Climatology of Stable Isotopes in Antarctic Snow and Ice: Current Status and Prospects

Review

Progress of Projects Supported by NSFC April 2013 Vol.58 No.10: 10951106 Oceanology doi: 10.1007/s11434-012-5543-y

Climatology of stable isotopes in Antarctic snow and ice: Current status and prospects

HOU ShuGui1,3*, WANG YeTang2* & PANG HongXi1

1 Key Laboratory for Coast and Island Development (Ministry of Education), School of Geographic and Oceanographic Sciences, Nanjing University, Nanjing 210093, China; 2 Shandong Provincial Key Laboratory of Marine Ecological Restoration, Shandong Marine Fisheries Research Institute, Yantai 264006, China; 3 State Key Laboratory of Cryospheric Science, Cold and Arid Regions Environmental and Engineering Research Institute, Chinese Academy of Sciences, Lanzhou 730000, China

Received May 28, 2012; accepted September 27, 2012; published online December 24, 2012

Stable isotopic composition in Antarctic snow and ice is commonly regarded as one of invaluable palaeoclimate proxies and plays a critically important role in reconstructing past climate change. In this paper we summarized the spatial distribution and the controlling factors of D, 18O, d-excess and 17O-excess in Antarctic snow and ice, and discussed their reliability and applicability as palaeoclimate proxies. Recent progress in the stable isotopic records from Antarctic deep ice cores was reviewed, and perspectives on bridging the current understanding gaps were suggested.

Antarctic Ice Sheet, D and 18O, d-excess, 17O-excess, snow and ice, climate change

Citation: Hou S G, Wang Y T, Pang H X. Climatology of stable isotopes in Antarctic snow and ice: Current status and prospects. Chin Sci Bull, 2013, 58: 1095 1106, doi: 10.1007/s11434-012-5543-y

Antarctic Ice Sheet is a highly important part of the Earth site providing an ice core which covers more than 700 ka system. Thanks to its extraordinary environment of very [5]. The robust couplings of dust-climate and CO2-climate low temperature, extremely low snow accumulation rate and over the glacial-interglacial timescales are also revealed by 18 thick ice layer, a wealth of high resolution and long chro- a comparison between D ( O) and the corresponding nology paleoclimatic information is stored, and hence Ant- dust and CO2 records from the same ice cores, taking ac- arctic Ice Sheet is honored as archives of the Earth’s climate. count of the ice core ice-age and gas-age difference [6–8]. Because the reliability of future climate prediction is, to a These results contribute significantly to our understanding great degree, dependent on our knowledge of the past cli- of the Earth’s climatic and environmental evolution during matic evolution, Antarctic ice core records play an im- the past hundreds of thousands years. A combination of D 18 18 portant role in the current global change studies. and  O (i.e. deuterium-excess or d-excess=D−8 O [9]) As one of most valuable and applicable climate proxies, provides a second-order stable isotopic information, which 18 stable isotopic composition (D,  O) recorded in Antarc- reflects the kinetic fractionation during evaporation. It largely tic ice cores is widely utilized to reconstruct the past climate depends on the sea surface temperature (SST), relative hu- 18 change. Particularly, D or  O in the Vostok and the EPICA midity and wind speed at the moisture source region [10,11]. Dome C ice cores have documented temperatures over the Therefore, d-excess in Antarctic snow and ice is generally past 400 ka and 800 ka BP (before present), respectively used to infer moisture source history, and to calibrate the 18 [1–4], which well reflects the glacial-interglacial change. A climatic interpretation of D and  O records. Recent de- drilling has successfully reached the bedrock at the Dome F velopment in the stable isotopic analysis technology makes 17 18 it possible to measure  O and  O with a high precision *Corresponding authors (email: [email protected]; [email protected]) [12,13]. Similar to d-excess, another second order parameter

