TY - JOUR
T1 - Assessment of extreme rainfall estimates from satellite-based
T2 - Regional analysis
AU - Araujo Palharini, Rayana Santos
AU - Vila, Daniel Alejandro
AU - Rodrigues, Daniele Torres
AU - Palharini, Rodrigo Cassinelli
AU - Mattos, Enrique Vieira
AU - Pedra, George Ulguim
N1 - Publisher Copyright:
© 2021
PY - 2021/8
Y1 - 2021/8
N2 - Excessive rain may cause several problems for society. Understanding the behaviour of extreme rainfall and quantifying it in an assertive manner is important for whole society. The purpose of this work is to evaluate the ability of satellite precipitation products to detect the extreme rainfall over different regions of Brazil. The products evaluated in this investigation were from Frequent Rainfall Observations on GridS (FROGS) database. The results show that, each region of Brazil is characterized by extremes of rain with different intensities. The regions that presented the highest values are south and north regions of Brazil with values around 125.0 mm/day. In both regions, the GSMAP product (with rain gauges adjustments) have better performance, as shown in the metrics for the south and north regions where bias = −1.20 mm/day and −6.49 mm/day; r = 0.65 and 0.50; std = 10.15 mm/day and 10.63 mm/day; rmse = 9.58 mm/day and 13.16 mm/day respectively. On the other hand, the regions with the lowest intensities are the northeastern region, inland and coast, presented frequent extreme values of approximately 35.0 mm/day. At these regions, both versions of product 3B42RT v7.0 demonstrated a better performance, as demonstrated in the metrics for inland and coast northeastern regions, bias = 2.82 mm/day and −2.94 mm/day; r = 0.18 and 0.30; std = 8.53 mm/day and 6.97 mm/day; rmse = 14.75 mm/day and 7.03 mm/day, respectively. It is worth mentioning that the precipitation values found in this work do not necessarily cause disasters or generate impacts in the analyzed regions, they were considered extreme from a statistical point of view, considering the analyzed database.
AB - Excessive rain may cause several problems for society. Understanding the behaviour of extreme rainfall and quantifying it in an assertive manner is important for whole society. The purpose of this work is to evaluate the ability of satellite precipitation products to detect the extreme rainfall over different regions of Brazil. The products evaluated in this investigation were from Frequent Rainfall Observations on GridS (FROGS) database. The results show that, each region of Brazil is characterized by extremes of rain with different intensities. The regions that presented the highest values are south and north regions of Brazil with values around 125.0 mm/day. In both regions, the GSMAP product (with rain gauges adjustments) have better performance, as shown in the metrics for the south and north regions where bias = −1.20 mm/day and −6.49 mm/day; r = 0.65 and 0.50; std = 10.15 mm/day and 10.63 mm/day; rmse = 9.58 mm/day and 13.16 mm/day respectively. On the other hand, the regions with the lowest intensities are the northeastern region, inland and coast, presented frequent extreme values of approximately 35.0 mm/day. At these regions, both versions of product 3B42RT v7.0 demonstrated a better performance, as demonstrated in the metrics for inland and coast northeastern regions, bias = 2.82 mm/day and −2.94 mm/day; r = 0.18 and 0.30; std = 8.53 mm/day and 6.97 mm/day; rmse = 14.75 mm/day and 7.03 mm/day, respectively. It is worth mentioning that the precipitation values found in this work do not necessarily cause disasters or generate impacts in the analyzed regions, they were considered extreme from a statistical point of view, considering the analyzed database.
KW - Brazil
KW - Extreme rainfall
KW - FROGS dataset
KW - Satellite estimates
UR - https://www.scopus.com/pages/publications/85112231287
U2 - 10.1016/j.rsase.2021.100603
DO - 10.1016/j.rsase.2021.100603
M3 - Article
AN - SCOPUS:85112231287
SN - 2352-9385
VL - 23
JO - Remote Sensing Applications: Society and Environment
JF - Remote Sensing Applications: Society and Environment
M1 - 100603
ER -