Precipitation estimations based on remote sensing compared with data from weather stations over agricultural region of Argentina pampas

Autores
Ovando, Gustavo Gabriel; Sayago, Silvina; Bellini Saibene, Yanina Noemi; Belmonte, María Laura; Bocco, Mónica
Año de publicación
2021
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Global patterns of precipitation have changed due to the increase in temperature as a result of climate change. Measuring the amount of precipitation at a given location using surface instruments is relatively simple. However, the great spatial and temporal variability of the intensity, type and occurrence of this phenomenon, makes direct and uniformly calibrated measurements difficult in large regions. Satellite information is an important alternative to describe precipitation events; the Global Precipitation Measurement (GPM) mission estimates precipitation, considering different time periods, with three products Integrated Multi-Satellite Retrievals for GPM (IMERG), in near real time. This study evaluates and quantifies, temporal and spatially, the monthly precipitation estimated by Early (IMERG-E), Late (IMERG-L) and Final (IMERG-F) products compared with data from weather stations located in agricultural areas of the Pampas region in Argentina. Data of precipitation belonging to meteorological stations located at four provinces: Buenos Aires, Córdoba, La Pampa and Santa Fe, for 2014–2018 periods, were considered. The spatial performance of IMERG was evaluated using statistical coefficients and Taylor diagrams, considering at region, province and stations level. The adjustment of the products increased from IMERG-E to IMERG–F, obtaining R2 values between 0.86 and 0.95 and RMSE from 14.2 to 29.3 mm, the best results corresponding to Córdoba and the worst to La Pampa. The performance of GPM products varies temporally; IMERG-F presented a higher correlation coefficient and a lower percent root mean square error in warm than in cold seasons. The results indicate that GPM can effectively capture the amount and patterns of monthly precipitation over the Pampas region of Argentina, which is important for its application to agricultural production and disaster prevention.
EEA Anguil
Fil: Ovando, Gustavo. Universidad Nacional de Córdoba. Facultad de Ciencias Agropecuarias; Argentina
Fil: Sayago, Silvina. Universidad Nacional de Córdoba. Facultad de Ciencias Agropecuarias; Argentina
Fil: Bellini Saibene, Yanina. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Anguil; Argentina
Fil: Belmonte, María Laura. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Anguil; Argentina
Fil: Bocco, Monica. Universidad Nacional de Córdoba. Facultad de Ciencias Agropecuarias; Argentina
Fuente
Remote Sensing Applications: Society and Environment 23 : Article 100589. (August 2021)
Materia
Precipitación Atmosférica
Teledetección
Meteorología
Precipitation
Remote Sensing
Meteorology
Región Pampeana
Taylor Diagram
Nivel de accesibilidad
acceso restringido
Condiciones de uso
Repositorio
INTA Digital (INTA)
Institución
Instituto Nacional de Tecnología Agropecuaria
OAI Identificador
oai:localhost:20.500.12123/10833
Acceder
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spelling Precipitation estimations based on remote sensing compared with data from weather stations over agricultural region of Argentina pampasOvando, Gustavo GabrielSayago, SilvinaBellini Saibene, Yanina NoemiBelmonte, María LauraBocco, MónicaPrecipitación AtmosféricaTeledetecciónMeteorologíaPrecipitationRemote SensingMeteorologyRegión PampeanaTaylor DiagramGlobal patterns of precipitation have changed due to the increase in temperature as a result of climate change. Measuring the amount of precipitation at a given location using surface instruments is relatively simple. However, the great spatial and temporal variability of the intensity, type and occurrence of this phenomenon, makes direct and uniformly calibrated measurements difficult in large regions. Satellite information is an important alternative to describe precipitation events; the Global Precipitation Measurement (GPM) mission estimates precipitation, considering different time periods, with three products Integrated Multi-Satellite Retrievals for GPM (IMERG), in near real time. This study evaluates and quantifies, temporal and spatially, the monthly precipitation estimated by Early (IMERG-E), Late (IMERG-L) and Final (IMERG-F) products compared with data from weather stations located in agricultural areas of the Pampas region in Argentina. Data of precipitation belonging to meteorological stations located at four provinces: Buenos Aires, Córdoba, La Pampa and Santa Fe, for 2014–2018 periods, were considered. The spatial performance of IMERG was evaluated using statistical coefficients and Taylor diagrams, considering at region, province and stations level. The adjustment of the products increased from IMERG-E to IMERG–F, obtaining R2 values between 0.86 and 0.95 and RMSE from 14.2 to 29.3 mm, the best results corresponding to Córdoba and the worst to La Pampa. The performance of GPM products varies temporally; IMERG-F presented a higher correlation coefficient and a lower percent root mean square error in warm than in cold seasons. The results indicate that GPM can effectively capture the amount and patterns of monthly precipitation over the Pampas region of Argentina, which is important for its application to agricultural production and disaster prevention.EEA AnguilFil: Ovando, Gustavo. Universidad Nacional de Córdoba. Facultad de Ciencias Agropecuarias; ArgentinaFil: Sayago, Silvina. Universidad Nacional de Córdoba. Facultad de Ciencias Agropecuarias; ArgentinaFil: Bellini Saibene, Yanina. