The use of satellite data‐based “critical relative humidity” in cloud parameterization and its role in modulating cloud feedback

The critical relative humidity (RHc), which approximately measures the subgrid-scale variability of moisture, is important to cloud parameterization. Based on the diagnostics from CloudSat/CALIPSO satellite data, we propose an improved RHc formula that incorporates geographic dependence and allows for non-monotonic variations in the vertical. With the parameterized RHc, a cloud macrophysics scheme is constructed in which fractional cloudiness and subgrid-scale condensation are synergistically solved, with the latter being calculated using two different approaches. Results show the new scheme largely alleviates the underestimation of high- and mid-level clouds in the default model. The performance is also superior to the simulations applying a globally uniform RHc as conventionally used in the literature. Varying RHc and the techniques for computing subgrid-scale condensation leads to a marked diversity in cloud feedback, which nearly replicates the range of uncertainty found in Coupled Model Intercomparison Project Phase 6 models. Using smaller RHc leads to larger spread than using larger ones. And the spread caused by different techniques for calculating subgrid-scale condensation is larger than that caused by the choice of RHc. While many previous studies have emphasized the diversity of cloud feedback due to low clouds, varying RHc and its implementation leads to diversity of cloud feedback being mainly due to optically thick clouds. These results highlight the importance of RHc in inducing uncertainty of cloud feedback, as well as notes of caution to modelers when using RHc to tune models.