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 |
| Summary: | 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. |
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| ISSN: | 1027-5606 1607-7938 |