Simulating Observations of Southern Ocean Clouds and Implications for Climate

Abstract

Southern Ocean (S. Ocean) clouds are important for climate prediction. Yet previous global climate models failed to accurately represent cloud phase distributions in this observation-sparse region. In this study, data from the Southern Ocean Clouds, Radiation, Aerosol, Transport Experimental Study (SOCRATES) experiment is compared to constrained simulations from a global climate model (the Community Atmosphere Model, CAM). Nudged versions of CAM are found to reproduce many of the features of detailed in situ observations, such as cloud location, cloud phase, and boundary layer structure. The simulation in CAM6 has improved its representation of S. Ocean clouds with adjustments to the ice nucleation and cloud microphysics schemes that permit more supercooled liquid. Comparisons between modeled and observed hydrometeor size distributions suggest that the modeled hydrometeor size distributions represent the dual peaked shape and form of observed distributions, which is remarkable given the scale difference between model and observations. Comparison to satellite observations of cloud physics is difficult due to model assumptions that do not match retrieval assumptions. Some biases in the model's representation of S. Ocean clouds and aerosols remain, but the detailed cloud physical parameterization provides a basis for process level improvement and direct comparisons to observations. This is crucial because cloud feedbacks and climate sensitivity are sensitive to the representation of S. Ocean clouds. Plain Language Summary Clouds over the Southern Ocean are important for climate prediction and may influence the evolution of global temperatures. Thus, these clouds are important to represent properly in models; however, recent studies have revealed models inadequately represent Southern Ocean cloud occurrence and phase, which drive large biases in radiation and subsequent climate sensitivity. Observations from research aircraft over the Southern Ocean south of Australia are compared to simulations with a global climate model which is "nudged" to reproduce the day-today cloud systems which are sampled. Despite being a coarse horizontal and vertical resolution, the model is able to reproduce many details of cloud phase and water content during the flights. However, the model has some biases, and these observations have been used to improve the model to better represent cloud phase. These results point to specific observational constraints for improving model simulations.

Influences of Recent Particle Formation on Southern Ocean Aerosol Variability and Low Cloud Properties

“…While precipitation bias is small on average for SOCRATES CAM6 simulations, precipitation is over-produced in cumulus-like clouds and under-produced in stratocumulus clouds (Zhou et al, 2020). CAM6 phase partitioning, particularly production of super-cooled liquid clouds, shows little bias across the campaign (Gettelman et al, 2020;Zhou et al, 2020) but cumulus clouds are excessively glaciated (Atlas et al, 2020). Activation of CCN into N d is dependent on CCN availability (which we show in this paper has a campaign-wide bias) and turbulent updrafts.…”

Observations of Clouds, Aerosols, Precipitation, and Surface Radiation over the Southern Ocean: An Overview of CAPRICORN, MARCUS, MICRE, and SOCRATES

“…For instance, aircraftmeasured temperatures were typically within 1 K of the reanalysis and within 2 K of the nudged GCMs. Figure 5 of Gettelman et al (2020) shows the example of RF07, in which CAM6 is nudged to the MERRA2 reanalysis. Both MERRA2 and the ERA5 reanalysis used by the nudged AM4 are fine choices for the nudged-meteorology approach.…”

“…Figures 10 and 14 of Gettelman et al (2020) show examples of comparisons of nudged versions of CAM6 and its predecessor version CAM5 with aircraft cloud microphysical observations from SOCRATES RF07. These show that CAM6 correctly simulates a BL stratocumulus layer that is observed to be primarily supercooled liquid, while CAM5 incorrectly simulates the same cloud layer to mainly be ice.…”

Climate Impacts of COVID‐19 Induced Emission Changes

“…One is the Community Earth System Model version 2 (CESM2), (Danabasoglu et al, 2020). The atmospheric model in CESM is the Community Atmosphere Model version 6 (CAM6), described by Gettelman et al (2020). CAM6 features a detailed two-moment cloud microphysics scheme (Gettelman & Morrison, 2015) coupled to an aerosol microphysics and chemistry model (Liu et al, 2016), as detailed in Gettelman et al (2019).…”

“…For CESM we use the standard resolution (∼1° horizontal resolution, 32 levels to 3 hPa), in a nudged configuration as described by Gettelman et al (2020). The model time step is 1,800s.…”