Precipitation plays an important role in various processes over the Southern Ocean (SO), ranging from the hydrological cycle to cloud and aerosol processes. The main objective of this study is to characterize SO precipitation properties. We use data from the Southern Ocean Clouds Radiation Aerosol Transport Experimental Study (SOCRATES), and leverage observations from airborne radar, lidar, and in situ probes. For the cold-topped clouds (cloud-top-temperature < 0°C), the phase of precipitation with reflectivity > 0 dBZ is predominately ice, while reflectivity < -10 dBZ is predominately liquid. Liquid-phase precipitation properties are retrieved where radar and lidar are zenith-pointing. The power-law relationships between reflectivity (Z) and rain rate (R) are developed, and the derived Z-R relationships show vertical dependence and sensitivity to the intermediate drops (diameters between 10-40 μm). Using derived Z-R relationships, reflectivity-velocity (ZV) retrieval method, and a radar-lidar retrieval method, we derive rain rate and other precipitation properties. The retrieved rain rate from all three methods shows good agreement with in-situ aircraft estimates. Rain rate features the prevalence of light precipitation (<0.1 mm hr-1). We examine the vertical distribution of precipitation properties, and found that rain rate, precipitation number concentration, precipitation liquid water all decreases as one gets closer to the surface, while precipitation size and width increases. We also examine how cloud base rain rate (RCB) depends on cloud depth (H) and aerosol concentration (Na) for particles with diameter greater than 70nm, and we find a linear relationship between RCB and H3.6Na-1.

Shallow cloud decks residing in or near the boundary layer cover a large fraction of the Southern Ocean (SO) and play a major role in determining the amount of shortwave radiation reflected back to space from this region. In this article, we examine the macrophysical characteristics and thermodynamic phase of low clouds (tops < 3 km) and precipitation using ground-based ceilometer, depolarization lidar and vertically-pointing W-band radar measurements collected during the Macquarie Island Cloud and Radiation Experiment (MICRE) from April 2016-March 2017. During MICRE, low clouds occurred ~65% of the time on average (slightly more often in austral winter than summer). About 2/3 of low clouds were cold-topped (temperatures < 0°C); these were thicker and had higher bases on average than warm-topped clouds. 83-88% of cold-topped low clouds were liquid phase at cloud base (depending on the season). The majority of low clouds had precipitation in the vertical range 150 to 250 meters below cloud base, a significant fraction of which did not reach the surface. Phase characterization is limited to the period between April 2016 and November 2016. Small-particle (low-radar-reflectivity) precipitation (which dominates precipitation occurrence) was mostly liquid below-cloud, while large-particle precipitation (which dominates total accumulation) was predominantly mixed/ambiguous or ice phase. Approximately 40% of cold-topped clouds had mixed/ambiguous or ice phase precipitation below (with predominantly liquid phase cloud droplets at cloud base). Below-cloud precipitation with radar reflectivity factors below about -10 dBZ were predominantly liquid, while reflectivity factors above about 0 dBZ were predominantly ice.

The accurate representation of cloud droplet number concentration (Nd) is crucial for predicting future climate. However, models often underestimate Nd over the Southern Ocean (SO), where natural sources dominate, and aerosols are composed primarily of marine biogenic sulfate and sea spray. This study uses a range of diverse datasets to evaluate and untangle biases in E3SMv2 simulated clouds, aerosols, and sulfur species. The default E3SMv2 underestimates Nd over SO by a factor of 2 when compared with observations in 3km-resolution simulations. Updating the dimethyl sulfide (DMS) emission and chemistry leads to a better agreement between the model and the observations in Nd and boundary layer aerosols, but low biases persist in the free tropospheric aerosol concentrations larger than 70 nm, possibly attributable to insufficient particle growth. Preliminary evaluation also reveals biases in simulated sulfur species, including overestimation in DMS at high latitudes, and in simulated sulfate mass concentration, highlighting the necessity for further efforts to improve the model treatment of relevant processes.

Cloud radiative feedbacks are currently the largest source of spread in estimates of climate sensitivity. Here we examine how cloud feedbacks relate to biases in model simulations of present-day clouds relative to NASA Multiangle Imaging SpectroRadiometer (MISR) satellite observations. Specifically, we examine relationships between bias in cloud fraction, cloud-top-height, and cloud optical depth with tropical high cloud, midlatitude low cloud, global high-cloud altitude, and tropical low cloud feedbacks for CMIP5 and CMIP6 models that have produced MISR simulator output. We find that the strength of all four of these simulated cloud feedbacks have statistically significant relationships with biases in present-day simulations of clouds. We use these relationships in an emergent constraint analysis to narrow the spread in the strength of each feedback. This suggests that future expert assessments of cloud feedbacks (and climate sensitivity) should consider present day biases in clouds and the climate modeling community might consider undertaking simulations where models are systematically tuned to eliminate (or at least reduce) biases relative to satellite observations.

