Science Daily May 31, 2022
Analyses of global climate models consistently show that clouds constitute the biggest source of uncertainty and instability. But they occur on a length- and timescale that today’s models can’t come close to reproducing. Therefore, they included in models through a variety of approximations. A team of researchers in the US (UC Irvine, Lawrence Livermore National Laboratory, University of Washington, industry) is working to fix this glaring gap by breaking the climate modeling problem into two parts: a coarse-grained, lower-resolution (100km) planetary model and many small patches with 100 to 200 meter resolution. They developed a way for a supercomputer to best split up the work of simulating the cloud physics over different parts of the world using the ‘Multiscale Modeling Framework (MMF),’ has been around since 2000. They demonstrated that the multi-model approach did not produce unwanted side-effects even where patches using different cloud-resolving grid structures met…read more. Open Access TECHNICAL ARTICLEÂ
Box plot of the cloud fraction differences… Credit: Journal of Advances in Modeling Earth Systems, 2022; 14 (5)Â