A Process-Oriented Diagnostic to Assess Precipitation-Thermodynamic Relations and Application to CMIP6 Models

A process-oriented diagnostic (POD) is introduced to measure the thermodynamic sensitivity of convection in climate models. The physical basis for this POD is the observed tropical precipitation-buoyancy relationship. Fast timescale precipitation and thermodynamic profiles over oceans are POD inputs; these are used to evaluate model precipitation sensitivities to lower-tropospheric measures of subsaturation (SUBSAT(L)) and undilute conditional instability. The POD is used to diagnose 24 coupled model inter-comparison project phase six (CMIP6) models. Half the diagnosed models exhibit SUBSAT(L) sensitivity close to observed, while six models are excessively sensitive. Parameter perturbation experiments with the Community Atmospheric Model (CAM5) support the physical basis for the POD. Increasing entrainment increases the CAM5 precipitation SUBSAT(L) sensitivity. Switching off the convective scheme or modifying the convective trigger to be oversensitive to moisture reproduces the excessive SUBSAT(L) sensitivity seen among CMIP6 models. Models with excessive SUBSAT(L) sensitivities have precipitating mean states closer to grid-scale saturation and likely support more grid-scale convection.

Automated summary

A process-oriented diagnostic (POD) is introduced to measure the thermodynamic sensitivity of convection in climate models based on the observed tropical precipitation-buoyancy relationship. The study diagnosed 24 coupled model inter-comparison project phase six (CMIP6) models and found that half of them exhibited sensitivity close to observed, while six models were excessively sensitive.