An Adaptive Rainfall Estimation Algorithm for Dual-Polarization Radar

Dual-polarization radar provides information about precipitation microphysics through drop size distribution and hydrometeor classification, and, therefore, can produce improvement in quantitative precipitation estimation. Rainfall relations combination is an optimization algorithm; however, optimal...

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Bibliographic Details
Published in:IEEE geoscience and remote sensing letters 2022, Vol.19, p.1-5
Main Authors: Kou, Leilei, Tang, Jiaqi, Wang, Zhixuan, Jiang, Yinfeng, Chu, Zhigang
Format: Article
Language:English
Subjects:
Adaptive algorithms
Adaptive rainfall algorithm
Algorithms
Atmospheric precipitations
C band
Classification
Classification algorithms
Data models
Drop size
Drop size distribution
Dual polarization radar
Estimation
Forecasting
Hydrometeors
logistic regression model
Logistics
Logit models
Microphysics
Neural networks
Optimization
Particle size distribution
Polarization
Precipitation
Precipitation estimation
quantitative precipitation estimation (QPE)
Radar
Radar data
Radar polarimetry
Radar rainfall
Rain
Rain gauges
Rainfall
Rainfall estimation
Regression models
Size distribution
Tornadoes
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Summary:Dual-polarization radar provides information about precipitation microphysics through drop size distribution and hydrometeor classification, and, therefore, can produce improvement in quantitative precipitation estimation. Rainfall relations combination is an optimization algorithm; however, optimally selecting the rainfall relation is challenging in dual-polarization rainfall estimation. In this study, an adaptive rainfall algorithm is developed using a logistic regression model to guide the choice of the optimal radar rainfall relation. The logistic model is established according to the matched dual-polarization radar data and rain gauge data. Only liquid particles are considered for the rainfall estimation determined by the hydrometeor classification of dual-polarization radar, and the polarimetric rainfall relations are obtained with a neural network algorithm based on the disdrometer data. The proposed algorithm is validated with C-band dual-polarization radar data, and the results show that the adaptive algorithm outperforms the single rainfall relation and conventional combination algorithm.
ISSN:1545-598X
1558-0571
DOI:10.1109/LGRS.2022.3143118