Comparison of Different Quantitative Precipitation Estimation Methods Based on a Severe Rainfall Event in Tuscany, Italy, November 2023

被引：0

作者：

Biondi, Alessio ^{[1
]}

Facheris, Luca ^{[1
]}

Argenti, Fabrizio ^{[1
]}

Cuccoli, Fabrizio ^{[2
]}

机构：

[1] Univ Florence, Dept Informat Engn, Via Santa Marta 3, I-50139 Florence, Italy

[2] Interuniv Natl Consortium Telecommun CNIT, Radar & Surveillance Syst RASS Lab, Glleria G B Gerace 14, I-56124 Pisa, Italy

来源：

REMOTE SENSING | 2024年 / 16卷 / 21期

关键词：

weather radar; rain gauge; quantitative precipitation estimation (QPE); rainfall; data fusion; merging methods; SPATIAL INTERPOLATION; MERGING METHODS; RADAR; VARIABILITY;

D O I：

10.3390/rs16213985

中图分类号：

X [环境科学、安全科学];

学科分类号：

08 ; 0830 ;

摘要：

Accurate quantitative precipitation estimation (QPE) is fundamental for a large number of hydrometeorological applications, especially when addressing extreme rainfall phenomena. This paper presents a comprehensive comparison of various rainfall estimation methods, specifically those relying on weather radar data, rain gauge data, and their fusion. The study evaluates the accuracy and reliability of each method in estimating rainfall for a severe event that occurred in Tuscany, Italy. The results obtained confirm that merging radar and rain gauge data outperforms both individual approaches by reducing errors and improving the overall reliability of precipitation estimates. This study highlights the importance of data fusion in enhancing the accuracy of QPE and also supports its application in operational contexts, providing further evidence for the greater reliability of merging methods.

引用

页数：19

共 47 条

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