DOI: 10.5194/hess-21-589-2017
Scopus记录号: 2-s2.0-85011049856
论文题名: MSWEP: 3-hourly 0.25° global gridded precipitation (1979-2015) by merging gauge, satellite, and reanalysis data
作者: Beck H ; E ; , Van Dijk A ; I ; J ; M ; , Levizzani V ; , Schellekens J ; , Miralles D ; G ; , Martens B ; , De Roo A
刊名: Hydrology and Earth System Sciences
ISSN: 10275606
出版年: 2017
卷: 21, 期: 1 起始页码: 589
结束页码: 615
语种: 英语
Scopus关键词: Calibration
; Catchments
; Hydrology
; Precipitation (meteorology)
; Remote sensing
; Runoff
; Satellites
; Comparative performance
; Correlation coefficient
; Global land surface
; Global precipitation
; Hydrological modeling
; Orographic effects
; Satellite remote sensing
; Temporal variability
; Gages
; calibration
; hydrological modeling
; interpolation
; land surface
; philosophy
; precipitation assessment
; raingauge
; remote sensing
; satellite altimetry
; streamflow
; Hepatitis B virus
英文摘要: 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 km/2) across the globe. Specifically, we calibrated the simple conceptual hydrological model HBV (Hydrologiska Byräns 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. © Author(s) 2017. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/79277
Appears in Collections: 气候变化事实与影响
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作者单位: European Commission, Joint Research Centre (JRC), Via Enrico Fermi 2749, Ispra (VA), Italy; Fenner School of Environment and Society, Australian National University, Canberra, Australia; National Research Council of Italy, Institute of Atmospheric Sciences and Climate (CNR-ISAC), Bologna, Italy; Inland Water Systems Unit, Deltares, Delft, Netherlands; Laboratory of Hydrology and Water Management, Ghent University, Ghent, Belgium; Department of Earth Sciences, VU University Amsterdam, Amsterdam, Netherlands
Recommended Citation:
Beck H,E,, Van Dijk A,et al. MSWEP: 3-hourly 0.25° global gridded precipitation (1979-2015) by merging gauge, satellite, and reanalysis data[J]. Hydrology and Earth System Sciences,2017-01-01,21(1)