THE INFLUENCE OF THE REMOTELY SENSED RAINFALL PRODUCTS’ SPATIAL RESOLUTION TO UNMASK EXTREME EVENTS IN NORTHEAST BRAZIL

This work presents the influence of the spatial resolution on precipitation samples to understand extreme events in the Agreste region of Pernambuco, northeast of Brazil. Among the materials used, the following sources of precipitation data (1998 to 2019) can be cited: The Tropical Rainfall Measurin...

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Detalles Bibliográficos
Autores: Nova, Raquel Arcoverde Vila, Gonçalves, Rodrigo Mikosz, Ferreira, Lígia Albuquerque de Alcântara, Lima, Fábio Vinícius Marley Santos
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2022
País:Brasil
Institución:Universidade Federal do Paraná (UFPR)
Repositorio:Boletim de Ciências Geodésicas
Idioma:inglés
OAI Identifier:oai:ojs.pkp.sfu.ca:article/84201
Acceso en línea:https://revistas.ufpr.br/bcg/article/view/84201
Access Level:acceso abierto
Palabra clave:Precipitation
Climate extremes
TRMM
CRU
SPI.
Descripción
Sumario:This work presents the influence of the spatial resolution on precipitation samples to understand extreme events in the Agreste region of Pernambuco, northeast of Brazil. Among the materials used, the following sources of precipitation data (1998 to 2019) can be cited: The Tropical Rainfall Measuring Mission (TRMM), the Climatic Research Unit (CRU), and weather stations. In the process of validating the precipitation time series with the weather stations, the TRMM data showed a strong Pearson correlation (0.86 - 0.90) and the CRU data a moderate one (0.71 - 0.76). The relative bias (RB) and the standard deviation of observation ratio (RSR) were also calculated to identify the data’s trend, which showed an overestimation for both sources. The extreme events were identified through the calculation of the Standardized Precipitation Index (SPI), where the TRMM with strong correlation (0.80 - 0.91) obtained a better performance than the CRU data. The TRMM data were selected to understand the extreme drought events in the study area, where the cities with altitudes above 500m obtained maximum values of probability of occurrence with 19%. Conversely, for extreme humidity events, the maximum was 14% for those with altitudes below 200m.