Multiregional satellite precipitation products evaluation over complex terrain

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dc.contributor.authorderin, yagmur
dc.contributor.authorAnagnostou, Emmanouil
dc.contributor.authorBerne, Alexis
dc.contributor.authorBorga, Marco
dc.contributor.authorBoudevillain, Brice
dc.contributor.authorBuytaert, Wouter
dc.contributor.authorChang, Che-Hao
dc.contributor.authorDelrieu, Guy
dc.contributor.authorHong, Yang
dc.contributor.authorHsu, Yung-Chia
dc.contributor.authorlavado-casimiro, waldo
dc.contributor.authorManz, Bastian
dc.contributor.authorMoges, Semu
dc.contributor.authorNikolopoulos, Efthymios
dc.contributor.authorSahlu, Dejene
dc.contributor.authorSalerno, Franco
dc.contributor.authorRodríguez Sánchez, Juan Pablo
dc.contributor.authorVergara, Humberto J.
dc.contributor.authorYilmaz, Koray K.
dc.date.accessioned2020-04-24T16:48:52Z
dc.date.available2020-04-24T16:48:52Z
dc.date.issued2016
dc.description.abstractenglishAn extensive evaluation of nine global-scale high-resolution satellite-based rainfall (SBR) products is performed using a minimum of 6 years (within the period of 2000–13) of reference rainfall data derived from rain gauge networks in nine mountainous regions across the globe. The SBR products are compared to a recently released global reanalysis dataset from the European Centre for Medium-Range Weather Forecasts (ECMWF). The study areas include the eastern Italian Alps, the Swiss Alps, the western Black Sea of Turkey, the French Cévennes, the Peruvian Andes, the Colombian Andes, the Himalayas over Nepal, the Blue Nile in East Africa, Taiwan, and the U.S. Rocky Mountains. Evaluation is performed at annual, monthly, and daily time scales and 0.25° spatial resolution. The SBR datasets are based on the following retrieval algorithms: Tropical Rainfall Measuring Mission Multisatellite Precipitation Analysis (TMPA), the NOAA/Climate Prediction Center morphing technique (CMORPH), Precipitation Estimation from Remotely Sensed Information Using Artificial Neural Networks (PERSIANN), and Global Satellite Mapping of Precipitation (GSMaP). SBR products are categorized into those that include gauge adjustment versus unadjusted. Results show that performance of SBR is highly dependent on the rainfall variability. Many SBR products usually underestimate wet season and overestimate dry season precipitation. The performance of gauge adjustment to the SBR products varies by region and depends greatly on the representativeness of the rain gauge network.eng
dc.format.mimetypeapplication/pdf
dc.identifier.doihttps://doi.org/10.1175/JHM-D-15-0197.1
dc.identifier.instnameinstname:Universidad El Bosquespa
dc.identifier.issn1525-7541
dc.identifier.reponamereponame:Repositorio Institucional Universidad El Bosquespa
dc.identifier.repourlrepourl:https://repositorio.unbosque.edu.co
dc.identifier.urihttps://hdl.handle.net/20.500.12495/2372
dc.language.isoeng
dc.publisherAmerican Meteorological Societyspa
dc.publisher.journalJournal of hydrometeorologyspa
dc.relation.ispartofseriesJournal of hydrometeorology, 1525-7541. Nro, 17, Vol, 6. 2016, p. 1817-1836spa
dc.relation.urihttps://journals.ametsoc.org/doi/full/10.1175/JHM-D-15-0197.1
dc.rights.accessrightsinfo:eu-repo/semantics/openAccess
dc.rights.accessrightshttps://purl.org/coar/access_right/c_abf119
dc.rights.creativecommons2016
dc.rights.localAcceso cerradospa
dc.subject.unescoControl meteorológicospa
dc.subject.unescoSatélite meteorológicospa
dc.subject.unescoCartografíaspa
dc.titleMultiregional satellite precipitation products evaluation over complex terrainspa
dc.title.translatedMultiregional satellite precipitation products evaluation over complex terrain
dc.typearticlespa
dc.type.hasversioninfo:eu-repo/semantics/publishedVersion
dc.type.localartículospa

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Derin Y., Anagnostou E., Berne A., Borga M., Boudevillain B., Buytaert W., Chang C.-H., Delrieu G., Hong Y., Hsu Y.C., Lavado-Casimiro W., Manz B., Moges S., Nikolopoulos E_2016.pdf
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