Advances in numerical weather prediction represent a quiet revolution because they have
resulted from a steady accumulation of scientific knowledge and technological advances …

During recent years, urban building energy modeling has become known as a novel
approach for identification, support and improvement of sustainable urban development …

Weather forecasting is important for science and society. At present, the most accurate
forecast system is the numerical weather prediction (NWP) method, which represents …

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) …

In this paper, we present Pangu-Weather, a deep learning based system for fast and
accurate global weather forecast. For this purpose, we establish a data-driven environment …

Weather forecasting is a fundamental problem for anticipating and mitigating the impacts of
climate change. Recently, data-driven approaches for weather forecasting based on deep …

It is well-known that numerical weather prediction (NWP) models require considerable
computer power to solve complex mathematical equations to obtain a forecast based on …

Climate projections continue to be marred by large uncertainties, which originate in
processes that need to be parameterized, such as clouds, convection, and ecosystems. But …

Mathematical modeling of atmospheric composition is a formidable scientific and
computational challenge. This comprehensive presentation of the modeling methods used …

Precipitation process is generally considered to be poorly represented in numerical
weather/climate models. Statistical downscaling (SD) methods, which relate precipitation …