JOURNAL ARTICLE

Development of precipitation nowcasting method using geostationary satellite data

A.I. AndreevN.I. PerervaM. O. Kuchma

Year: 2020 Journal:   Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa Vol: 17 (6)Pages: 18-22

Abstract

The paper considers the development of a model for precipitation field nowcasting using the data obtained from the Himawari-8 satellite and a GFS numerical forecast model.The nowcasting method employs a convolutional and recurrent neural network architecture.A peculiarity of the developed model is a possibility to make a forecast using no ground-based meteorological radars data.The authors present preliminary research results as exemplified by the precipitation field nowcasting for a 30-minute period and the 60-minute forecast of the cloud cover optical depth distribution.Finally, the paper outlines the areas for further research with the account to the identified drawbacks of the existing forecasting algorithm software implementation.

Keywords:
Nowcasting Geostationary orbit Meteorology Precipitation Satellite Field (mathematics) Quantitative precipitation forecast Remote sensing Computer science Weather forecasting Environmental science Geography Engineering Aerospace engineering

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Topics

Meteorological Phenomena and Simulations
Physical Sciences →  Earth and Planetary Sciences →  Atmospheric Science
Atmospheric aerosols and clouds
Physical Sciences →  Environmental Science →  Global and Planetary Change
Climate variability and models
Physical Sciences →  Environmental Science →  Global and Planetary Change
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