MSWEP: 3-hourly 0.25° global gridded precipitation (1979–2015) by merging gauge, satellite, and reanalysis data
Current global precipitation (P) datasets do not take full advantage of the complementary nature of satellite and reanalysis data. Here, we present Multi-Source Weighted-Ensemble Precipitation (MSWEP) version 1.1, a global P dataset for the period 1979–2015 with a 3-hourly temporal and 0.25° spatial...
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ftnonlinearchiv:oai:noa.gwlb.de:cop_mods_00010478 2023-05-15T13:34:49+02:00 MSWEP: 3-hourly 0.25° global gridded precipitation (1979–2015) by merging gauge, satellite, and reanalysis data Beck, Hylke E. van Dijk, Albert I. J. M. Levizzani, Vincenzo Schellekens, Jaap Miralles, Diego G. Martens, Brecht de Roo, Ad 2017-01 electronic https://doi.org/10.5194/hess-21-589-2017 https://noa.gwlb.de/receive/cop_mods_00010478 https://noa.gwlb.de/servlets/MCRFileNodeServlet/cop_derivate_00010435/hess-21-589-2017.pdf https://hess.copernicus.org/articles/21/589/2017/hess-21-589-2017.pdf eng eng Copernicus Publications Hydrology and Earth System Sciences -- http://www.bibliothek.uni-regensburg.de/ezeit/?2100610 -- http://www.hydrol-earth-syst-sci.net/volumes_and_issues.html -- 1607-7938 https://doi.org/10.5194/hess-21-589-2017 https://noa.gwlb.de/receive/cop_mods_00010478 https://noa.gwlb.de/servlets/MCRFileNodeServlet/cop_derivate_00010435/hess-21-589-2017.pdf https://hess.copernicus.org/articles/21/589/2017/hess-21-589-2017.pdf uneingeschränkt info:eu-repo/semantics/openAccess article Verlagsveröffentlichung article Text doc-type:article 2017 ftnonlinearchiv https://doi.org/10.5194/hess-21-589-2017 2022-02-08T22:57:03Z Current global precipitation (P) datasets do not take full advantage of the complementary nature of satellite and reanalysis data. Here, we present Multi-Source Weighted-Ensemble Precipitation (MSWEP) version 1.1, a global P dataset for the period 1979–2015 with a 3-hourly temporal and 0.25° spatial resolution, specifically designed for hydrological modeling. The design philosophy of MSWEP was to optimally merge the highest quality P data sources available as a function of timescale and location. The long-term mean of MSWEP was based on the CHPclim dataset but replaced with more accurate regional datasets where available. A correction for gauge under-catch and orographic effects was introduced by inferring catchment-average P from streamflow (Q) observations at 13 762 stations across the globe. The temporal variability of MSWEP was determined by weighted averaging of P anomalies from seven datasets; two based solely on interpolation of gauge observations (CPC Unified and GPCC), three on satellite remote sensing (CMORPH, GSMaP-MVK, and TMPA 3B42RT), and two on atmospheric model reanalysis (ERA-Interim and JRA-55). For each grid cell, the weight assigned to the gauge-based estimates was calculated from the gauge network density, while the weights assigned to the satellite- and reanalysis-based estimates were calculated from their comparative performance at the surrounding gauges. The quality of MSWEP was compared against four state-of-the-art gauge-adjusted P datasets (WFDEI-CRU, GPCP-1DD, TMPA 3B42, and CPC Unified) using independent P data from 125 FLUXNET tower stations around the globe. MSWEP obtained the highest daily correlation coefficient (R) among the five P datasets for 60.0 % of the stations and a median R of 0.67 vs. 0.44–0.59 for the other datasets. We further evaluated the performance of MSWEP using hydrological modeling for 9011 catchments (< 50 000 km2) across the globe. Specifically, we calibrated the simple conceptual hydrological model HBV (Hydrologiska Byråns Vattenbalansavdelning) against daily Q observations with P from each of the different datasets. For the 1058 sparsely gauged catchments, representative of 83.9 % of the global land surface (excluding Antarctica), MSWEP obtained a median calibration NSE of 0.52 vs. 0.29–0.39 for the other P datasets. MSWEP is available via http://www.gloh2o.org. Article in Journal/Newspaper Antarc* Antarctica Niedersächsisches Online-Archiv NOA Hydrology and Earth System Sciences 21 1 589 615 |
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English |
topic |
article Verlagsveröffentlichung |
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article Verlagsveröffentlichung Beck, Hylke E. van Dijk, Albert I. J. M. Levizzani, Vincenzo Schellekens, Jaap Miralles, Diego G. Martens, Brecht de Roo, Ad MSWEP: 3-hourly 0.25° global gridded precipitation (1979–2015) by merging gauge, satellite, and reanalysis data |
topic_facet |
article Verlagsveröffentlichung |
description |
