Multiregional satellite precipitation products evaluation over complex terrain

An 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 c...

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Autores:
derin, yagmur
Anagnostou, Emmanouil
Berne, Alexis
Borga, Marco
Boudevillain, Brice
Buytaert, Wouter
Chang, Che-Hao
Delrieu, Guy
Hong, Yang
Hsu, Yung-Chia
lavado-casimiro, waldo
Manz, Bastian
Moges, Semu
Nikolopoulos, Efthymios
Sahlu, Dejene
Salerno, Franco
Rodríguez Sánchez, Juan Pablo
Vergara, Humberto J.
Yilmaz, Koray K.
Tipo de recurso:
Fecha de publicación:
2016
Institución:
Universidad El Bosque
Repositorio:
Repositorio U. El Bosque
Idioma:
eng
OAI Identifier:
oai:repositorio.unbosque.edu.co:20.500.12495/2372
Acceso en línea:
http://hdl.handle.net/20.500.12495/2372
https://doi.org/10.1175/JHM-D-15-0197.1
Palabra clave:
Control meteorológico
Satélite meteorológico
Cartografía
Rights
License
Acceso cerrado
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network_name_str Repositorio U. El Bosque
repository_id_str
dc.title.spa.fl_str_mv Multiregional satellite precipitation products evaluation over complex terrain
dc.title.translated.none.fl_str_mv Multiregional satellite precipitation products evaluation over complex terrain
title Multiregional satellite precipitation products evaluation over complex terrain
spellingShingle Multiregional satellite precipitation products evaluation over complex terrain
Control meteorológico
Satélite meteorológico
Cartografía
title_short Multiregional satellite precipitation products evaluation over complex terrain
title_full Multiregional satellite precipitation products evaluation over complex terrain
title_fullStr Multiregional satellite precipitation products evaluation over complex terrain
title_full_unstemmed Multiregional satellite precipitation products evaluation over complex terrain
title_sort Multiregional satellite precipitation products evaluation over complex terrain
dc.creator.fl_str_mv derin, yagmur
Anagnostou, Emmanouil
Berne, Alexis
Borga, Marco
Boudevillain, Brice
Buytaert, Wouter
Chang, Che-Hao
Delrieu, Guy
Hong, Yang
Hsu, Yung-Chia
lavado-casimiro, waldo
Manz, Bastian
Moges, Semu
Nikolopoulos, Efthymios
Sahlu, Dejene
Salerno, Franco
Rodríguez Sánchez, Juan Pablo
Vergara, Humberto J.
Yilmaz, Koray K.
dc.contributor.author.none.fl_str_mv derin, yagmur
Anagnostou, Emmanouil
Berne, Alexis
Borga, Marco
Boudevillain, Brice
Buytaert, Wouter
Chang, Che-Hao
Delrieu, Guy
Hong, Yang
Hsu, Yung-Chia
lavado-casimiro, waldo
Manz, Bastian
Moges, Semu
Nikolopoulos, Efthymios
Sahlu, Dejene
Salerno, Franco
Rodríguez Sánchez, Juan Pablo
Vergara, Humberto J.
Yilmaz, Koray K.
dc.subject.unesco.spa.fl_str_mv Control meteorológico
Satélite meteorológico
Cartografía
topic Control meteorológico
Satélite meteorológico
Cartografía
description An 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.