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Anguil; ArgentinaFil: Belmonte, María Laura. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Anguil; ArgentinaFil: Bocco, Monica. Universidad Nacional de Córdoba. Facultad de Ciencias Agropecuarias; ArgentinaElsevier2021-12-02T12:48:00Z2021-12-02T12:48:00Z2021-08-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfhttp://hdl.handle.net/20.500.12123/10833https://www.sciencedirect.com/science/article/pii/S23529385210012572352-9385https://doi.org/10.1016/j.rsase.2021.100589Remote Sensing Applications: Society and Environment 23 : Article 100589. (August 2021)reponame:INTA Digital (INTA)instname:Instituto Nacional de Tecnología Agropecuariaenginfo:eu-repo/semantics/restrictedAccess2025-12-18T09:02:13Zoai:localhost:20.500.12123/10833instacron:INTAInstitucionalhttp://repositorio.inta.gob.ar/Organismo científico-tecnológicoNo correspondehttp://repositorio.inta.gob.ar/oai/requesttripaldi.nicolas@inta.gob.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:l2025-12-18 09:02:13.668INTA Digital (INTA) - Instituto Nacional de Tecnología Agropecuariafalse
dc.title.none.fl_str_mv Precipitation estimations based on remote sensing compared with data from weather stations over agricultural region of Argentina pampas
title Precipitation estimations based on remote sensing compared with data from weather stations over agricultural region of Argentina pampas
spellingShingle Precipitation estimations based on remote sensing compared with data from weather stations over agricultural region of Argentina pampas
Ovando, Gustavo Gabriel
Precipitación Atmosférica
Teledetección
Meteorología
Precipitation
Remote Sensing
Meteorology
Región Pampeana
Taylor Diagram
title_short Precipitation estimations based on remote sensing compared with data from weather stations over agricultural region of Argentina pampas
title_full Precipitation estimations based on remote sensing compared with data from weather stations over agricultural region of Argentina pampas
title_fullStr Precipitation estimations based on remote sensing compared with data from weather stations over agricultural region of Argentina pampas
title_full_unstemmed Precipitation estimations based on remote sensing compared with data from weather stations over agricultural region of Argentina pampas
title_sort Precipitation estimations based on remote sensing compared with data from weather stations over agricultural region of Argentina pampas
dc.creator.none.fl_str_mv Ovando, Gustavo Gabriel
Sayago, Silvina
Bellini Saibene, Yanina Noemi
Belmonte, María Laura
Bocco, Mónica
author Ovando, Gustavo Gabriel
author_facet Ovando, Gustavo Gabriel
Sayago, Silvina
Bellini Saibene, Yanina Noemi
Belmonte, María Laura
Bocco, Mónica
author_role author
author2 Sayago, Silvina
Bellini Saibene, Yanina Noemi
Belmonte, María Laura
Bocco, Mónica
author2_role author
author
author
author
dc.subject.none.fl_str_mv Precipitación Atmosférica
Teledetección
Meteorología
Precipitation
Remote Sensing
Meteorology
Región Pampeana
Taylor Diagram
topic Precipitación Atmosférica
Teledetección
Meteorología
Precipitation
Remote Sensing
Meteorology
Región Pampeana
Taylor Diagram
dc.description.none.fl_txt_mv Global patterns of precipitation have changed due to the increase in temperature as a result of climate change. Measuring the amount of precipitation at a given location using surface instruments is relatively simple. However, the great spatial and temporal variability of the intensity, type and occurrence of this phenomenon, makes direct and uniformly calibrated measurements difficult in large regions. Satellite information is an important alternative to describe precipitation events; the Global Precipitation Measurement (GPM) mission estimates precipitation, considering different time periods, with three products Integrated Multi-Satellite Retrievals for GPM (IMERG), in near real time. This study evaluates and quantifies, temporal and spatially, the monthly precipitation estimated by Early (IMERG-E), Late (IMERG-L) and Final (IMERG-F) products compared with data from weather stations located in agricultural areas of the Pampas region in Argentina. Data of precipitation belonging to meteorological stations located at four provinces: Buenos Aires, Córdoba, La Pampa and Santa Fe, for 2014–2018 periods, were considered. The spatial performance of IMERG was evaluated using statistical coefficients and Taylor diagrams, considering at region, province and stations level. The adjustment of the products increased from IMERG-E to IMERG–F, obtaining R2 values between 0.86 and 0.95 and RMSE from 14.2 to 29.3 mm, the best results corresponding to Córdoba and the worst to La Pampa. The performance of GPM products varies temporally; IMERG-F presented a higher correlation coefficient and a lower percent root mean square error in warm than in cold seasons. The results indicate that GPM can effectively capture the amount and patterns of monthly precipitation over the Pampas region of Argentina, which is important for its application to agricultural production and disaster prevention.
