On the spread of changes in marine low cloud cover in 1 climate model simulations of the 21 st century

In 36 climate change simulations associated with phases 3 and 5 of the 7 Coupled Model Intercomparison Project (CMIP3 and CMIP5), changes in marine low 8 cloud cover (LCC) exhibit a large spread, and may be either positive or negative. Here 9 we develop a heuristic model to understand the source of the spread. The model’s 10 premise is that simulated LCC changes can be interpreted as a linear combination of 11 contributions from factors shaping the clouds’ large-scale environment. We focus pri12 marily on two factors—the strength of the inversion capping the atmospheric boundary 13 layer (measured by the estimated inversion strength, EIS) and sea surface temperature 14 (SST). For a given global model, the respective contributions of EIS and SST are com15 puted. This is done by multiplying (1) the current-climate’s sensitivity of LCC to EIS 16 or SST variations, by (2) the climate-change signal in EIS or SST. The remaining LCC 17 changes are then attributed to changes in greenhouse gas and aerosol concentrations, 18 X. Qu, A. Hall Department of Atmospheric and Oceanic Sciences, University of California, Los Angeles, PO BOX 951565, CA 90095-1565 S.A. Klein, P.M. Caldwell Program for Climate Model Diagnosis and Intercomparison, Lawrence Livermore National Laboratory, Mail Code L-103, PO BOX 808, Livermore, CA 94551 E-mail: [email protected] 2 and other environmental factors. The heuristic model is remarkably skillful. Its SST 19 term dominates, accounting for nearly two-thirds of the intermodel variance of LCC 20 changes in CMIP3 models, and about half in CMIP5 models. Of the two factors govern21 ing the SST term (the SST increase and the sensitivity of LCC to SST perturbations), 22 the SST sensitivity drives the spread in the SST term and hence the spread in the 23 overall LCC changes. This sensitivity varies a great deal from model to model and is 24 strongly linked to the types of cloud and boundary layer parameterizations used in the 25 models. 26 EIS and SST sensitivities are also estimated using observational cloud and meteo27 rological data. The observed sensitivities are generally consistent with the majority of 28 models as well as expectations from prior research. Based on the observed sensitivities 29 and the relative magnitudes of simulated EIS and SST changes (which we argue are 30 also physically reasonable), the heuristic model predicts LCC will decrease over the 31 21st-century. However, to place a strong constraint, for example on the magnitude of 32 the LCC decrease, will require longer observational records and a careful assessment of 33 other environmental factors producing LCC changes. Meanwhile, addressing biases in 34 simulated EIS and SST sensitivities will clearly be an important step towards reducing 35 intermodel spread in simulated LCC changes. 36