Monthly precipitation in mm at 1 km resolution (multisource average) based on SM2RAIN-ASCAT 2007-2021, CHELSA Climate and WorldClim |
title_sort |
monthly precipitation in mm at 1 km resolution (multisource average) based on sm2rain-ascat 2007-2021, chelsa climate and worldclim |
publishDate |
2022 |
url |
https://zenodo.org/record/6458580 https://doi.org/10.5281/zenodo.6458580 |
genre |
Antarc* Antarctica |
genre_facet |
Antarc* Antarctica |
op_relation |
info:eu-repo/grantAgreement/EC/H2020/874850/ doi:10.5281/zenodo.2615278 doi:10.5281/zenodo.1420114 doi:10.5281/zenodo.1435912 https://zenodo.org/record/6458580 https://doi.org/10.5281/zenodo.6458580 oai:zenodo.org:6458580 |
op_rights |
info:eu-repo/semantics/openAccess https://creativecommons.org/licenses/by-sa/4.0/legalcode |
op_doi |
https://doi.org/10.5281/zenodo.645858010.5281/zenodo.261527810.5281/zenodo.142011410.5281/zenodo.1435912 |
_version_ |
1766255838190632960 |