As an alternative approach to the previous multisensor satellite evaluation method of cloud system resolving models, a method is presented using combined infrared and microwave channels for precipitation clouds in cloud system resolving models over the ocean. This method determines characteristics of cloud-top temperatures and ice scatterings for clouds using infrared 11-μm and microwave high frequencies (89.0 GHz) brightness temperatures (TBs). The threshold of the TB at low frequencies (18.7 GHz) is also used to identify precipitation regions. This method extends the previous approach via the wider swath of the passive microwave sensor and sensitivities to ice clouds compared to the previous Tropical Rainfall Measuring Mission (TRMM)-based analysis method using the narrower coverage of the Precipitation Radar.
The numerical results of the non-hydrostatic icosahedral atmospheric model (NICAM) with two cloud microphysics schemes are evaluated over the tropical open ocean using this method. The intensities of the scatterings in the two simulations at 89.0 GHz are different due to the parameterizations of the snow and graupel size distributions. A bimodal size distribution of the snow improved the underestimation of the TBs at 89.0 GHz. These results have a similar structure to the joint histograms of cloud-top temperatures and precipitation-top heights in the previous method: the overestimated intensity of scattering and the frequencies of high precipitation-top heights above 12 km in the control experiment. We find that the change in the snow size distribution in the cloud microphysics scheme can lead to better agreements of simulated TBs at 89.0 GHz with observations. We further investigate impacts of non-spherical assumptions for snow using a satellite simulator. The effect of a non-spherical shape of snow in the radiative transfer model causes a smaller change of TBs at 89.0 GHz compared to the difference between the TBs of the two simulations without non-spherical assumptions.
2018 The Author(s) CC-BY 4.0 (Before 2018: Copyright © Meteorological Society of Japan)