Measured ice crystal concentrations in natural clouds at modest supercooling (temperature ;.2108C) are often orders of magnitude greater than the number concentration of primary ice nucleating particles. Therefore, it has long been proposed that a secondary ice production process must exist that is able to rapidly enhance the number concentration of the ice population following initial primary ice nucleation events. Secondary ice production is important for the prediction of ice crystal concentration and the subsequent evolution of some types of clouds, but the physical basis of the process is not understood and the production rates are not well constrained. In November 2015 an international workshop was held to discuss the current state of the science and future work to constrain and improve our understanding of secondary ice production processes. Examples and recommendations for in situ observations, remote sensing, laboratory investigations, and modeling approaches are presented.

We compare measurements of the turbulent and radiative surface energy fluxes from an automatic weather station (AWS) on Larsen C Ice Shelf, Antarctica with corresponding fluxes from three high-resolution atmospheric models over a 1 month period during austral summer. All three models produce a reasonable simulation of the (relatively small) turbulent energy fluxes at the AWS site. However, biases in the modeled radiative fluxes, which dominate the surface energy budget, are significant. There is a significant positive bias in net shortwave radiation in all three models, together with a corresponding negative bias in net longwave radiation. In two of the models, the longwave bias only partially offsets the positive shortwave bias, leading to an excessive amount of energy available for heating and melting the surface, while, in the third, the negative longwave bias exceeds the positive shortwave bias, leading to a deficiency in calculated surface melt. Biases in shortwave and longwave radiation are anticorrelated, suggesting that they both result from the models simulating too little cloud (or clouds that are too optically thin). We conclude that, while these models may be able to provide some useful information on surface energy fluxes, absolute values of modeled melt rate are significantly biased and should be used with caution. Efforts to improve model simulation of melt should initially focus on the radiative fluxes and, in particular, on the simulation of the clouds that control these fluxes.

We use model data from the Antarctic Mesoscale Prediction System (AMPS), measurements from automatic weather stations and satellite observations to investigate the association between surface energy balance (SEB), surface melt, and the occurrence of föhn winds over Larsen C Ice Shelf (Antarctic Peninsula) over the period November 2010 to March 2011. Föhn conditions occurred for over 20% of the time during this period and are associated with increased air temperatures and decreased relative humidity (relative to nonföhn conditions) over the western part of the ice shelf. During föhn conditions, the downward turbulent flux of sensible heat and the downwelling shortwave radiation both increase. However, in AMPS, these warming tendencies are largely balanced by an increase in upward latent heat flux and a decrease in downwelling longwave radiation so the impact of föhn on the modeled net SEB is small. This balance is highly sensitive to the representation of surface energy fluxes in the model, and limited validation data suggest that AMPS may underestimate the sensitivity of SEB and melt to föhn. There is broad agreement on the spatial pattern of melt between the model and satellite observations but disagreement in the frequency with which melt occurs. Satellite observations indicate localized regions of persistent melt along the foot of the Antarctic Peninsula mountains which are not simulated by the model. Furthermore, melt is observed to persist in these regions during extended periods when föhn does not occur, suggesting that other factors may be important in controlling melt in these regions.

The eastern side of the Antarctic Peninsula (AP) mountain range and the adjacent ice shelves are frequently affected by föhn winds originating from upwind of the mountains. Six automatic weather stations (AWSs) and archived model output from 5 km resolution Antarctic Mesoscale Prediction System (AMPS) forecasts have been combined to identify the occurrence of föhn conditions, and their spatial distribution over the Larsen C Ice Shelf (LCIS) from 2009 to 2012. Algorithms for semi‐automatic detection of föhn conditions have been developed for both AWS and AMPS data. The frequency of föhn varies by location, being most frequent at the foot of the AP and in the north of the ice shelf. They are most common in spring, when they can prevail for 50% of the time. The results of this study have important implications for further research, investigating the impact of föhn on surface melting, and the surface energy budget of the ice shelf. This is of particular interest due to the collapse of Larsen A and B ice shelves in 1995 and 2002 respectively, and the potential instability issues following a large calving event on Larsen C in 2017.

Abstract. Antarctic tropospheric clouds are investigated using the DARDAR (raDAR/liDAR)-MASK products between 60 and 82∘ S. The cloud fraction (occurrence frequency) is divided into the supercooled liquid-water-containing cloud (SLC) fraction and its complementary part called the all-ice cloud fraction. A further distinction is made between SLC involving ice (mixed-phase clouds, MPC) or not (USLC, for unglaciated SLC). The low-level (<3 km above surface level) SLC fraction is larger over seas (20 %–60 %), where it varies according to sea ice fraction, than over continental regions (0 %–35 %). The total SLC fraction is much larger over West Antarctica (10 %–40 %) than it is over the Antarctic Plateau (0 %–10 %). In East Antarctica the total SLC fraction – in summer for instance – decreases sharply polewards with increasing surface height (decreasing temperatures) from 40 % at the coast to <5% at 82∘ S on the plateau. The geographical distribution of the continental total all-ice fraction is shaped by the interaction of the main low-pressure systems surrounding the continent and the orography, with little association with the sea ice fraction. Opportunistic comparisons with published ground-based supercooled liquid-water observations at the South Pole in 2009 are made with our SLC fractions at 82∘ S in terms of seasonal variability, showing good agreement. We demonstrate that the largest impact of sea ice on the low-level SLC fraction (and mostly through the MPC) occurs in autumn and winter (22 % and 18 % absolute decrease in the fraction between open water and sea ice-covered regions, respectively), while it is almost null in summer and intermediate in spring (11 %). Monthly variability of the MPC fraction over seas shows a maximum at the end of summer and a minimum in winter. Conversely, the USLC fraction has a maximum at the beginning of summer. However, monthly evolutions of MPC and USLC fractions do not differ on the continent. This suggests a seasonality in the glaciation process in marine liquid-bearing clouds. From the literature, we identify the pattern of the monthly evolution of the MPC fraction as being similar to that of the aerosols in coastal regions, which is related to marine biological activity. Marine bioaerosols are known to be efficient ice-nucleating particles (INPs). The emission of these INPs into the atmosphere from open waters would add to the temperature and sea ice fraction seasonalities as factors explaining the MPC fraction monthly evolution.