Work

Confronting Historical Precipitation Trends in Models With Observations: Forced Signal and Atmospheric Internal Variability

Year: 2026

Type: article

Abstract: Future precipitation projections rely heavily on climate models, underscoring the need to evaluate their ability to simulate historical precipitation changes. Using multiple atmospheric models and ensemble simulations, we estimate the forced signals driven by sea surface warming and the direct effects of greenhouse gases and aerosols, as well as the atmospheric internal variability in precipitation trends since 1980. We find that forced precipitation trends are generally consistent across models, while atmospheric internal variability significantly influences regional patterns. Additionally, a few model members can reasonably well reproduce the observed pattern of precipitation trends. We highlight some regional wetting and drying are likely driven by forcings rather than the atmospheric internal variability. Zonal‐mean trends over land reveal a “wet gets wetter, dry gets drier” paradigm in the Northern Hemisphere, while the Southern Hemisphere shows drying near 45°S associated with jet stream shifts. These results help improve our understanding of historical precipitation changes.

Source: Geophysical Research Letters

DOI: 10.1029/2025gl118712

Authors: Wengui Liang, Ming Zhao, Zhihong Tan, Thomas Knutson, Wenhao Dong, Bosong Zhang

Institutions: Louisiana State University, Princeton University, NOAA Geophysical Fluid Dynamics Laboratory, Tsinghua University

Language: English

Topic: Climate variability and models

Subfield: Global and Planetary Change

Field: Environmental Science

Domain: Physical Sciences

SDG: Climate action

Open Access status: gold

Estimated APC paid: $3,190