A review of current approaches to radar-based quantitative precipitation forecasts
Sara Liguori, Miguel A. Rico‐Ramirez
Abstract
Sara Liguori, Miguel A. Rico‐Ramirez
Abstract
Short-term radar-based forecasts of precipitation can be achieved through the implementation of nowcasting models, essentially based on the rainfall extrapolation from a series of consecutive radar scans. Recent advances in this field include the development of hybrid models, aimed at merging the benefits of radar nowcasting and numerical weather prediction models, and probabilistic systems, aimed at addressing the sources of uncertainty in radar rainfall forecasts by means of ensembles. This paper provides an overview of radar nowcasting methods and approaches, with an emphasis on recent developments in this field.
OpenAlex reports 48 citations for this work. Citation counts describe recorded attention and do not establish research quality.
A contribution statement is not available in the OpenAlex record.
Method details are not available in the OpenAlex metadata.
Findings are not separately available in the OpenAlex metadata.
Limitations are not available in the OpenAlex metadata.
Application details are not available in the OpenAlex metadata.
Short-term radar-based forecasts of precipitation can be achieved through the implementation of nowcasting models, essentially based on the rainfall extrapolation from a series of consecutive radar scans. Recent advances in this field include the development of hybrid models, aimed at merging the benefits of radar nowcasting and numerical weather prediction models, and probabilistic systems, aimed at addressing the sources of uncertainty in radar rainfall forecasts by means of ensembles. This paper provides an overview of radar nowcasting methods and approaches, with an emphasis on recent developments in this field.
Key concepts: Nowcasting, Radar, Extrapolation, Precipitation, Quantitative precipitation forecast, Probabilistic logic, Quantitative precipitation estimation, Meteorology