Zobrazeno 1 - 3
of 3
pro vyhledávání: '"Marta Pendesini"'
Autor:
Gabriele Franch, Daniele Nerini, Marta Pendesini, Luca Coviello, Giuseppe Jurman, Cesare Furlanello
Publikováno v:
Atmosphere, Vol 11, Iss 3, p 267 (2020)
One of the most crucial applications of radar-based precipitation nowcasting systems is the short-term forecast of extreme rainfall events such as flash floods and severe thunderstorms. While deep learning nowcasting models have recently shown to pro
Externí odkaz:
https://doaj.org/article/489c9a7c0efc4c7ba90b7061a28d7e0c
Autor:
Marta Pendesini, Giuseppe Jurman, Valerio Maggio, Cesare Furlanello, Gabriele Franch, Luca Coviello
Publikováno v:
Scientific Data
Franch, G, Maggio, V, Coviello, L, Pendesini, M, Jurman, G & Furlanello, C 2020, ' TAASRAD19, a high-resolution weather radar reflectivity dataset for precipitation nowcasting ', Scientific Data, vol. 7, 234 (2020) . https://doi.org/10.1038/s41597-020-0574-8
Scientific Data, Vol 7, Iss 1, Pp 1-13 (2020)
Franch, G, Maggio, V, Coviello, L, Pendesini, M, Jurman, G & Furlanello, C 2020, ' TAASRAD19, a high-resolution weather radar reflectivity dataset for precipitation nowcasting ', Scientific Data, vol. 7, 234 (2020) . https://doi.org/10.1038/s41597-020-0574-8
Scientific Data, Vol 7, Iss 1, Pp 1-13 (2020)
We introduce TAASRAD19, a high-resolution radar reflectivity dataset collected by the Civil Protection weather radar of the Trentino South Tyrol Region, in the Italian Alps. The dataset includes 894,916 timesteps of precipitation from more than 9 yea
Publikováno v:
Remote Sensing; Volume 11; Issue 24; Pages: 2922
The use of analog-similar weather patterns for weather forecasting and analysis is an established method in meteorology. The most challenging aspect of using this approach in the context of operational radar applications is to be able to perform a fa