Rainfall Estimates on a Gridded Network (REGEN) based on long-term station data V1.0
A global land-based gridded dataset of daily precipitation at 1 degree X 1 degree resolution from 1950 to 2013. Two datasets are available under the REGEN moniker. This dataset interpolates only the long-term precipitation stations (stations with at least 40 complete years of data). A second related...
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ftzenodo:oai:zenodo.org:4922150 2024-09-15T17:48:26+00:00 Rainfall Estimates on a Gridded Network (REGEN) based on long-term station data V1.0 Contractor, Steefan 2018-12-10 https://doi.org/10.25914/5b9fa67fce5d6 https://geonetwork.nci.org.au/geonetwork/srv/eng/catalog.search#/metadata/f4100_1361_8979_9332 https://researchdata.ands.org.au/rainfall-estimates-gridded-station-v10/1340690 eng eng Zenodo https://doi.org/10.5194/hess-2018-595 https://zenodo.org/communities/arc-coe-clex-data https://doi.org/10.25914/5b9fa67fce5d6 oai:zenodo.org:4922150 https://geonetwork.nci.org.au/geonetwork/srv/eng/catalog.search#/metadata/f4100_1361_8979_9332 https://researchdata.ands.org.au/rainfall-estimates-gridded-station-v10/1340690 info:eu-repo/semantics/openAccess Creative Commons Attribution Non Commercial Share Alike 4.0 International https://creativecommons.org/licenses/by-nc-sa/4.0/legalcode Precipitation Observations info:eu-repo/semantics/other 2018 ftzenodo https://doi.org/10.25914/5b9fa67fce5d610.5194/hess-2018-595 2024-07-27T01:59:04Z A global land-based gridded dataset of daily precipitation at 1 degree X 1 degree resolution from 1950 to 2013. Two datasets are available under the REGEN moniker. This dataset interpolates only the long-term precipitation stations (stations with at least 40 complete years of data). A second related dataset interpolates all stations available regardless of completeness of station timeseries. Besides the grid cell average precipitation amount per day (mm/day), the Yamamoto standard deviation per grid cell (mm/day), the kriging error per grid cell (%) and number of stations per grid cell variables are also included. Currently, there are two major data archives of global in situ daily rainfall data: 1. The Global Historical Station Network (GHCN-Daily) hosted by National Oceanic and Atmospheric Administration (NOAA) and 2. The Deutscher Wetterdienst (DWD) Global Precipitation Climatology Centre (GPCC). These two data archives are combined along with additional station data acquired from other researchers. The merged archive is quality controlled and the flagged stations are removed to create a long term high quality archive of raw station data. This dataset uses ordinary block kriging to interpolate a long-term station subset of this high quality merged archive. The REGEN all station based dataset instead interpolates all stations in this high quality merged archive. The output consists of a separate CF-compliant netcdf file for each year, each containing the four aforementioned variables. These values are available for global land areas with the exception of Antarctica. The time dimension of the netcdf ranges from 1950-01-01 to 2013-12-31. Each dataset (All station based and long-term station based) is in classic netcdf format and occupies around 350MB of disk space for each year with the combined total of all years being around 26GB. Besides these two netcdfs, two additional netcdfs containing a mask indicating the high data quality grid cells of each dataset (all station and long-term) are also available. These ... Other/Unknown Material Antarc* Antarctica Zenodo |
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English |
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Precipitation Observations |
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Precipitation Observations Contractor, Steefan Rainfall Estimates on a Gridded Network (REGEN) based on long-term station data V1.0 |
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Precipitation Observations |
description |
A global land-based gridded dataset of daily precipitation at 1 degree X 1 degree resolution from 1950 to 2013. Two datasets are available under the REGEN moniker. This dataset interpolates only the long-term precipitation stations (stations with at least 40 complete years of data). A second related dataset interpolates all stations available regardless of completeness of station timeseries. Besides the grid cell average precipitation amount per day (mm/day), the Yamamoto standard deviation per grid cell (mm/day), the kriging error per grid cell (%) and number of stations per grid cell variables are also included. Currently, there are two major data archives of global in situ daily rainfall data: 1. The Global Historical Station Network (GHCN-Daily) hosted by National Oceanic and Atmospheric Administration (NOAA) and 2. The Deutscher Wetterdienst (DWD) Global Precipitation Climatology Centre (GPCC). These two data archives are combined along with additional station data acquired from other researchers. The merged archive is quality controlled and the flagged stations are removed to create a long term high quality archive of raw station data. This dataset uses ordinary block kriging to interpolate a long-term station subset of this high quality merged archive. The REGEN all station based dataset instead interpolates all stations in this high quality merged archive. The output consists of a separate CF-compliant netcdf file for each year, each containing the four aforementioned variables. These values are available for global land areas with the exception of Antarctica. The time dimension of the netcdf ranges from 1950-01-01 to 2013-12-31. Each dataset (All station based and long-term station based) is in classic netcdf format and occupies around 350MB of disk space for each year with the combined total of all years being around 26GB. Besides these two netcdfs, two additional netcdfs containing a mask indicating the high data quality grid cells of each dataset (all station and long-term) are also available. These ... |
format |
Other/Unknown Material |
author |
Contractor, Steefan |
author_facet |
Contractor, Steefan |
author_sort |
Contractor, Steefan |
title |
Rainfall Estimates on a Gridded Network (REGEN) based on long-term station data V1.0 |
title_short |
Rainfall Estimates on a Gridded Network (REGEN) based on long-term station data V1.0 |
title_full |
Rainfall Estimates on a Gridded Network (REGEN) based on long-term station data V1.0 |
title_fullStr |
Rainfall Estimates on a Gridded Network (REGEN) based on long-term station data V1.0 |
title_full_unstemmed |
Rainfall Estimates on a Gridded Network (REGEN) based on long-term station data V1.0 |
title_sort |
rainfall estimates on a gridded network (regen) based on long-term station data v1.0 |
publisher |
Zenodo |
publishDate |
2018 |
url |
https://doi.org/10.25914/5b9fa67fce5d6 https://geonetwork.nci.org.au/geonetwork/srv/eng/catalog.search#/metadata/f4100_1361_8979_9332 https://researchdata.ands.org.au/rainfall-estimates-gridded-station-v10/1340690 |
genre |
Antarc* Antarctica |
genre_facet |
Antarc* Antarctica |
op_relation |
https://doi.org/10.5194/hess-2018-595 https://zenodo.org/communities/arc-coe-clex-data https://doi.org/10.25914/5b9fa67fce5d6 oai:zenodo.org:4922150 https://geonetwork.nci.org.au/geonetwork/srv/eng/catalog.search#/metadata/f4100_1361_8979_9332 https://researchdata.ands.org.au/rainfall-estimates-gridded-station-v10/1340690 |
op_rights |
info:eu-repo/semantics/openAccess Creative Commons Attribution Non Commercial Share Alike 4.0 International https://creativecommons.org/licenses/by-nc-sa/4.0/legalcode |
op_doi |
https://doi.org/10.25914/5b9fa67fce5d610.5194/hess-2018-595 |
_version_ |
1810289650507448320 |