Robustness and Uncertainties of Global Cloud-Resolving Models: Evaluations and Improvements of Clouds with a Seamless Approach

Abstract:

Global cloud-resolving models (GCRMs), which are defined as global models with horizontal resolution less than about 5km without using a convective parameterization scheme (Satoh et al. 2019, https://doi.org/10.1007/s40641-019-00131-0), produces a fine scale structure of upper clouds that is very similar to that of a geostationary satellite image, as demonstrated by the DYAMOND project (Stevens et al. 2020, https://doi.org/10.1186/s40645-019-0304-z). We show that they have very different vertical cloud profiles, which are one of the most uncertain aspects of GCRMs.

To improve cloud simulations, we take a seamless approach by using NICAM for global and regional domains. We propose an intensive collaboration study between NICAM and the ground observation data in the Tokyo area, called ULTIMATE (ULTra-sIte for Measuring Atmosphere of Tokyo metropolitan Environment). The comprehensive observation data is available in the Tokyo area, whose domain size is about 100 km×100km. By this approach, the improved models are promptly tested in the global domain to compare with satellite observations and to estimate climate sensitivity. We will promote ULTIMATE targeting the launch of the EarthCARE satellite which is planned in 2022 (Illingworth et al. 2015, https://dx.doi.org/10.1175/BAMS-D-12-00227.1).