EEA Anguil
Fil: Ovando, Gustavo. Universidad Nacional de Córdoba. Facultad de Ciencias Agropecuarias; Argentina
Fil: Sayago, Silvina. Universidad Nacional de Córdoba. Facultad de Ciencias Agropecuarias; Argentina
Fil: Bellini Saibene, Yanina. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Anguil; Argentina
Fil: Belmonte, María Laura. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Anguil; Argentina
Fil: Bocco, Monica. Universidad Nacional de Córdoba. Facultad de Ciencias Agropecuarias; Argentina
description Global patterns of precipitation have changed due to the increase in temperature as a result of climate change. Measuring the amount of precipitation at a given location using surface instruments is relatively simple. However, the great spatial and temporal variability of the intensity, type and occurrence of this phenomenon, makes direct and uniformly calibrated measurements difficult in large regions. Satellite information is an important alternative to describe precipitation events; the Global Precipitation Measurement (GPM) mission estimates precipitation, considering different time periods, with three products Integrated Multi-Satellite Retrievals for GPM (IMERG), in near real time. This study evaluates and quantifies, temporal and spatially, the monthly precipitation estimated by Early (IMERG-E), Late (IMERG-L) and Final (IMERG-F) products compared with data from weather stations located in agricultural areas of the Pampas region in Argentina. Data of precipitation belonging to meteorological stations located at four provinces: Buenos Aires, Córdoba, La Pampa and Santa Fe, for 2014–2018 periods, were considered. The spatial performance of IMERG was evaluated using statistical coefficients and Taylor diagrams, considering at region, province and stations level. The adjustment of the products increased from IMERG-E to IMERG–F, obtaining R2 values between 0.86 and 0.95 and RMSE from 14.2 to 29.3 mm, the best results corresponding to Córdoba and the worst to La Pampa. The performance of GPM products varies temporally; IMERG-F presented a higher correlation coefficient and a lower percent root mean square error in warm than in cold seasons. The results indicate that GPM can effectively capture the amount and patterns of monthly precipitation over the Pampas region of Argentina, which is important for its application to agricultural production and disaster prevention.
publishDate 2021
dc.date.none.fl_str_mv 2021-12-02T12:48:00Z
2021-12-02T12:48:00Z
2021-08-01
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/20.500.12123/10833
https://www.sciencedirect.com/science/article/pii/S2352938521001257
2352-9385
https://doi.org/10.1016/j.rsase.2021.100589
url http://hdl.handle.net/20.500.12123/10833
https://www.sciencedirect.com/science/article/pii/S2352938521001257
https://doi.org/10.1016/j.rsase.2021.100589
identifier_str_mv 2352-9385
dc.language.none.fl_str_mv eng
language eng
dc.rights.none.fl_str_mv info:eu-repo/semantics/restrictedAccess
eu_rights_str_mv restrictedAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Elsevier
publisher.none.fl_str_mv Elsevier
dc.source.none.fl_str_mv Remote Sensing Applications: Society and Environment 23 : Article 100589. (August 2021)
reponame:INTA Digital (INTA)
instname:Instituto Nacional de Tecnología Agropecuaria
reponame_str INTA Digital (INTA)
collection INTA Digital (INTA)
instname_str Instituto Nacional de Tecnología Agropecuaria
repository.name.fl_str_mv INTA Digital (INTA) - Instituto Nacional de Tecnología Agropecuaria
repository.mail.fl_str_mv tripaldi.nicolas@inta.gob.ar
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score 12.952241

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