Radar-based rainfall information has been widely used in hydrological and meteorological
applications, as it provides data with a high spatial and temporal resolution that improve …

Hydrology requires accurate and reliable rainfall input. Because of the strong spatial and
temporal variability of precipitation, estimation of spatially distributed rain rates is …

Extreme precipitation is a considerable contributor to meteorological disasters and there is a
great need to mitigate its socioeconomic effects through skilful nowcasting that has high …

强对流天气预报业务包括监测, 分析, 预报, 预警和检验等方面. 对流初生识别,
对流系统强度识别和对流天气类型识别等监测技术取得新进展, 综合多源资料的监测技术已应用 …

Pysteps is an open-source and community-driven Python library for probabilistic
precipitation nowcasting, that is, very-short-range forecasting (0–6 h). The aim of pysteps is …

Quantitative precipitation nowcasting (QPN) has become an essential technique in various
application contexts, such as early warning or urban sewage control. A common heuristic …

Weather radar plays an important role in accurate weather monitoring and modern weather
forecasting, as it can provide timely and refined weather forecasts for the public and for …

Deep learning is emerging as a powerful tool in scientific applications, such as radar-based
convective storm nowcasting. However, it is still a challenge to extend the application of a …

Weather radar has become an invaluable tool for monitoring rainfall and studying its link to
hydrological response. However, when it comes to accurately measuring small-scale rainfall …

Abstract The Geostationary Operational Environmental Satellite (GOES)-R convective
initiation (CI) algorithm predicts CI in real time over the next 0–60 min. While GOES-R CI has …