Explicitly-coupled cloud physics and radiation parameterizations and subsequent evaluation in WRF high-resolution convective forecasts

•Existing WRF model assumes a prior cloud droplet and ice crystal sizes irrespective of assumptions in microphysics schemes.•Explicit coupling of microphysics−derived effective size and optical depth capably demonstrates “cloud brightening” effect.•Observed versus WRF synthetic satellite reveals abundant model clouds near + 10 °C and deficient model clouds near − 10 °C.

The impacts of various assumptions of cloud properties represented within a numerical weather prediction model's radiation scheme are demonstrated. In one approach, the model assumed the radiative effective radii of cloud water, cloud ice, and snow were represented by values assigned a priori, whereas a second, “coupled” approach utilized known cloud particle assumptions in the microphysics scheme that evolved during the simulations to diagnose the radii explicitly. This led to differences in simulated infrared (IR) brightness temperatures, radiative fluxes through clouds, and resulting surface temperatures that ultimately affect model-predicted diurnally-driven convection. The combined approach of evaluating simulated versus observed IR brightness temperatures, radiation reaching the ground, and surface temperature forecasts revealed the root model biases better than evaluating any single variable. This study found that the Weather Research and Forecasting (WRF) model predicted less overall clouds than was observed, particularly in the mid‑troposphere, but that properly connecting the assumptions of particle sizes in the microphysics scheme to the radiation scheme resulted in sensible cloud-radiation indirect effects and modest improvements in simulated IR brightness temperature, amount of solar radiation reaching the ground, and surface temperature.