Work

Using a 10-Year Radar Archive for Nowcasting Precipitation Growth and Decay: A Probabilistic Machine Learning Approach

Year: 2019

Type: article

Source: Weather and Forecasting

DOI: 10.1175/waf-d-18-0206.1

Authors: Loris Foresti, Ioannis V. Sideris, Daniele Nerini, Lea Beusch, Urs Germann

Institutions: Federal Office of Meteorology and Climatology MeteoSwiss, ETH Zurich, Institute for Atmospheric and Climate Science

Language: English

Topic: Precipitation Measurement and Analysis

Subfield: Atmospheric Science

Field: Earth and Planetary Sciences

Domain: Physical Sciences

Open Access status: closed

Funder: Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung

Award: Precipitation attractor from radar and satellite data archives and implications for seamless very short-term forecasting

OpenAlex ID: W2963511153

FWCI: 3.345

Cites: 95

Cited by: 60

Related to: 10