Abstract: The Correct Derivation Of Paleotemperatures From Ice Cores Requires Exact Knowledge Of All Processes Involved Before And After The Deposition Of Snow And The Subsequent Formation Of Ice. At The Antarctic Deep Ice Core Drilling Site Dome C, A Unique Data Set Of Daily Precipitation Amount, Type, And Stable Water Isotope Ratios Is Available That Enables Us To Study In Detail Atmospheric Processes That Influence The Stable Water Isotope Ratio Of Precipitation. Meteorological Data From Both Automatic Weather Station And A Mesoscale Atmospheric Model Were Used To Investigate How Different Atmospheric Flow Patterns Determine The Precipitation Parameters. A Classification Of Synoptic Situations That Cause Precipitation At Dome C Was Established And, Together With Back-trajectory Calculations, Was Utilized To Estimate Moisture Source Areas. With The Resulting Source Area Conditions (Wind Speed, Sea Surface Temperature, And Relative Humidity) As Input, The Precipitation Stable Isotopic Composition Was Modeled Using The So-called Mixed Cloud Isotope Model (Mcim). The Model Generally Underestimates The Depletion Of 18o In Precipitation, Which Was Not Improved By Using Condensation Temperature Rather Than Inversion Temperature. Contrary To The Assumption Widely Used In Ice Core Studies, A More Northern Moisture Source Does Not Necessarily Mean Stronger Isotopic Fractionation. This Is Due To The Fact That Snowfall Events At Dome C Are Often Associated With Warm Air Advection Due To Amplification Of Planetary Waves, Which Considerably Increases The Site Temperature And Thus Reduces The Temperature Difference Between Source Area And Deposition Site. In Addition, No Correlation Was Found Between Relative Humidity At The Moisture Source And The Deuterium Excess In Precipitation. The Significant Difference In The Isotopic Signal Of Hoarfrost And Diamond Dust Was Shown To Disappear After Removal Of Seasonality. This Study Confirms The Results Of An Earlier Study Carried Out At Dome Fuji With A Shorter Data Set Using The Same Methods.

Abstract:

Abstract. The isotopic compositions of oxygen and hydrogen in ice cores are invaluable tools for the reconstruction of past climate variations. Used alone, they give insights into the variations of the local temperature, whereas taken together they can provide information on the climatic conditions at the point of origin of the moisture. However, recent analyses of snow from shallow pits indicate that the climatic signal can become erased in very low accumulation regions, due to local processes of snow reworking. The signal-to-noise ratio decreases and the climatic signal can then only be retrieved using stacks of several snow pits. Obviously, the signal is not completely lost at this stage, otherwise it would be impossible to extract valuable climate information from ice cores as has been done, for instance, for the last glaciation. To better understand how the climatic signal is passed from the precipitation to the snow, we present here results from varied snow samples from East Antarctica. First, we look at the relationship between isotopes and temperature from a geographical point of view, using results from three traverses across Antarctica, to see how the relationship is built up through the distillation process. We also take advantage of these measures to see how second-order parameters (d-excess and ¹⁷O-excess) are related to ?¹⁸O and how they are controlled. d-excess increases in the interior of the continent (i.e., when ?¹⁸O decreases), due to the distillation process, whereas ¹⁷O-excess decreases in remote areas, due to kinetic fractionation at low temperature. In both cases, these changes are associated with the loss of original information regarding the source. Then, we look at the same relationships in precipitation samples collected over 1 year at Dome C and Vostok, as well as in surface snow at Dome C. We note that the slope of the ?¹⁸O vs. temperature (T) relationship decreases in these samples compared to those from the traverses, and thus caution is advocated when using spatial slopes for past climate reconstruction. The second-order parameters behave in the same way in the precipitation as in the surface snow from traverses, indicating that similar processes are active and that their interpretation in terms of source climatic parameters is strongly complicated by local temperature effects in East Antarctica. Finally we check if the same relationships between ?¹⁸O and second-order parameters are also found in the snow from four snow pits. While the d-excess remains opposed to ?¹⁸O in most snow pits, the ¹⁷O-excess is no longer positively correlated to ?¹⁸O and even shows anti-correlation to ?¹⁸O at Vostok. This may be due to a stratospheric influence at this site and/or to post-deposition processes.

Abstract: Sea ice variability within the marginal ice zone (MIZ) and polynyas plays an important role for phytoplankton productivity and krill abundance. Therefore, mapping their spatial extent as well as seasonal and interannual variability is essential for understanding how current and future changes in these biologically active regions may impact the Antarctic marine ecosystem. Knowledge of the distribution of MIZ, consolidated pack ice and coastal polynyas in the total Antarctic sea ice cover may also help to shed light on the factors contributing towards recent expansion of the Antarctic ice cover in some regions and contraction in others. The long-term passive microwave satellite data record provides the longest and most consistent record for assessing the proportion of the sea ice cover that is covered by each of these ice categories. However, estimates of the amount of MIZ, consolidated pack ice and polynyas depend strongly on which sea ice algorithm is used. This study uses two popular passive microwave sea ice algorithms, the NASA Team and Bootstrap, and applies the same thresholds to the sea ice concentrations to evaluate the distribution and variability in the MIZ, the consolidated pack ice and coastal polynyas. Results reveal that the seasonal cycle in the MIZ and pack ice is generally similar between both algorithms, yet the NASA Team algorithm has on average twice the MIZ and half the consolidated pack ice area as the Bootstrap algorithm. Trends also differ, with the Bootstrap algorithm suggesting statistically significant trends towards increased pack ice area and no statistically significant trends in the MIZ. The NASA Team algorithm on the other hand indicates statistically significant positive trends in the MIZ during spring. Potential coastal polynya area and amount of broken ice within the consolidated ice pack are also larger in the NASA Team algorithm. The timing of maximum polynya area may differ by as much as 5 months between algorithms. These differences lead to different relationships between sea ice characteristics and biological processes, as illustrated here with the breeding success of an Antarctic seabird.

Abstract: Spectral albedo of the snow surface in the visible/near-infrared range has been measured for 3 years by an automatic spectral radiometer installed at Dome C (75°?S, 123°?E) in Antarctica in order to retrieve the specific surface area (SSA) of superficial snow. This study focuses on the uncertainties of the SSA retrieval due to instrumental and data processing limitations. We find that when the solar zenith angle is high, the main source of uncertainties is the imperfect angular response of the light collectors. This imperfection introduces a small spurious wavelength-dependent trend in the albedo spectra which greatly affects the SSA retrieval. By modeling this effect, we show that for typical snow and illumination conditions encountered at Dome C, retrieving SSA with an accuracy better than 15?% (our target) requires the difference of response between 400 and 1100?nm to not exceed 2?%. Such a small difference can be achieved only by (i) a careful design of the collectors, (ii) an ad hoc correction of the spectra using the actual measured angular response of the collectors, and (iii) for solar zenith angles less than 75°. The 3-year time series of retrieved SSA features a 3-fold decrease every summer which is significantly larger than the estimated uncertainties. This highlights the high dynamics of near-surface SSA at Dome C.