It is predicted by both theory and models that high-altitude clouds will occur higher in the atmosphere as a result of climate warming. This produces a positive longwave feedback and has a substantial impact on the Earth’s response to warming. This effect is well established by theory, but is poorly constrained by observations, and there is large spread in the feedback strength between climate models. We use the NASA Multi-angle Imaging SpectroRadiometer (MISR) to examine changes in Cloud-Top-Height (CTH). MISR uses a stereo-imaging technique to determine CTH. This approach is geometric in nature and insensitive to instrument calibration and therefore is well suited for trend analysis and studies of variability on long time scales. In this article we show that the current MISR record does have an increase in CTH for high-altitude cloud over Southern Hemisphere (SH) oceans but not over Tropical or the Northern Hemisphere (NH) oceans. We use climate model simulations to estimate when MISR might be expected to detect trends in CTH, that include the NH. The analysis suggests that according to the models used in this study MISR should detect changes over the SH ocean earlier than the NH, and if the model predictions are correct should be capable of detecting a trend over the Tropics and NH very soon (3 to 10 years). This result highlights the potential value of a follow-on mission to MISR, which no longer maintains a fixed equator crossing time and is unlikely to be making observations for another 10 years.

Aircraft observations collected during the Southern Ocean Cloud Radiation Aerosol Transport Experimental Study (SOCRATES) in January-February of 2018 are used to evaluate cloud properties from three satellite-imager datasets: (i) the Moderate Resolution Imaging Spectroradiometer (MODIS) level 2 (collection 6.1) cloud product, (ii) the CERES-MODIS Edition 4 cloud product, and (iii) the NASA SatCORPS Himawari-8 cloud product. Overall the satellite retrievals compare well with the in situ observations, with little bias and modest to good correlation coefficients when considering all aircraft profiles for which there are coincident MODIS observations. The Himawari-8 product does, however, show a statistically significant mean bias of about 1.2 μm for effective radius (re) and 2.6 for optical depth (τ) when applied to a larger set of profiles with coincident Himawari-8 observations. The low overall mean-bias in the re retrievals is due in part to compensating errors between cases that are non- or lightly-precipitating, with cases that have heavier precipitation. re is slightly biased high (by about 0.5 to 1.0 μm) for non- and lightly-precipitating cases and biased low by about 3 to 4 μm for heavily-precipitating cases when precipitation exits near cloud top. The bias in non- and lightly-precipitating conditions is due to (at least in part) having assumed a drop size distribution in the retrieval that is too broad. These biases in the re ultimately propagate into the retrieved liquid water path and number concentration.

Many studies involving surface radiative fluxes rely on surface fluxes retrieved by the Clouds and the Earth’s Radiant Energy System (CERES) project, or derived from spaceborne cloud radar and lidar observations (CloudSat-CALIPSO). In particular, most climate models that participated in the Coupled Model Intercomparison Project Phase 5 (CMIP5) were found to have too little shortwave radiation being reflected back to space and excessive shortwave radiation reaching the surface over the Southern Ocean – an error with significant consequences for predicting both regional and global climate. There have been few evaluations of CERES or CloudSat retrievals over the Southern Ocean. In this article, CERES and CloudSat retrieved surface shortwave (SW) and longwave (LW) downwelling fluxes are evaluated using surface observations collected over the Southern Ocean during the Macquarie Island Cloud and Radiation Experiment (MICRE). Overall, biases (CERES – surface observations) in the CERES- surface fluxes are found to be slightly larger over Macquarie Island than most other regions, approximately +10 Wm for the SW and -10 Wm for the LW in the annual mean, but with significant seasonal and diurnal variations. If the Macquarie observations are representative of the larger SO, these results imply that CMIP5 model errors in SW surface fluxes are (if anything) somewhat larger than previous evaluation studies suggest. The bias in LW surface flux shows a marked increase at night, which explains most of the total LW bias. The nighttime bias is due to poor representation of cloud base associated with low clouds.

Climate models exhibit major radiative biases over the Southern Ocean owing to a poor representation of mixed-phase clouds. This study uses the remote-sensing dataset from the Measurements of Aerosols, Radiation and Clouds over the Southern Ocean (MARCUS) campaign to assess the ability of the Weather Research and Forecasting (WRF) model to reproduce frontal clouds off Antarctica. It focuses on the modeling of thin mid-level supercooled liquid water layers which precipitate ice. The standard version of WRF produces almost fully glaciated clouds and cannot reproduce cloud top turbulence. Our work demonstrates the importance of adapting the ice nucleation parameterization to the pristine austral atmosphere to reproduce the supercooled liquid layers. Once simulated, droplets significantly impact the cloud radiative effect by increasing downwelling longwave fluxes and decreasing downwelling shortwave fluxes at the surface. The net radiative effect is a warming of snow and ice covered surfaces and a cooling of the ocean. Despite improvements in our simulations, the local circulation related to cloud-top radiative cooling is not properly reproduced, advocating for the need to develop a parameterization for top-down convection to capture the turbulence-microphysics interplay at cloud top.