Description: We present four melt climatology estimates based on a simulation of Antarctic iceberg drift and melting that includes small, medium-sized, and giant tabular icebergs with a realistic size distribution. For the first time, an iceberg model is initialized with a set of nearly 7000 observed iceberg positions and sizes around Antarctica. We simulate drift and lateral melt using iceberg-draft averaged ocean currents, temperature, and salinity. A new basal melting scheme, originally applied in ice shelf melting studies, uses in situ temperature, salinity, and relative velocities at an iceberg's bottom. The climatology estimates based on simulations of small (SMA), 'small-to-medium'-sized (MED12 & MED123), and small-to-giant icebergs (ALL) exhibit differential characteristics: successive inclusion of larger icebergs leads to a reduced seasonality of the iceberg meltwater flux and a shift of the mass input to the area north of 58°S, while less meltwater is released into the coastal areas. This highlights the necessity to account for larger and giant icebergs in order to obtain accurate melt climatologies. The four monthly melt climatologies [mm/day] are available as netCDF files with 1°x1° spatial resolution and can be used, e.g., for sensitivity studies with uncoupled sea ice-ocean models, or as spatio-temporal templates for the redistribution of land ice from the Antarctic ice sheet over the Southern Ocean in climate models.

Description: This bibliography unites the individual data collected by different types of autonomous platforms deployed during MOSAiC in 2019/2020.

Description: This study introduces a new flow‐dependent distribution sampling (FDDS) scheme for air–sea coupling. The FDDS scheme is implemented in a climate model and used to improve the simulated mean and variability of atmospheric and oceanic surface fields and thus air–sea fluxes. Most coupled circulation models use higher resolutions in the sea ice and ocean compared to the atmospheric model component, thereby explicitly simulating the atmospheric subgrid‐scale at the interface. However, the commonly applied averaging of surface fields and air–sea fluxes tends to smooth fine‐scale structures, such as oceanic fronts. The stochastic FDDS scheme samples the resolved spatial ocean (and sea ice) subgrid distribution that is usually not visible to a coarser‐resolution atmospheric model. Randomly drawn nodal ocean values are passed to the corresponding atmospheric boxes for the calculation of surface fluxes, aiming to enhance surface flux variability. The resulting surface field perturbations of the FDDS scheme are based on resolved dynamics, displaying pronounced seasonality with realistic magnitude. The AWI Climate Model is used to test the scheme on interannual time‐scales. Our set‐up features a high ocean‐to‐atmosphere resolution ratio in the Tropics, with grid‐point ratios of about 60:1. Compared to the default deterministic averaging, changes are largest in the Tropics leading to an improved spatial distribution of precipitation with bias reductions of up to 50%. Enhanced sea‐surface temperature variability in boreal winter further improves the seasonal phase locking of temperature anomalies associated with the El Niño–Southern Oscillation. Mean 2m temperature, sea ice thickness and concentration react with a contrasting dipole pattern between hemispheres but a joint increase of monthly and interannual variability. This first approach to implement a flow‐dependent stochastic coupling scheme shows considerable benefits for simulations of global climate, and various extensions and modifications of the scheme are possible.