Global-scale evaluation of 22 precipitation datasets using gauge observations and hydrological modeling
We undertook a comprehensive evaluation of 22 gridded (quasi-)global (sub-)daily precipitation (<i>P</i>) datasets for the period 2000–2016. Thirteen non-gauge-corrected <i>P</i> datasets were evaluated using daily <i>P</i> gauge observations from 76 086 gauges...
| Main Authors: | , , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Copernicus Publications
2017-12-01
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| Series: | Hydrology and Earth System Sciences |
| Online Access: | https://www.hydrol-earth-syst-sci.net/21/6201/2017/hess-21-6201-2017.pdf |
| _version_ | 1818452798197465088 |
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| author | H. E. Beck N. Vergopolan M. Pan V. Levizzani A. I. J. M. van Dijk G. P. Weedon L. Brocca F. Pappenberger G. J. Huffman E. F. Wood |
| author_facet | H. E. Beck N. Vergopolan M. Pan V. Levizzani A. I. J. M. van Dijk G. P. Weedon L. Brocca F. Pappenberger G. J. Huffman E. F. Wood |
| author_sort | H. E. Beck |
| collection | DOAJ |
| description | We undertook a comprehensive evaluation of 22 gridded (quasi-)global
(sub-)daily precipitation (<i>P</i>) datasets for the period 2000–2016. Thirteen
non-gauge-corrected <i>P</i> datasets were evaluated using daily <i>P</i> gauge
observations from 76 086 gauges worldwide. Another nine gauge-corrected
datasets were evaluated using hydrological modeling, by calibrating the HBV
conceptual model against streamflow records for each of 9053 small to
medium-sized ( < 50 000 km<sup>2</sup>) catchments worldwide, and comparing the
resulting performance. Marked differences in spatio-temporal patterns and
accuracy were found among the datasets. Among the uncorrected <i>P</i> datasets,
the satellite- and reanalysis-based MSWEP-ng V1.2 and V2.0 datasets generally
showed the best temporal correlations with the gauge observations, followed
by the reanalyses (ERA-Interim, JRA-55, and NCEP-CFSR) and the satellite- and
reanalysis-based CHIRP V2.0 dataset, the estimates based primarily on passive
microwave remote sensing of rainfall (CMORPH V1.0, GSMaP V5/6, and TMPA
3B42RT V7) or near-surface soil moisture (SM2RAIN-ASCAT), and finally,
estimates based primarily on thermal infrared imagery (GridSat V1.0,
PERSIANN, and PERSIANN-CCS). Two of the three reanalyses (ERA-Interim and
JRA-55) unexpectedly obtained lower trend errors than the satellite datasets.
Among the corrected <i>P</i> datasets, the ones directly incorporating daily gauge
data (CPC Unified, and MSWEP V1.2
and V2.0) generally provided the best calibration scores, although the good
performance of the fully gauge-based CPC Unified is unlikely to translate to
sparsely or ungauged regions. Next best results were obtained with <i>P</i>
estimates directly incorporating temporally coarser gauge data (CHIRPS V2.0,
GPCP-1DD V1.2, TMPA 3B42 V7, and WFDEI-CRU), which in turn outperformed the
one indirectly incorporating gauge data through another multi-source dataset
(PERSIANN-CDR V1R1). Our results highlight large differences in estimation
accuracy, and hence the importance of <i>P</i> dataset selection in both research
and operational applications. The good performance of MSWEP emphasizes that
careful data merging can exploit the complementary strengths of gauge-,
satellite-, and reanalysis-based <i>P</i>
estimates. |
| first_indexed | 2024-12-14T21:28:49Z |
| format | Article |
| id | doaj.art-0267ddf272fc441aab133e6987039a74 |
| institution | Directory Open Access Journal |
| issn | 1027-5606 1607-7938 |
| language | English |
| last_indexed | 2024-12-14T21:28:49Z |
| publishDate | 2017-12-01 |
| publisher | Copernicus Publications |
| record_format | Article |
| series | Hydrology and Earth System Sciences |