publishDate 2016
dc.date.issued.none.fl_str_mv 2016
dc.date.accessioned.none.fl_str_mv 2020-04-24T16:48:52Z
dc.date.available.none.fl_str_mv 2020-04-24T16:48:52Z
dc.type.spa.fl_str_mv article
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dc.type.local.spa.fl_str_mv artículo
dc.identifier.issn.none.fl_str_mv 1525-7541
dc.identifier.uri.none.fl_str_mv http://hdl.handle.net/20.500.12495/2372
dc.identifier.doi.none.fl_str_mv https://doi.org/10.1175/JHM-D-15-0197.1
dc.identifier.instname.spa.fl_str_mv instname:Universidad El Bosque
dc.identifier.reponame.spa.fl_str_mv reponame:Repositorio Institucional Universidad El Bosque
dc.identifier.repourl.none.fl_str_mv repourl:https://repositorio.unbosque.edu.co
identifier_str_mv 1525-7541
instname:Universidad El Bosque
reponame:Repositorio Institucional Universidad El Bosque
repourl:https://repositorio.unbosque.edu.co
url http://hdl.handle.net/20.500.12495/2372
https://doi.org/10.1175/JHM-D-15-0197.1
dc.language.iso.none.fl_str_mv eng
language eng
dc.relation.ispartofseries.spa.fl_str_mv Journal of hydrometeorology, 1525-7541. Nro, 17, Vol, 6. 2016, p. 1817-1836
dc.relation.uri.none.fl_str_mv https://journals.ametsoc.org/doi/full/10.1175/JHM-D-15-0197.1
dc.rights.coar.fl_str_mv http://purl.org/coar/access_right/c_abf2
dc.rights.local.spa.fl_str_mv Acceso cerrado
dc.rights.accessrights.none.fl_str_mv http://purl.org/coar/access_right/c_abf119
dc.rights.creativecommons.none.fl_str_mv 2016
rights_invalid_str_mv Acceso cerrado
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2016
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dc.format.mimetype.none.fl_str_mv application/pdf
dc.publisher.spa.fl_str_mv American Meteorological Society
dc.publisher.journal.spa.fl_str_mv Journal of hydrometeorology
institution Universidad El Bosque
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spelling derin, yagmurAnagnostou, EmmanouilBerne, AlexisBorga, MarcoBoudevillain, BriceBuytaert, WouterChang, Che-HaoDelrieu, GuyHong, YangHsu, Yung-Chialavado-casimiro, waldoManz, BastianMoges, SemuNikolopoulos, EfthymiosSahlu, DejeneSalerno, FrancoRodríguez Sánchez, Juan PabloVergara, Humberto J.Yilmaz, Koray K.2020-04-24T16:48:52Z2020-04-24T16:48:52Z20161525-7541http://hdl.handle.net/20.500.12495/2372https://doi.org/10.1175/JHM-D-15-0197.1instname:Universidad El Bosquereponame:Repositorio Institucional Universidad El Bosquerepourl:https://repositorio.unbosque.edu.coapplication/pdfengAmerican Meteorological SocietyJournal of hydrometeorologyJournal of hydrometeorology, 1525-7541. Nro, 17, Vol, 6. 2016, p. 1817-1836https://journals.ametsoc.org/doi/full/10.1175/JHM-D-15-0197.1Multiregional satellite precipitation products evaluation over complex terrainMultiregional satellite precipitation products evaluation over complex terrainarticleartículohttp://purl.org/coar/version/c_970fb48d4fbd8a85http://purl.org/coar/resource_type/c_6501Control meteorológicoSatélite meteorológicoCartografíaAn 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.Acceso cerradohttp://purl.org/coar/access_right/c_abf1192016http://purl.org/coar/access_right/c_abf2THUMBNAILDerin 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.jpgDerin 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.jpgimage/jpeg5775https://repositorio.unbosque.edu.co/bitstreams/5a95b3a9-55fc-4bcb-9602-7d15a26dad61/download7210a811635d1799e7c05fee5d259be7MD53ORIGINALDerin 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.pdfDerin 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.pdfapplication/pdf3752955https://repositorio.unbosque.edu.co/bitstreams/483cb9a2-909b-47f1-8ef9-31dbbff99fe6/downloadd5fe420df636a45d00adb32403c00fb9MD51LICENSElicense.txtlicense.txttext/plain; charset=utf-81748https://repositorio.unbosque.edu.co/bitstreams/356a2ac6-386b-4865-a794-d21a6c2a9462/download8a4605be74aa9ea9d79846c1fba20a33MD52TEXTDerin 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.txtDerin 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.txtExtracted texttext/plain80765https://repositorio.unbosque.edu.co/bitstreams/73df71b8-a30f-4b88-9a31-44e29b774c45/download42fc711a7824428c4ed04d1eebe29d7eMD5420.500.12495/2372oai:repositorio.unbosque.edu.co:20.500.12495/23722024-02-06 22:41:01.565restrictedhttps://repositorio.unbosque.edu.coRepositorio Institucional Universidad El Bosquebibliotecas@biteca.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