Significant Spatial Variability in Radar-Derived West Antarctic Accumulation Linked to Surface Winds and Topography

Across the Antarctic Ice Sheet, accumulation heavily influences firn compaction and surface height changes. Therefore, accumulation varies over short distances (25 km) that are too coarse to resolve this variability. To address this limitation, we construct a fine-scale accumulation product from airborne snow radar observations by superimposing along-track fluctuations in accumulation onto an atmospheric reanalysis product. Our resulting airborne product reflects large-scale (>25 km) orographic precipitation patterns while providing robust and unprecedented insight into Antarctic accumulation variability on subgrid scales. On these smaller scales, we find significant, regionally dependent accumulation variability ((sub relative) > 40%). This variability in accumulation is correlated with variability in topographic surface slope in the wind direction (p < 0.01), confirming that subgrid-scale accumulation variability is driven by snow redistribution by wind

Influence of Sea-Ice Anomalies on Antarctic Precipitation Using Source Attribution in the Community Earth System Model

We conduct sensitivity experiments using a general circulation model that has an explicit water source tagging capability forced by prescribed composites of pre-industrial sea-ice concentrations (SICs) and corresponding sea surface temperatures (SSTs) to understand the impact of sea-ice anomalies on regional evaporation, moisture transport and sourcereceptor relationships for Antarctic precipitation in the absence of anthropogenic forcing. Surface sensible heat fluxes, evaporation and column-integrated water vapor are larger over Southern Ocean (SO) areas with lower SICs. Changes in Antarctic precipitation and its source attribution with SICs have a strong spatial variability. Among the tagged source regions, the Southern Ocean (south of 50 S) contributes the most (40 %) to the Antarctic total precipitation, followed by more northerly ocean basins, most notably the South Pacific Ocean (27%), southern Indian Ocean (16 %) and South Atlantic Ocean (11 %). Comparing two experiments prescribed with high and low pre-industrial SICs, respectively, the annual mean Antarctic precipitation is about 150 Gt yr1 (or 6 %) more in the lower SIC case than in the higher SIC case. This difference is larger than the model-simulated interannual variability in Antarctic precipitation (99 Gt yr1). The contrast in contribution from the Southern Ocean, 102 Gt yr1, is even more significant compared to the interannual variability of 35 Gt yr1 in Antarctic precipitation that originates from the Southern Ocean. The horizontal transport pathways from individual vapor source regions to Antarctica are largely determined by large-scale atmospheric circulation patterns. Vapor from lower-latitude source regions takes elevated pathways to Antarctica. In contrast, vapor from the Southern Ocean moves southward within the lower troposphere to the Antarctic continent along moist isentropes that are largely shaped by local ambient conditions and coastal topography. This study also highlights the importance of atmospheric dynamics in affecting the thermodynamic impact of sea-ice anomalies associated with natural variability on Antarctic precipitation. Our analyses of the seasonal contrast in changes of basin-scale evaporation, moisture flux and precipitation suggest that the impact of SIC anomalies on regional Antarctic precipitation depends on dynamic changes that arise from SICSST perturbations along with internal variability. The latter appears to have a more significant effect on the moisture transport in austral winter than in summer

Dynamical Interaction between Atmosphere and Sea Ice in Antarctica

Abstract Sea ice that covers large parts of the polar oceans throughout most of the year responds to changes in the atmosphere or the ocean within a short period of time. The rapid decrease of the Arctic sea ice cover in the past decades has led to a fundamental discussion of the role of sea ice in the climate system. Surprisingly, in contrast to the northern hemisphere, the sea ice in the Southern Ocean has been slightly increasing over the last decades. This is owing to essentially different processes that take place around Antarctica. There, the ice is not confined to a basin as in the Arctic Ocean but can move rather freely around the Antarctic continent which results in a strong response to changes in the wind field. In this Master&apos;s thesis I examined the impact of the variations in the coastal Antarctic atmospheric boundary layer on the sea ice. By studying wind driven sea ice transport in the Southern Ocean and temporal and spatial variabilities in the period 1989 to 2006, I have revealed important characteristics of the sea ice cover and processes that determine its growth and decay. The near surface wind field over the coastal continent and ocean as well as its forcing mechanisms were described in detail by using output from a regional atmospheric climate model. This showed strong relations to key parameters that I have deduced from a satellite record of sea ice concentration and sea ice motion. The regions of the largest sea ice extent, the Ross and Weddell Seas, are also those areas where most of the sea ice transport takes place and where its variability is the largest. Interannual variations and trends of transport are associated with varying sea ice concentration just north of these areas in the Ross and Weddell Seas. Comparing the wind field and the sea ice motion, I found out that spatial patterns of persistent southerly or south-easterly winds coincide with those of ice drift. The winds in these regions result from combined effects of the large-scale pressure distribution, cold air that accumulates over the ice shelves, and large topographic barriers that alter the flow. Adjacent to the large Ross and Ronne-Filchner Ice Shelves constant outflow of cold air takes place almost year-round. Here, sea ice is constantly exported from the coastal region, and large polynyas and leads form. As the cold winds not only lead to sea ice transport but also support refreezing of the open water, these areas are associated with strong sea ice formation. I have defined an index that captures the outflow of cold continental air from the ice shelves. The long-term variations in outflow correlate well with variations of the sea ice cover and meridional sea ice transport in the Ross and western Weddell Seas. Further, the results suggest that the positive trend of sea ice cover in western Ross Sea and the negative trend in the western Weddell Sea are related to a respective seasonal increase and decrease of cold air outflow. Overall, in my thesis, I showed that the dynamical interaction between the atmospheric boundary layer and the sea ice is a regional key element in the interannual variability and the long-term changes of the sea ice cover in the Southern Ocean

