Monthly precipitation in mm at 1 km resolution based on SM2RAIN-ASCAT 2007-2018, IMERGE, CHELSA Climate and WorldClim
Monthly precipitation in mm at 1 km resolution based on SM2RAIN-ASCAT 2007-2018 (https://doi.org/10.5281/zenodo.2615278). Downscaled to 1 km resolution using gdalwarp (cubic splines) and combined with WorldClim (http://biogeo.ucdavis.edu/data/worldclim/v2.0/), CHELSA Climate (https://www.wsl.ch/lud/...
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Online Access: | https://dx.doi.org/10.5281/zenodo.1435912 https://zenodo.org/record/1435912 |
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ftdatacite:10.5281/zenodo.1435912 2023-05-15T13:57:31+02:00 Monthly precipitation in mm at 1 km resolution based on SM2RAIN-ASCAT 2007-2018, IMERGE, CHELSA Climate and WorldClim Hengl, Tomislav 2018 https://dx.doi.org/10.5281/zenodo.1435912 https://zenodo.org/record/1435912 en eng Zenodo https://dx.doi.org/10.5281/zenodo.1435913 https://dx.doi.org/10.5281/zenodo.1435935 https://dx.doi.org/10.5281/zenodo.2671754 https://dx.doi.org/10.5281/zenodo.2673444 https://dx.doi.org/10.5281/zenodo.3256275 Open Access Creative Commons Attribution Share Alike 4.0 International https://creativecommons.org/licenses/by-sa/4.0/legalcode cc-by-sa-4.0 info:eu-repo/semantics/openAccess CC-BY-SA precipitation global LandGIS dataset Dataset 2018 ftdatacite https://doi.org/10.5281/zenodo.1435912 https://doi.org/10.5281/zenodo.1435913 https://doi.org/10.5281/zenodo.1435935 https://doi.org/10.5281/zenodo.2671754 https://doi.org/10.5281/zenodo.2673444 https://doi.org/10.5281/zenodo.3256275 2021-11-05T12:55:41Z Monthly precipitation in mm at 1 km resolution based on SM2RAIN-ASCAT 2007-2018 (https://doi.org/10.5281/zenodo.2615278). Downscaled to 1 km resolution using gdalwarp (cubic splines) and combined with WorldClim (http://biogeo.ucdavis.edu/data/worldclim/v2.0/), CHELSA Climate (https://www.wsl.ch/lud/chelsa/data/climatologies/prec/) and IMERGE monthly (ftp://jsimpson.pps.eosdis.nasa.gov/NRTPUB/imerg/gis/ see files e.g. "3B-MO-L.GIS.IMERG.20180601.V05B.tif") products. Final values are estimated as a weighted average between the four precipitation data sources; 3x higher weight is given to the SM2RAIN-ASCAT data since it assumed to be the most accurate. Processing steps are available here . Antarctica is not included. 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, sm2rain.oct = determination method: SM2RAIN-ASCAT long-term average values for October, m = mean value, 1km = spatial resolution / block support: 1 km, s0..0cm = vertical reference: land surface, 2007..2018 = time reference: from 2007 to 2018, v0.2 = version number: 0.2, : {"references": ["Brocca, L., Filippucci, P., Hahn, S., Ciabatta, L., Massari, C., Camici, S., Sch\u00fcller, L., Bojkov, B., Wagner, W. (2019). SM2RAIN-ASCAT (2007-2018): global daily satellite rainfall from ASCAT soil moisture. submitted to Earth System Science Data.", "Karger, D. N., Conrad, O., B\u00f6hner, J., Kawohl, T., Kreft, H., Soria-Auza, R. W., ... & Kessler, M. (2017). Climatologies at high resolution for the earth's land surface areas. Scientific data, 4, 170122.", "Huffman, G. J., D. T. Bolvin, D. Braithwaite, K. Hsu, R. Joyce, and P. Xie, (2014). NASA Global Precipitation Measurement (GPM) Integrated Multi-satellitE Retrievals for GPM (IMERG), Algorithm Theoretical Basis Document (ATBD). https://storm- pps.gsfc.nasa.gov/storm/IMERG_ATBD_V4.pdf", "Fick, S. E., & Hijmans, R. J. (2017). WorldClim 2: new 1\u2010km spatial resolution climate surfaces for global land areas. International Journal of Climatology, 37(12), 4302-4315."]} Dataset Antarc* Antarctica DataCite Metadata Store (German National Library of Science and Technology) Huffman ENVELOPE(-72.259,-72.259,-75.313,-75.313) |
institution |
Open Polar |
collection |
DataCite Metadata Store (German National Library of Science and Technology) |
op_collection_id |
ftdatacite |
language |
English |
topic |
precipitation global LandGIS |
spellingShingle |
