Evaluation of Cloud and Precipitation Parameterization Using a Single-Column Model: A TWP-ICE Case Study

Abstract:

Cloud and precipitation parameterization schemes are evaluated, and their sensitivity to the method and/or parameters used to determine cloud physical processes is examined using a singlecolumn version of the Unified Model (SCUM). In the experiment for TWP-ICE, cloud fraction is overestimated (underestimated) in the upper (lower) troposphere due to the wet (dry) bias. The precipitation rate is well simulated during the active monsoon period, but overestimated during the suppressed monsoon and clear skies periods. In the moist convection scheme, trigger condition and entrainment process affect the lower tropospheric humidity through the impact on convective occurrence frequency and intensity, respectively. Strengthening the trigger condition and using the adaptive entrainment method alleviate the low-level dry bias. In the microphysics scheme, more large-scale precipitation is produced with prognostic rain, due to rain sedimentation considering vertical velocity of rain drop, than with diagnostic rain. Less ice/snow deposition with the prognostic two-ice category results in lower ice water content and upper-level cloud fraction than with the diagnostic splitting method for the twoice category. In the cloud macrophysics scheme, the prognostic cloud fraction and cloud/ice water content scheme produces a larger cloud fraction and more cloud/ice water content than the diagnostic scheme, mainly due to detrainment from moist convection (cloud source) that surpasses the effect of convective heating and drying (cloud sink). This affects temperature by influencing the radiative, convective, and microphysical processes. The experiment with combined modifications in cloud and precipitation schemes shows that interaction between modified moist convection and cloud macrophysics schemes results in more alleviation of the cold bias not only at the lower levels but also at the upper levels.