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resumen

Resumen
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 [ver mas...]
dc.contributor.authorOvando, Gustavo Gabriel
dc.contributor.authorSayago, Silvina
dc.contributor.authorBellini Saibene, Yanina Noemi
dc.contributor.authorBelmonte, María Laura
dc.contributor.authorBocco, Mónica
dc.date.accessioned2021-12-02T12:48:00Z
dc.date.available2021-12-02T12:48:00Z
dc.date.issued2021-08-01
dc.identifier.issn2352-9385
dc.identifier.otherhttps://doi.org/10.1016/j.rsase.2021.100589
dc.identifier.urihttp://hdl.handle.net/20.500.12123/10833
dc.identifier.urihttps://www.sciencedirect.com/science/article/pii/S2352938521001257
dc.description.abstractGlobal 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.eng
dc.formatapplication/pdfes_AR
dc.language.isoenges_AR
dc.publisherElsevier
dc.rightsinfo:eu-repo/semantics/restrictedAccesses_AR
dc.sourceRemote Sensing Applications: Society and Environment 23 : Article 100589. (August 2021)es_AR
dc.subjectPrecipitación Atmosféricaes_AR
dc.subjectTeledetecciónes_AR
dc.subjectMeteorologíaes_AR
dc.subjectPrecipitationeng
dc.subjectRemote Sensingeng
dc.subjectMeteorologyeng
dc.subject.otherRegión Pampeanaes_AR
dc.subject.otherTaylor Diagrames_AR
dc.titlePrecipitation estimations based on remote sensing compared with data from weather stations over agricultural region of Argentina pampases_AR
dc.typeinfo:ar-repo/semantics/artículoes_AR
dc.typeinfo:eu-repo/semantics/articlees_AR
dc.typeinfo:eu-repo/semantics/publishedVersiones_AR
dc.description.origenEEA Anguiles_AR
dc.description.filFil: Ovando, Gustavo. Universidad Nacional de Córdoba. Facultad de Ciencias Agropecuarias; Argentinaes_AR
dc.description.filFil: Sayago, Silvina. Universidad Nacional de Córdoba. Facultad de Ciencias Agropecuarias; Argentinaes_AR
dc.description.filFil: Bellini Saibene, Yanina. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Anguil; Argentinaes_AR
dc.description.filFil: Belmonte, María Laura. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Anguil; Argentinaes_AR
dc.description.filFil: Bocco, Monica. Universidad Nacional de Córdoba. Facultad de Ciencias Agropecuarias; Argentinaes_AR
dc.subtypecientifico


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