The long-term trends of global land precipitation in GFDL's CM4 and ESM4 climate models
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The long-term trends of global land precipitation in GFDL's CM4 and ESM4 climate models

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  • Journal Title:
    Journal of Climate
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  • Description:
    Historical precipitation and temperature trends and variations over global land regions are compared with simulations of two climate models focusing on grid points with substantial observational coverage from the early 20th century. Potential mechanisms for the differences between modeled and observed trends are investigated using subsets of historical forcings, including ones using only anthropogenic greenhouse gases or aerosols, and simulations forced with the observed sea surface temperature and sea ice distribution. For century-scale (1915–2014) precipitation trends, underestimated increasing or unrealistic decreasing trends are found in the models over the extratropical Northern Hemisphere. The temporal evolution of key discrepancies between the observations and simulations indicates: (1) for averages over 15°–45° N, while there is not a significant trend in observations, both models simulate reduced precipitation from 1940 to 2014; (2) for 45°–80° N: observations suggest sizable precipitation increases while models do not show a significant increase particularly during ~1950–1980. The timing of differences between models and observations suggesting a key role for aerosols in these dry trend biases over the extratropical Northern Hemisphere. (3) for 15°S–15°N, the observed multidecadal decrease over tropical west Africa (1950-1980) is roughly only captured by simulations forced with observed sea surface temperature; and (4) in the all-forcing runs, the model with higher global climate sensitivity, simulates increasing trends of temperature and precipitation over lands north of 45°N, that are significantly stronger than the lower-sensitivity model and more consistent with the observed increases. Thus, underestimated greenhouse gas-induced warming—particularly in the lower sensitivity model—may be another important factor, besides aerosols, contributing to the modeled biases in precipitation trends.
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    Journal of Climate (2023)
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  • ISSN:
    0894-8755;1520-0442;
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