GTS v1.0: a macrophysics scheme for climate models based on a probability density function

Abstract. Cloud macrophysics schemes are unique parameterizations for general circulation models. We propose an approach based on a probability density function (PDF) that utilizes cloud condensates and saturation ratios to replace the assumption of critical relative humidity (RH). test this approach, called Global Forecast System (GFS) – Taiwan Earth Model (TaiESM) Sundqvist (GTS) scheme, using scheme within Community Atmosphere version 5.3 (CAM5.3) framework. Via single-column model results, new simulates fraction (CF)–RH distributions closer those observations when compared default CAM5.3 scheme. also validate impact GTS global climate simulations with satellite observations. The simulated CF is comparable CloudSat/Cloud-Aerosol Lidar Infrared Pathfinder Satellite Observation (CALIPSO) data. Comparisons vertical water content (CWC), as functions large-scale dynamic thermodynamic parameters, CloudSat/CALIPSO data suggest can closely simulate This particularly noticeable such RH, upper-tropospheric temperature, total precipitable water, implying our variation in associated RH more reliably than Changes CWC would affect climatic fields via cloud–radiation interaction. Both climatological means annual cycles many GTS-simulated variables improved respect vapor fields. Different PDF shapes significantly simulations.