气候变化领域集成服务门户(CCPortal): Bias correction of global high-resolution precipitation climatologies using streamflow observations from 9372 catchments

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DOI	10.1175/JCLI-D-19-0332.1
	Bias correction of global high-resolution precipitation climatologies using streamflow observations from 9372 catchments
	Beck H.E.; Wood E.F.; McVicar T.R.; Zambrano-Bigiarini M.; Alvarez-Garreton C.; Baez-Villanueva O.M.; Sheffield J.; Karger D.N.
发表日期	2020
ISSN	0894-8755
起始页码	1299
结束页码	1315
卷号	33 期号:4
英文摘要	We introduce a set of global high-resolution (0.058) precipitation (P) climatologies corrected for bias using streamflow (Q) observations from 9372 stations worldwide. For each station, we inferred the ‘‘true’’ long-term P using a Budyko curve, which is an empirical equation relating long-term P, Q, and potential evaporation. We subsequently calculated long-term bias correction factors for three state-of-the-art P climatologies [the ‘‘WorldClim version 2’’ database (WorldClim V2); Climatologies at High Resolution for the Earth’s Land Surface Areas, version 1.2 (CHELSA V1.2); and Climate Hazards Group Precipitation Climatology, version 1 (CHPclim V1)], after which we used random-forest regression to produce global gap-free bias correction maps for the P climatologies. Monthly climatological bias correction factors were calculated by disaggregating the long-term bias correction factors on the basis of gauge catch efficiencies. We found that all three climatologies systematically underestimate P over parts of all major mountain ranges globally, despite the explicit consideration of orography in the production of each climatology. In addition, all climatologies underestimate P at latitudes .608N, likely because of gauge undercatch. Exceptionally high long-term correction factors (.1.5) were obtained for all three P climatologies in Alaska, High Mountain Asia, and Chile—regions characterized by marked elevation gradients, sparse gauge networks, and significant snowfall. Using the bias-corrected WorldClim V2, we demonstrated that other widely used P datasets (GPCC V2015, GPCP V2.3, and MERRA-2) severely underestimate P over Chile, the Himalayas, and along the Pacific coast of North America. Mean P for the global land surface based on the bias-corrected WorldClim V2 is 862 mm yr21 (a 9.4% increase over the original WorldClim V2). The annual and monthly bias-corrected P climatologies have been released as the Precipitation Bias Correction (PBCOR) dataset, which is available online (http://www.gloh2o.org/pbcor/). © 2020 American Meteorological Society.
英文关键词	Catchments; Decision trees; Earth (planet); Gages; Random forests; Stream flow; Surface measurement; Correction factors; Elevation gradient; Empirical equations; Global land surface; Mountain ranges; Potential evaporation; Precipitation climatology; State of the art; Climatology; catchment; correlation; precipitation (climatology); rainfall-runoff modeling; raingauge; sampling bias; spatial resolution; streamflow
语种	英语
来源期刊	Journal of Climate
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/171454
作者单位	Department of Civil and Environmental Engineering, Princeton University, Princeton, NJ, United States; CSIRO Land and Water, Black Mountain, Canberra, Australia; Australian Research Council Centre of Excellence for Climate Extremes, Canberra, Australia; Department of Civil Engineering, Universidad de La Frontera, Temuco, Chile; Center for Climate and Resilience Research, Santiago, Chile; Institute of Conservation, Biodiversity and Territory, Universidad Austral de Chile, Valdivia, Chile; Institute for Technology and Resources Management in the Tropics and Subtropics (ITT), Technology Arts Sciences TH Koln, €, Cologne, Germany; Faculty of Spatial Planning, TU Dortmund University, Dortmund, Germany; School of Geography and Environmental Science, University of Southampton, Southampton, United Kingdom; Swiss Federal Research Institute WSL, Birmensdorf, Switzerland
推荐引用方式 GB/T 7714	Beck H.E.,Wood E.F.,McVicar T.R.,et al. Bias correction of global high-resolution precipitation climatologies using streamflow observations from 9372 catchments[J],2020,33(4).
APA	Beck H.E..,Wood E.F..,McVicar T.R..,Zambrano-Bigiarini M..,Alvarez-Garreton C..,...&Karger D.N..(2020).Bias correction of global high-resolution precipitation climatologies using streamflow observations from 9372 catchments.Journal of Climate,33(4).
MLA	Beck H.E.,et al."Bias correction of global high-resolution precipitation climatologies using streamflow observations from 9372 catchments".Journal of Climate 33.4(2020).