Reconciling the surface temperature–surface mass balance relationship in models and ice cores in Antarctica over the last 2 centuries

Ice cores are an important record of the past surface mass balance (SMB) of ice sheets, with SMB mitigating the ice sheets' sea level impact over the recent decades. For the Antarctic Ice Sheet (AIS), SMB is dominated by large-scale atmospheric circulation, which collects warm moist air from further north and releases it in the form of snow as widespread accumulation or focused atmospheric rivers on the continent. This suggests that the snow deposited at the surface of the AIS should record strongly coupled SMB and surface air temperature (SAT) variations. Ice cores use δ18O as a proxy for SAT as they do not record SAT directly. Here, using isotope-enabled global climate models and the RACMO2.3 regional climate model, we calculate positive SMB–SAT and SMB–δ18O annual correlations over ∼90 % of the AIS. The high spatial resolution of the RACMO2.3 model allows us to highlight a number of areas where SMB and SAT are not correlated, and we show that wind-driven processes acting locally, such as foehn and katabatic effects, can overwhelm the large-scale atmospheric contribution in SMB and SAT responsible for the positive SMB–SAT annual correlations. We focus in particular on Dronning Maud Land, East Antarctica, where the ice promontories clearly show these wind-induced effects. However, using the PAGES2k ice core compilations of SMB and δ18O of Thomas et al. (2017) and Stenni et al. (2017), we obtain a weak annual correlation, on the order of 0.1, between SMB and δ18O over the past ∼150 years. We obtain an equivalently weak annual correlation between ice core SMB and the SAT reconstruction of Nicolas and Bromwich (2014) over the past ∼50 years, although the ice core sites are not spatially co-located with the areas displaying a low SMB–SAT annual correlation in the models. To resolve the discrepancy between the measured and modeled signals, we show that averaging the ice core records in close spatial proximity increases their SMB–SAT annual correlation. This increase shows that the weak measured annual correlation partly results from random noise present in the ice core records, but the change is not large enough to match the annual correlation calculated in the models. Our results thus indicate a positive correlation between SAT and SMB in models and ice core reconstructions but with a weaker value in observations that may be due to missing processes in models or some systematic biases in ice core data that are not removed by a simple average

Influence of Persistent Wind Scour on the Surface Mass Balance of Antarctica

Accurate quantification of surface snow accumulation over Antarctica is a key constraint for estimates of the Antarctic mass balance, as well as climatic interpretations of ice-core records. Over Antarctica, near-surface winds accelerate down relatively steep surface slopes, eroding and sublimating the snow. This wind scour results in numerous localized regions (< or = 200 sq km) with reduced surface accumulation. Estimates of Antarctic surface mass balance rely on sparse point measurements or coarse atmospheric models that do not capture these local processes, and overestimate the net mass input in wind-scour zones. Here we combine airborne radar observations of unconformable stratigraphic layers with lidar-derived surface roughness measurements to identify extensive wind-scour zones over Dome A, in the interior of East Antarctica. The scour zones are persistent because they are controlled by bedrock topography. On the basis of our Dome A observations, we develop an empirical model to predict wind-scour zones across the Antarctic continent and find that these zones are predominantly located in East Antarctica. We estimate that approx. 2.7-6.6% of the surface area of Antarctica has persistent negative net accumulation due to wind scour, which suggests that, across the continent, the snow mass input is overestimated by 11-36.5 Gt /yr in present surface-mass-balance calculations

Ice core evidence for a recent increase in snow accumulation in coastal Dronning Maud Land, East Antarctica

Abstract. Ice cores provide temporal records of snow accumulation, a crucial component of Antarctic mass balance. Coastal areas are particularly under-represented in such records, despite their relatively high and sensitive accumulation rates. Here we present records from a 120 m ice core drilled on Derwael Ice Rise, coastal Dronning Maud Land (DML), East Antarctica in 2012. We date the ice core bottom back to 1745 ± 2 AD. δ18O and δD stratigraphy is supplemented by discontinuous major ion profiles, and verified independently by electrical conductivity measurements (ECM) to detect volcanic horizons. The resulting annual layer history is combined with the core density profile to calculate accumulation history, corrected for the influence of ice deformation. The mean long-term accumulation is 0.425 ± 0.035 m water equivalent (w.e.) a−1 (average corrected value). Reconstructed annual accumulation rates show an increase from 1955 onward to a mean value of 0.61 ± 0.02 m w.e. a−1 between 1955 and 2012. This trend is compared to other reported accumulation data in Antarctica, generally showing a high spatial variability. Output of the fully coupled Community Earth System Model demonstrates that sea ice and atmospheric patterns largely explain the accumulation variability. This is the first and longest record from a coastal ice core in East Antarctica showing a steady increase during the 20th and 21st centuries, thereby supporting modelling predictions. </jats:p

