Increasing resolution and resolving convection improves the simulation of cloud-radiative effects over the North Atlantic

Abstract

Clouds interact with atmospheric radiation and substantially modify the Earth's energy budget. Cloud formation processes occur over a vast range of spatial and temporal scales, which make their thorough numerical representation challenging. Therefore, the impact of parameter choices for simulations of cloud-radiative effects is assessed in the current study. Numerical experiments are carried out using the ICOsahedral Nonhydrostatic (ICON) model with varying grid spacings between 2.5 and 80 km and with different subgrid-scale parameterization approaches. Simulations are performed over the North Atlantic with either one-moment or two-moment microphysics and with convection being parameterized or explicitly resolved by grid-scale dynamics. Simulated cloud-radiative effects are compared to products derived from Meteosat measurements. Furthermore, a sophisticated cloud classification algorithm is applied to understand the differences and dependencies of simulated and observed cloud-radiative effects. The cloud classification algorithm developed for the satellite observations is also applied to the simulation output based on synthetic infrared brightness temperatures, a novel approach that is not impacted by changing insolation and guarantees a consistent and fair comparison. It is found that flux biases originate equally from clear-sky and cloudy parts of the radiation field. Simulated cloud amounts and cloud-radiative effects are dominated by marine, shallow clouds, and their behavior is highly resolution dependent. Bias compensation between shortwave and longwave flux biases, seen in the coarser simulations, is significantly diminished for higher resolutions. Based on the analysis results, it is argued that cloud-microphysical and cloud-radiative properties have to be adjusted to further improve agreement with observed cloud-radiative effects.Plain Language Summary Clouds are a major challenge for climate science, and their effects are difficult to quantify. Clouds scatter sunlight back into space and thus prevent the Earth from warming up. But clouds also hold back heat radiation upwelling from the surface. Both effects typically compensate each other and thus lead to the net cloud-radiative effect. Computer programs that are used to simulate the climate-so-called climate models-often use very coarse grid-box sizes in their computational mesh. Cloud processes and their effects are represented in them in a very simplified way, which leads to problems. For this reason, this study deals with the question to what extent the simulations of cloud-radiative effects can be improved by choosing more precise descriptions of the cloud processes. To investigate this, different configurations of more realistic models were taken to simulate cloud formation over the North Atlantic. The resulting simulation data were compared to satellite observations. It could be shown that problematic biases of the coarser climate models are reduced if, as is usual in weather models, one switches to smaller grid-box sizes and improved descriptio...