Most climate models in phase 6 of the Coupled Model Intercomparison Project (CMIP6) still suffer pronounced warm and dry summer biases in the central United States (CUS), even in high-resolution simulations. We found that the cloud base definition in the cumulus parameterization was the dominant factor determining the spread of the biases among models and those defining cloud base at the lifting condensation level (LCL) performed the best. To identify the underlying mechanisms, we developed a physically based analytical bias model (ABM) to capture the key feedback processes of land–atmosphere coupling. The ABM has significant explanatory power, capturing 80% variance of temperature and precipitation biases among all models. Our ABM analysis via counterfactual experiments indicated that the biases are attributed mostly by surface downwelling longwave radiation errors and second by surface net shortwave radiation errors, with the former 2–5 times larger. The effective radiative forcing from these two errors as weighted by their relative contributions induces runaway temperature and precipitation feedbacks, which collaborate to cause CUS summer warm and dry biases. The LCL cumulus reduces the biases through two key mechanisms: it produces more clouds and less precipitable water, which reduce radiative energy input for both surface heating and evapotranspiration to cause a cooler and wetter soil; it produces more rainfall and wetter soil conditions, which suppress the positive evapotranspiration–precipitation feedback to damp the warm and dry bias coupling. Most models using non-LCL schemes underestimate both precipitation and cloud amounts, which amplify the positive feedback to cause significant biases.
This content will become publicly available on November 3, 2024
Radiative feedbacks govern the Earth's climate sensitivity and elucidate the geographic patterns of climate change in response to a carbon‐dioxide forcing. We develop an analytical model for patterned radiative feedbacks that depends only on changes in local surface temperature. The analytical model combines well‐known moist adiabatic theory with the radiative‐advective equilibrium that describes the energy balance in high latitudes. Together with a classic analytical function for surface albedo, all of the non‐cloud feedbacks are represented. The kernel‐based analytical feedbacks reproduce the feedbacks diagnosed from global climate models at the global, zonal‐mean, and seasonal scales, including in the polar regions, though with less intermodel spread. The analytical model thus provides a framework for a quantitative understanding of radiative feedbacks from simple physics, independent of the detailed atmospheric and cryospheric responses simulated by comprehensive climate models.
more » « less- Award ID(s):
- 1753034
- NSF-PAR ID:
- 10472719
- Publisher / Repository:
- American Geophysical Union
- Date Published:
- Journal Name:
- Geophysical Research Letters
- Volume:
- 50
- Issue:
- 21
- ISSN:
- 0094-8276
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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