Current global precipitation (P) datasets do not take full advantage of the complementary nature of satellite and reanalysis data. Here, we present Multi-Source Weighted-Ensemble Precipitation (MSWEP) version 1.1, a global P dataset for the period 1979–2015 with a 3-hourly temporal and 0.25° spatial resolution, specifically designed for hydrological modeling. The design philosophy of MSWEP was to optimally merge the highest quality P data sources available as a function of timescale and location. The long-term mean of MSWEP was based on the CHPclim dataset but replaced with more accurate regional datasets where available. A correction for gauge under-catch and orographic effects was introduced by inferring catchment-average P from streamflow (Q) observations at 13 762 stations across the globe. The temporal variability of MSWEP was determined by weighted averaging of P anomalies from seven datasets; two based solely on interpolation of gauge observations (CPC Unified and GPCC), three on satellite remote sensing (CMORPH, GSMaP-MVK, and TMPA 3B42RT), and two on atmospheric model reanalysis (ERA-Interim and JRA-55). For each grid cell, the weight assigned to the gauge-based estimates was calculated from the gauge network density, while the weights assigned to the satellite- and reanalysis-based estimates were calculated from their comparative performance at the surrounding gauges. The quality of MSWEP was compared against four state-of-the-art gauge-adjusted P datasets (WFDEI-CRU, GPCP-1DD, TMPA 3B42, and CPC Unified) using independent P data from 125 FLUXNET tower stations around the globe. MSWEP obtained the highest daily correlation coefficient (R) among the five P datasets for 60.0 % of the stations and a median R of 0.67 vs. 0.44–0.59 for the other datasets. We further evaluated the performance of MSWEP using hydrological modeling for 9011 catchments (< 50 000 km2) across the globe. Specifically, we calibrated the simple conceptual hydrological model HBV (Hydrologiska Byråns Vattenbalansavdelning) against daily Q observations with P from each of the different datasets. For the 1058 sparsely gauged catchments, representative of 83.9 % of the global land surface (excluding Antarctica), MSWEP obtained a median calibration NSE of 0.52 vs. 0.29–0.39 for the other P datasets. MSWEP is available via http://www.gloh2o.org. |
format |
Article in Journal/Newspaper |
author |
Beck, Hylke E. van Dijk, Albert I. J. M. Levizzani, Vincenzo Schellekens, Jaap Miralles, Diego G. Martens, Brecht de Roo, Ad |
author_facet |
Beck, Hylke E. van Dijk, Albert I. J. M. Levizzani, Vincenzo Schellekens, Jaap Miralles, Diego G. Martens, Brecht de Roo, Ad |
author_sort |
Beck, Hylke E. |
title |
MSWEP: 3-hourly 0.25° global gridded precipitation (1979–2015) by merging gauge, satellite, and reanalysis data |
title_short |
MSWEP: 3-hourly 0.25° global gridded precipitation (1979–2015) by merging gauge, satellite, and reanalysis data |
title_full |
MSWEP: 3-hourly 0.25° global gridded precipitation (1979–2015) by merging gauge, satellite, and reanalysis data |
title_fullStr |
MSWEP: 3-hourly 0.25° global gridded precipitation (1979–2015) by merging gauge, satellite, and reanalysis data |
title_full_unstemmed |
MSWEP: 3-hourly 0.25° global gridded precipitation (1979–2015) by merging gauge, satellite, and reanalysis data |
title_sort |
mswep: 3-hourly 0.25° global gridded precipitation (1979–2015) by merging gauge, satellite, and reanalysis data |
publisher |
Copernicus Publications |
publishDate |
2017 |
url |
https://doi.org/10.5194/hess-21-589-2017 https://noa.gwlb.de/receive/cop_mods_00010478 https://noa.gwlb.de/servlets/MCRFileNodeServlet/cop_derivate_00010435/hess-21-589-2017.pdf https://hess.copernicus.org/articles/21/589/2017/hess-21-589-2017.pdf |
genre |
Antarc* Antarctica |
genre_facet |
Antarc* Antarctica |
op_relation |
Hydrology and Earth System Sciences -- http://www.bibliothek.uni-regensburg.de/ezeit/?2100610 -- http://www.hydrol-earth-syst-sci.net/volumes_and_issues.html -- 1607-7938 https://doi.org/10.5194/hess-21-589-2017 https://noa.gwlb.de/receive/cop_mods_00010478 https://noa.gwlb.de/servlets/MCRFileNodeServlet/cop_derivate_00010435/hess-21-589-2017.pdf https://hess.copernicus.org/articles/21/589/2017/hess-21-589-2017.pdf |
op_rights |
uneingeschränkt info:eu-repo/semantics/openAccess |
op_doi |
https://doi.org/10.5194/hess-21-589-2017 |
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Hydrology and Earth System Sciences |
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21 |
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589 |
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615 |
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