Dec 20, 2022 · The relationships between rain rates and over 15 variables derived from data products of dual-polarimetric weather radar were investigated and ...
Dec 20, 2022 · The developed ML regression models could be used to predict the mean rain rate and top 10% mean rain rate of an MCS storm cell.
To improve ML model performance, it is essential first and foremost to quantify the importance of radar variables and identify pertinent predictors of rainfall ...
Jan 10, 2023 · The main objective of the study was to use ML regression methods to quantify the relative importance of radar variables for nowcasting heavy ...
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We investigated the relationship between rainfall rates and over 15 products from dual-polarimetric radar for each MCS type.
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Relative Importance of Radar Variables for Nowcasting Heavy Rainfall: A Machine Learning Approach · Yi WangSeung Hee Kim +4 authors. M. Kafatos. Environmental ...
A deep neural network using radar reflectivity and ERA5 reanalysis data was proposed to improve precipitation nowcasting. •. Nowcasting performance of deep ...
Missing: Relative | Show results with:Relative
Jan 19, 2024 · This work presents the importance of polarimetric variables as an additional data source for nowcasting thunderstorm hazards using an existing neural network ...
This work is part of a larger study devoted to nowcasting rain and wind speed in the area of Malpensa airport by merging different datasets.
Nov 1, 2023 · Precise and timely rainfall nowcasting plays a critical role in ensuring public safety amid disasters triggered by heavy precipitation.