precipitation global LandGIS Hengl, Tomislav Monthly precipitation in mm at 1 km resolution based on SM2RAIN-ASCAT 2007-2018, IMERGE, CHELSA Climate and WorldClim |
topic_facet |
precipitation global LandGIS |
description |
Monthly precipitation in mm at 1 km resolution based on SM2RAIN-ASCAT 2007-2018 (https://doi.org/10.5281/zenodo.2615278). Downscaled to 1 km resolution using gdalwarp (cubic splines) and combined with WorldClim (http://biogeo.ucdavis.edu/data/worldclim/v2.0/), CHELSA Climate (https://www.wsl.ch/lud/chelsa/data/climatologies/prec/) and IMERGE monthly (ftp://jsimpson.pps.eosdis.nasa.gov/NRTPUB/imerg/gis/ see files e.g. "3B-MO-L.GIS.IMERG.20180601.V05B.tif") products. Final values are estimated as a weighted average between the four precipitation data sources; 3x higher weight is given to the SM2RAIN-ASCAT data since it assumed to be the most accurate. Processing steps are available here . Antarctica is not included. 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, sm2rain.oct = determination method: SM2RAIN-ASCAT long-term average values for October, m = mean value, 1km = spatial resolution / block support: 1 km, s0..0cm = vertical reference: land surface, 2007..2018 = time reference: from 2007 to 2018, v0.2 = version number: 0.2, : {"references": ["Brocca, L., Filippucci, P., Hahn, S., Ciabatta, L., Massari, C., Camici, S., Sch\u00fcller, L., Bojkov, B., Wagner, W. (2019). SM2RAIN-ASCAT (2007-2018): global daily satellite rainfall from ASCAT soil moisture. submitted to Earth System Science Data.", "Karger, D. N., Conrad, O., B\u00f6hner, J., Kawohl, T., Kreft, H., Soria-Auza, R. W., ... & Kessler, M. (2017). Climatologies at high resolution for the earth's land surface areas. Scientific data, 4, 170122.", "Huffman, G. J., D. T. Bolvin, D. Braithwaite, K. Hsu, R. Joyce, and P. Xie, (2014). NASA Global Precipitation Measurement (GPM) Integrated Multi-satellitE Retrievals for GPM (IMERG), Algorithm Theoretical Basis Document (ATBD). https://storm- pps.gsfc.nasa.gov/storm/IMERG_ATBD_V4.pdf", "Fick, S. E., & Hijmans, R. J. (2017). WorldClim 2: new 1\u2010km spatial resolution climate surfaces for global land areas. International Journal of Climatology, 37(12), 4302-4315."]} |
format |
Dataset |
author |
Hengl, Tomislav |
author_facet |
Hengl, Tomislav |
author_sort |
Hengl, Tomislav |
title |
Monthly precipitation in mm at 1 km resolution based on SM2RAIN-ASCAT 2007-2018, IMERGE, CHELSA Climate and WorldClim |
title_short |
Monthly precipitation in mm at 1 km resolution based on SM2RAIN-ASCAT 2007-2018, IMERGE, CHELSA Climate and WorldClim |
title_full |
Monthly precipitation in mm at 1 km resolution based on SM2RAIN-ASCAT 2007-2018, IMERGE, CHELSA Climate and WorldClim |
title_fullStr |
Monthly precipitation in mm at 1 km resolution based on SM2RAIN-ASCAT 2007-2018, IMERGE, CHELSA Climate and WorldClim |
title_full_unstemmed |
Monthly precipitation in mm at 1 km resolution based on SM2RAIN-ASCAT 2007-2018, IMERGE, CHELSA Climate and WorldClim |
title_sort |
monthly precipitation in mm at 1 km resolution based on sm2rain-ascat 2007-2018, imerge, chelsa climate and worldclim |
publisher |
Zenodo |
publishDate |
2018 |
url |
https://dx.doi.org/10.5281/zenodo.1435912 https://zenodo.org/record/1435912 |
long_lat |
ENVELOPE(-72.259,-72.259,-75.313,-75.313) |
geographic |
Huffman |
geographic_facet |
Huffman |
genre |
Antarc* Antarctica |
genre_facet |
Antarc* Antarctica |
op_relation |
https://dx.doi.org/10.5281/zenodo.1435913 https://dx.doi.org/10.5281/zenodo.1435935 https://dx.doi.org/10.5281/zenodo.2671754 https://dx.doi.org/10.5281/zenodo.2673444 https://dx.doi.org/10.5281/zenodo.3256275 |
op_rights |
Open Access Creative Commons Attribution Share Alike 4.0 International https://creativecommons.org/licenses/by-sa/4.0/legalcode cc-by-sa-4.0 info:eu-repo/semantics/openAccess |
op_rightsnorm |
CC-BY-SA |
op_doi |
https://doi.org/10.5281/zenodo.1435912 https://doi.org/10.5281/zenodo.1435913 https://doi.org/10.5281/zenodo.1435935 https://doi.org/10.5281/zenodo.2671754 https://doi.org/10.5281/zenodo.2673444 https://doi.org/10.5281/zenodo.3256275 |
_version_ |
1766265194514743296 |