| spelling | doaj.art-0267ddf272fc441aab133e6987039a742022-12-21T22:46:43ZengCopernicus PublicationsHydrology and Earth System Sciences1027-56061607-79382017-12-01216201621710.5194/hess-21-6201-2017Global-scale evaluation of 22 precipitation datasets using gauge observations and hydrological modelingH. E. Beck0N. Vergopolan1M. Pan2V. Levizzani3A. I. J. M. van Dijk4G. P. Weedon5L. Brocca6F. Pappenberger7G. J. Huffman8E. F. Wood9Department of Civil and Environmental Engineering, Princeton University, Princeton, New Jersey, USADepartment of Civil and Environmental Engineering, Princeton University, Princeton, New Jersey, USADepartment of Civil and Environmental Engineering, Princeton University, Princeton, New Jersey, USANational Research Council of Italy, Institute of Atmospheric Sciences and Climate (CNR-ISAC), Bologna, ItalyFenner School of Environment & Society, The Australian National University, Canberra, AustraliaMet Office, Joint Centre for Hydro-Meteorological Research, Wallingford, UKResearch Institute for Geo-Hydrological Protection, National Research Council, Perugia, ItalyEuropean Centre for Medium-Range Weather Forecasts, Shinfield Park, Reading, UKMesoscale Atmospheric Processes Laboratory, NASA Goddard Space Flight Center, Greenbelt, Maryland, USADepartment of Civil and Environmental Engineering, Princeton University, Princeton, New Jersey, USAWe undertook a comprehensive evaluation of 22 gridded (quasi-)global (sub-)daily precipitation (<i>P</i>) datasets for the period 2000–2016. Thirteen non-gauge-corrected <i>P</i> datasets were evaluated using daily <i>P</i> gauge observations from 76 086 gauges worldwide. Another nine gauge-corrected datasets were evaluated using hydrological modeling, by calibrating the HBV conceptual model against streamflow records for each of 9053 small to medium-sized ( < 50 000 km<sup>2</sup>) catchments worldwide, and comparing the resulting performance. Marked differences in spatio-temporal patterns and accuracy were found among the datasets. Among the uncorrected <i>P</i> datasets, the satellite- and reanalysis-based MSWEP-ng V1.2 and V2.0 datasets generally showed the best temporal correlations with the gauge observations, followed by the reanalyses (ERA-Interim, JRA-55, and NCEP-CFSR) and the satellite- and reanalysis-based CHIRP V2.0 dataset, the estimates based primarily on passive microwave remote sensing of rainfall (CMORPH V1.0, GSMaP V5/6, and TMPA 3B42RT V7) or near-surface soil moisture (SM2RAIN-ASCAT), and finally, estimates based primarily on thermal infrared imagery (GridSat V1.0, PERSIANN, and PERSIANN-CCS). Two of the three reanalyses (ERA-Interim and JRA-55) unexpectedly obtained lower trend errors than the satellite datasets. Among the corrected <i>P</i> datasets, the ones directly incorporating daily gauge data (CPC Unified, and MSWEP V1.2 and V2.0) generally provided the best calibration scores, although the good performance of the fully gauge-based CPC Unified is unlikely to translate to sparsely or ungauged regions. Next best results were obtained with <i>P</i> estimates directly incorporating temporally coarser gauge data (CHIRPS V2.0, GPCP-1DD V1.2, TMPA 3B42 V7, and WFDEI-CRU), which in turn outperformed the one indirectly incorporating gauge data through another multi-source dataset (PERSIANN-CDR V1R1). Our results highlight large differences in estimation accuracy, and hence the importance of <i>P</i> dataset selection in both research and operational applications. The good performance of MSWEP emphasizes that careful data merging can exploit the complementary strengths of gauge-, satellite-, and reanalysis-based <i>P</i> estimates.https://www.hydrol-earth-syst-sci.net/21/6201/2017/hess-21-6201-2017.pdf |
| spellingShingle | H. E. Beck N. Vergopolan M. Pan V. Levizzani A. I. J. M. van Dijk G. P. Weedon L. Brocca F. Pappenberger G. J. Huffman E. F. Wood Global-scale evaluation of 22 precipitation datasets using gauge observations and hydrological modeling Hydrology and Earth System Sciences |
| title | Global-scale evaluation of 22 precipitation datasets using gauge observations and hydrological modeling |
| title_full | Global-scale evaluation of 22 precipitation datasets using gauge observations and hydrological modeling |
| title_fullStr | Global-scale evaluation of 22 precipitation datasets using gauge observations and hydrological modeling |
| title_full_unstemmed | Global-scale evaluation of 22 precipitation datasets using gauge observations and hydrological modeling |
| title_short | Global-scale evaluation of 22 precipitation datasets using gauge observations and hydrological modeling |
| title_sort | global scale evaluation of 22 precipitation datasets using gauge observations and hydrological modeling |
| url | https://www.hydrol-earth-syst-sci.net/21/6201/2017/hess-21-6201-2017.pdf |
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