Lower Tropospheric Processes: A Control on the Global Mean Precipitation Rate.

The spread in global mean precipitation among climate models is explored in two ensembles using the complementary perspectives of surface evaporation and energy budgets. Models with higher global mean precipitation have stronger oceanic evaporation, driven by drier near‐surface air. The drier surface conditions occur alongside increases in near‐surface temperature and moisture at 925 hPa, which point to stronger boundary layer mixing. Correlations suggest that the degree of lower tropospheric mixing explains 18%–49% of the intermodel precipitation variance. To test this hypothesis, the degree of mixing is indirectly varied in a single‐model experiment by adjusting the relative humidity threshold that controls low‐cloud fraction. Indeed, increasing lower tropospheric mixing results in more global mean precipitation. Energetically, increased precipitation rates are associated with more downwelling longwave radiation to the surface and weaker sensible heat fluxes. These results highlight how lower‐tropospheric processes must be better constrained to reduce the precipitation discrepancy among climate models. Plain Language Summary: Climate models exhibit a spread in their simulation of the present‐day global mean precipitation rate; a fundamental climate statistic whose spread is surprisingly understudied. This 13% spread compares with the expected change in the global mean precipitation rate in a warmer climate scenario. Complex precipitation physics can make understanding what processes control the global mean precipitation rate across climate models inherently difficult. We find that the degree of mixing within the lower 1‐km of the atmosphere (lower‐tropospheric mixing) controls a large fraction of the spread in global mean precipitation across models. We also show linkages between the lower tropospheric mixing and the energy budget framework that is typically used to understand the global mean precipitation rate. Our results highlight a local scale process (mixing) that controls and impacts a global scale climate statistic (global mean precipitation). They also suggest that future attempts to bridge satellite observations and climate model output can potentially help reduce the existing spread and bias among climate models. Key Points: Fifth Coupled Model Intercomparison Project Atmospheric Model Intercomparison Project simulations disagree on the magnitude of the present‐day global mean precipitation rate by 13%Lower tropospheric mixing explains as much as 49% of the intermodel varianceMost (up to 75%) of the spread in column atmospheric energy happens at the surface [ABSTRACT FROM AUTHOR]