Mixed-phase cloud physics and Southern Ocean cloud feedback in climate models. T 5050 Liquid Condensate Fraction (LCF) Correlation between T5050 and ∆LWP.

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Mixed-phase cloud physics and Southern Ocean cloud feedback in climate models. T 5050 Liquid Condensate Fraction (LCF) Correlation between T5050 and ∆LWP Correlation between T5050 and LWP 0 Correlation between T5050 and IWP 0 The fraction of cloud water that is liquid as a function of atmospheric temperature for the 19 GCMs surveyed. Lidar observations from Hu et al are shown as a red dashed line for comparison. Colored curves each show a GCM. The temperature where ice and liquid are equally prevalent (T5050) is noted with a red, horizontal line. This value varies by 40K across models. The across-model correlation coefficients between each model’s T5050 and various zonal- mean quantities over the Southern Ocean. Correlation coefficients are shown in latitude and season. [Top] the correlation coefficient between the change in liquid water path (LWP) between the historical and RCP8.5 simulations. [Middle] the correlation coefficient between T5050 and the historical LWP of each model. [Bottom] the correlation coefficient between T5050 and the historical ice water path (IWP) of each model. Models that create ice at higher temperatures have a larger increase in liquid water in a warming climate, a lower amount of liquid water in the historical climate, and a larger amount of ice in the historical climate. Objective To analyze the diversity in how global climate models (GCMs) represent the freezing of liquid in clouds as a function of temperature. Based on this, we wish to understand how much this diversity affects the way that midlatitude clouds over the Southern Ocean clouds change their brightness as the climate warms. Approach GCM simulations from the historical scenario and a global warming scenario (RCP8.5) were used to study how clouds in the current climate partition between ice and liquid as a function of temperature. The changes cloud liquid and ice amount were examined in the context of how each model partitioned ice and liquid. Each model was assigned a index based on the temperature where ice and liquid were equally prevalent (T5050) and this index was found to vary by 40K between models and explain a significant amount of the variability in how the amount of liquid increased as the climate warmed and how much liquid and ice were in the climate mean state. Impact The SW cloud feedback is one of the major sources of model uncertainty in the representation of equilibrium climate sensitivity and the shortwave (SW) cloud feedback is robustly negative in the midlatitudes because dull ice transitions to bright liquid with warming. Understanding how model parameterization choices affect this is important to understanding the spread in the SW cloud feedback in GCMs. We find that models have a 40K spread in the temperature where they think ice and liquid are equally common and this significantly affects both their historical state and their response to warming, indicating that model parameterizations of ice-liquid partitioning must be more thoroughly vetted. McCoy DT, Hartmann DL, Zelinka MD, Ceppi P, Grosvenor DP /2015JD T(K)