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Current‐generation climate models project that Africa will warm by up to 5°C in the coming century, severely stressing African populations. Past and ongoing work indicates, however, that the models used to create these projections do not match proxy records of past temperature in Africa during the mid‐Holocene (MH), raising concerns that their future projections may house large uncertainties. Rather than reproducing proxy‐based reconstructions of MH warming relative to the Pre‐Industrial (PI), models instead simulate MH temperatures very similar to or slightly colder than the PI. This data‐model mismatch could be due to a variety of factors, including biases in model surface energy budgets or inaccurate representation of the feedbacks between temperature and hydrologic change during the "Green Sahara." We focus on the differences among model simulations in the Paleoclimate Modeling Intercomparison Project Phases 3 and 4 (PMIP3 and PMIP4), examining surface temperature and energy budgets to investigate controls on temperature and the potential model sources of this paleoclimate data‐model mismatch. Our results suggest that colder conditions simulated by PMIP3 and PMIP4 models during the MH are in large part due to the joint impacts of feedback uncertainties in response to increased precipitation, a strengthened West African Monsoon (WAM) in the Sahel, and the Green Sahara. We extend these insights into suggestions for model physics and boundary condition changes, and discuss implications for the accuracy of future climate model projections over Africa. Key Points: We evaluate the simulation of African air temperatures in Paleoclimate Modeling Intercomparison Project Phases 3 and 4 simulations of the mid‐HoloceneEnergy balance decomposition analyses indicate the hydrologic cycle plays a key role in causing mid‐Holocene cooling in model simulations"Green Sahara" experiments show that dust and vegetation affect simulated temperatures, revealing pathways for refining model simulations [ABSTRACT FROM AUTHOR]

Reliable precipitation simulation over the Tibetan Plateau (TP) remains a challenge, manifested by a prominent systematic wet bias in the warm season. Previous studies have generally neglected the potential linkage between surface radiation energy budget and precipitation bias. Prevalent scattered cumulus and thunderstorms over the TP in summer strongly influence surface radiation. A cloud fraction scheme considering subgrid temperature and humidity fluctuations is implemented in the WRF model and tested for a month‐long simulation. It is found that the scheme better reproduces the surface solar radiation compared to a default cloud fraction scheme in the WRF model. Using abundant surface observations, we find that overestimation of the downward surface shortwave radiation (DSSR) would lead to wet bias. DSSR overestimation contributes to higher surface temperature and larger evaporation and enhanced atmospheric instability, which favor more simulated convective precipitation. The study suggests that a better simulation of clouds and surface radiation would benefit precipitation simulation over the plateau. Plain Language Summary: Summer precipitation over the Tibetan Plateau (TP) is generally overestimated in general circulation models as well as regional weather forecasts and climate models. The prevailing "popcorn‐like" clouds over the TP in summer would strongly impact surface radiation. Considering the potential linkage between surface radiation energy budget and precipitation bias, a statistical cloud fraction and subgrid condensation scheme (GS‐PDF scheme) is implemented in the WRF model and tested for a month‐long simulation. The GS‐PDF scheme better captures clouds over the TP with more mid‐low cloud water (ice) than the default Xu‐Randall scheme. Increased mid‐low cloud water in the GS‐PDF scheme reduced simulated downward surface shortwave radiation, reduced simulated surface temperatures, atmospheric instabilities and convective precipitation, leading to alleviated wet bias over the TP. This study suggests that better simulations of cloud and surface radiation would be beneficial for simulations of hydrological cycles over the TP. Key Points: A new cloud macrophysics scheme considering subgrid temperature and humidity fluctuations is implemented in the WRF modelThe new macrophysics scheme reduced simulated downward surface shortwave radiation, surface temperatures and atmospheric instabilitiesA better simulation of clouds and surface radiation would benefit precipitation simulation over the Tibetan Plateau [ABSTRACT FROM AUTHOR]