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Effective training strategies for deep-learning-based precipitation nowcasting and estimation [PDF]

open access: yesComputers and Geosciences, 2022
Deep learning has been successfully applied to precipitation nowcasting. In this work, we propose a pre-training scheme and a new loss function for improving deep-learning-based nowcasting.
Kijung Shin, Kyuhan Lee, Seok-Woo Son
exaly   +2 more sources
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Verification of the radar precipitation nowcasting

Hydrometeorological research and forecasting, 2023
The application of the Fraction Skill Score (FSS) to the radar nowcasting of precipitation fields is considered. The main feature of the method is that the quality is estimated not at the points (or cells) of the fields, but in their neighborhoods. Verification of field forecasts acquires a probabilistic character, due to which the well-known “double ...
A.V Muravev .., D.B. Kiktev, A.V Smirnov
openaire   +1 more source

Nowcasting of precipitation systems

Reviews of Geophysics, 1989
Digital remotely sensed observations of the atmosphere, particularly from radars and satellites, have become increasingly available over the last 15 years. Together with developments in computer technology this has stimulated the design and operation of a variety of systems to exploit these data in weather forecasting.
K. A. Browning, C. G. Collier
openaire   +1 more source

Quantitative Precipitation Nowcasting: A Lagrangian Pixel-Based Approach [PDF]

open access: yesAtmospheric Research, 2012
Short-term high-resolution precipitation forecasting has important implications for navigation, flood forecasting, and other hydrological and meteorological concerns.
Soroosh Sorooshian   +2 more
exaly   +3 more sources

Nowcasting precipitation — a proposal for a way forward

Journal of Hydrology, 2000
Abstract There is little doubt that hybrid mesoscale model and image extrapolation systems will eventually become widespread for the nowcasting of precipitation for hydrology and aviation safety. Arguably the final forecast output that is required for these applications needs to be probabilistic in nature, therefore appropriate forecast schemes ...
G L Austin
exaly   +2 more sources

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