Peak refreezing in the Greenland firn layer under future warming scenarios

Firn (compressed snow) covers approximately 90% of the Greenland ice sheet (GrIS) and currently retains about half of rain and meltwater through refreezing, reducing runoff and subsequent mass loss. The loss of firn could mark a tipping point for sustained GrIS mass loss, since decades to centuries of cold summers would be required to rebuild the firn buffer. Here we estimate the warming required for GrIS firn to reach peak refreezing, using 51 climate simulations statistically downscaled to 1 km resolution, that project the long-term firn layer evolution under multiple emission scenarios (1850–2300). We predict that refreezing stabilises under low warming scenarios, whereas under extreme warming, refreezing could peak and permanently decline starting in southwest Greenland by 2100, and further expanding GrIS-wide in the early 22nd century. After passing this peak, the GrIS contribution to global sea level rise would increase over twenty-fold compared to the last three decades

Recent surface mass balance from Syowa Station to Dome F, East Antarctica: comparison of field observations, atmospheric reanalyses, and a regional atmospheric climate model

Stake measurements at 2 km intervals are used to determine the spatial and temporal surface mass balance (SMB) in recent decades along the Japanese Antarctic Research Expedition traverse route from Syowa Station to Dome F. To determine SMB variability at regional scales, this traverse route is divided into four regions, i.e., coastal, lower katabatic, upper katabatic and inland plateau. We also perform a regional evaluation of large scale SMB simulated by the regional atmospheric climate model versions 2.1 and 2.3 (RACMO2.1 and RACMO2.3), and the four more recent global reanalyses. Large-scale spatial variability in the multi-year averaged SMB reveals robust relationships with continentality and surface elevation. In the katabatic regions, SMB variability is also highly associated with surface slope, which in turn is affected by bedrock topography. Stake observation records show large inter-annual variability in SMB, but did not indicate any significant trends over both the last 40 years for the coastal and lower katabatic regions, and the last 20 years record for the upper katabatic and inland plateau regions. The four reanalyses and the regional climate model reproduce the macro-scale spatial pattern well for the multi-year averaged SMB, but fail to capture the mesoscale SMB increase at the distance interval ~300 to ~400 km from Syowa station. Thanks to the updated scheme in the cloud microphysics, RACMO2.3 shows the best spatial agreement with stake measurements over the inland plateau region. ERA-interim, JRA-55 and MERRA exhibit high agreement with the inter-annual variability of observed SMB in the coastal, upper katabatic and inland plateau regions, and moderate agreement in the lower katabatic region, while NCEP2 and RACMO2.1 inter-annual variability shows no significant correlation with the observations for the inland plateau region

A comparison of Antarctic ice sheet surface mass balance from atmospheric climate models and in situ observations

In this study, 3265 multiyear averaged in situ observations and 29 observational records at annual time scale are used to examine the performance of recent reanalysis and regional atmospheric climate model products [ERA-Interim, JRA-55, MERRA, the Polar version of MM5 (PMM5), RACMO2.1, and RACMO2.3] for their spatial and interannual variability of Antarctic surface mass balance (SMB), respectively. Simulated precipitation seasonality is also evaluated using three in situ observations and model intercomparison. All products qualitatively capture the macroscale spatial variability of observed SMB, but it is not possible to rank their relative performance because of the sparse observations at coastal regions with an elevation range from 200 to 1000 m. In terms of the absolute amount of observed snow accumulation in interior Antarctica, RACMO2.3 fits best, while the other models either underestimate (JRA-55, MERRA, ERA-Interim, and RACMO2.1) or overestimate (PMM5) the accumulation. Despite underestimated precipitation by the three reanalyses and RACMO2.1, this feature is clearly improved in JRA-55. However, because of changes in the observing system, especially the dramatically increased satellite observations for data assimilation, JRA-55 presents a marked jump in snow accumulation around 1979 and a large increase after the late 1990s. Although precipitation seasonality over the whole ice sheet is common for all products, ERA-Interim provides an unrealistic estimate of precipitation seasonality on the East Antarctic plateau, with high precipitation strongly peaking in summer. ERA-Interim shows a significant correlation with interannual variability of observed snow accumulation measurements at 28 of 29 locations, whereas fewer than 20 site observations significantly correlate with simulations by the other models. This suggests that ERA-Interim exhibits the highest performance of interannual variability in the observed precipitatio