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 …

In the atmosphere, microphysics refers to the microscale processes that affect cloud and
precipitation particles and is a key linkage among the various components of Earth's …

This article reviews how precipitation microphysics processes are observed in dual-
polarization radar observations. These so-called “fingerprints” of precipitation processes are …

Machine learning (ML) algorithms are powerful tools to build models of clouds and climate
that are more faithful to the rapidly increasing volumes of Earth system data than commonly …

Projecting climate change is a generalization problem: We extrapolate the recent past using
physical models across past, present, and future climates. Current climate models require …

Extreme precipitation concerning typhoons brings great losses to coastal cities every year.
How to accurately describe the natural cloud and precipitation processes in model remains …

Parameterizations of unresolved turbulent processes often compromise the fidelity of large‐
scale ocean models. In this work, we argue for a Bayesian approach to the refinement and …

The small‐scale microphysical processes governing the formation of precipitation particles
cannot be resolved explicitly by cloud resolving and climate models. Instead, they are …

The raindrop size distribution (DSD) is vital for applications such as quantitative precipitation
estimation, understanding microphysical processes, and validation/improvement of two …

Accelerated progress in climate modeling is urgently needed for proactive and effective
climate change adaptation. The central challenge lies in accurately representing processes …