Forecast combinations have flourished remarkably in the forecasting community and, in
recent years, have become part of mainstream forecasting research and activities …

Over the past decades, the scientific community has made significant efforts to simulate
flooding conditions using a variety of complex physically based models. Despite all …

The Weather Research and Forecasting (WRF) Model is an atmospheric modeling system
designed for both research and numerical weather prediction. WRF is an open-source …

WeatherBench 2 is an update to the global, medium‐range (1–14 days) weather forecasting
benchmark proposed by (Rasp et al., 2020, https://doi. org/10.1029/2020ms002203) …

Skillful subseasonal forecasts are crucial for various sectors of society but pose a grand
scientific challenge. Recently, machine learning-based weather forecasting models …

综合论述了近年来已在国际上引起高度重视的新一代动力随机预报方法———集合预报.
随着计算机技术的迅猛发展和由于大气初值和数值模式中物理过程存在着不确定性的事实 …

Since its discovery in the early 1970s, the crucial role of the Madden‐Julian Oscillation
(MJO) in the global hydrological cycle and its tremendous influence on high‐impact climate …

Predictions of the Earth system, such as weather forecasts and climate projections, require
models informed by observations at many levels. Some methods for integrating models and …

Variational and ensemble methods have been developed separately by various research
and development groups and each brings its own benefits to data assimilation. In the last …

A probabilistic forecast takes the form of a predictive probability distribution over future
quantities or events of interest. Probabilistic forecasting aims to maximize the sharpness of …