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

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.

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Publication Details

Journal
Geophysical Research Letters
Published
2026-01-29
DOI
https://doi.org/10.1029/2025gl118712
Primary Topic
Climate variability and models
Type
article
Field-Weighted Citation Impact
0.00

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article

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

Bosong Zhang, Thomas R. Knutson, Wengui Liang, Dong Wenhao et al.
Geophysical Research Letters
Climate variability and models
article

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

Bosong Zhang, Thomas R. Knutson, Wengui Liang, Dong Wenhao, Ming Zhao, Zhihong Tan
article en

Abstract

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.

Geophysical Research LettersVol. 53(3)
Louisiana State University (US), NOAA Geophysical Fluid Dynamics Laboratory (US), Princeton University (US), Tsinghua University (CN)
U.S. Department of Commerce, National Oceanic and Atmospheric Administration
Climate action
Openalex Percentile: Top 80%
Climate variability and models
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