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 …

We present the first ever real‐time numerical weather prediction system with 30‐s update
cycles at a 500‐m grid spacing for the prediction of convective precipitation in the …

Data assimilation is crucial in a wide range of applications, but it often faces challenges such
as high computational costs due to data dimensionality and incomplete understanding of …

Frozen hydrometeors are found in a huge range of shapes and sizes, with variability on
much smaller scales than those of typical model grid boxes or satellite fields of view. Neither …

Prediction of dendrite growth during alloy solidification is important for controlling the
microstructures and mechanical properties of alloys. To this end, quantitative phase-field …

To reduce the uncertainty estimation of clouds and improve the forecast of surface
shortwave radiation (SSR) over the Tibetan Plateau, a new cloud assimilation system is …

Direct assimilation of Dual‐frequency Precipitation Radar (DPR) data of the Global
Precipitation Measurement (GPM) core satellite is challenging mainly due to its long …

The tropical cyclone (TC) surface-exchange coefficients of enthalpy (C k) and momentum (C
d) at high wind speeds have been notoriously challenging to estimate. This difficulty arises …

Data assimilation is a relevant framework to merge a dynamical model with noisy
observations. When various models are in competition, the question is to find the model that …

Determining physical process parameters in atmospheric models is critical to obtaining
accurate weather and climate simulations; estimating optimal parameters is essential for …