17 6 17 O-excess, expressed as 10 ×(ln( O/1000+1)0.528ln depletion of the heavy stable isotopes from mid-latitudes to 18 18 ( O/1000+1)) [14], is developed as a new tracer of the hy- high latitudes, decline of D and  O from the coast to- 17 18 drological cycle. O-excess in atmospheric water vapor is ward Antarctic inland, and decreasing D and  O with strongly controlled by the relative humility [15], but insen- increasing elevation. 18 sitive to temperature and  O of the oceanic surface water Early attempts to represent the spatial stable isotopic dis- where moisture evaporates [16]. It therefore provides poten- tribution in Antarctic surface snow involved a continuous tial for Antarctic ice cores to retrieve singular meteorologi- trend surface generated by spatial interpolation technologies. cal information over the moisture origin region. However, Giovinetto and Zwally [19] and Zwally et al. [20] estab- monitoring and modeling of the stable isotopic fractionation lished a multiple linear regression model by investigating 18 exhibit modulation of the stable isotopic signals caused by the relationship between Antarctic surface snow  O data many processes (e.g., atmospheric circulation, firn process, vs. geographical and meteorological parameters including ice flow), which challenge the quantification of the past latitude, elevation, distance from coast and air temperature. 18 climatic change by means of the stable isotopic composition A 100-km resolution  O map was generated using this in Antarctic snow and ice. linear regression model and digital elevation model (DEM). This paper firstly summarized the spatial distribution of However, the accuracy of the maps was challenged by the the stable isotopic composition in Antarctic surface snow colinearity of predictor variables. Based on the recent com- and the factors controlling this distribution based on the pilation of the stable isotopic composition in Antarctic sur- stable isotopic observation and simulation. In particular, we face snow by Masson Delmotte et al. [21], Wang et al. [22] discussed the extent that the stable isotopic proxies can be modified the Bowen and Wilkinson (BW) model [23] and 18 used as a surrogate for climatic variables. Additionally, re- explored a quantitative relationship between  O in Ant- sults of the climate change reconstruction by the stable iso- arctic surface snow vs. latitude and altitude. This quantita- 18 topes in Antarctic deep ice cores were reviewed. In the last tive model integrating with the other factors affecting  O paragraph, perspectives on future development were offered. (e.g., moisture origin, moisture transportation paths) was 18 employed to produce a 1-km resolution gridded map of  O.

18 It is convinced by cross validation that generalized additive 1 Spatial distribution of D and  O model (GAM) is a useful tool to assess the spatial distribu- in Antarctic surface snow and the factors 18 tion of  O and D in Antarctic surface snow [24]. A 1-km controlling their variability 18 resolution gridded dataset of  O and D were produced 18 using high resolution DEM as an input for this model (Fig- 1.1 Spatial distribution of D and  O ure 1). The resulting stable isotopic distribution indicates An accurate assessment of spatial distribution of D and the effects of latitudinal, altitudinal, and continentality on 18O in Antarctic surface snow is required for the interpreta- the stable isotopes in precipitation. It is highly useful for the tion of Antarctic ice core stable isotopic records. However, comparison/validation with simulation of atmospheric gen- sufficient in situ observations are prerequisite for the as- eral circulation models (AGCMs) and mixed cloud isotopic sessment. Lorius and Merlivat [17] documented the rela- model (MCIM). 18 tionship between both D and  O and parameters such as the mean annual temperature and the surface elevation for 1.2 Factors controlling spatial distribution of D and sites in the sector between Dumont d’Urville and Vostok. 18  O Morgan [18] collected 18O measurements at 189 sites and constructed the first database of stable isotopic composition According to Rayleigh distillation model, Dansgaard [9] in Antarctic surface snow. In 1997, Giovinetto and Zwally summarized the factors controlling stable isotopes in mete- [19] updated this database by extending spatial coverage of oric precipitation, including temperature effect, latitude ef- 18  O measurements. In the following year, this database was fect, elevation effect, continental effect, moisture origin and updated again by Zwally et al. [20]. Most recently, Masson- so on. Previous studies have shown that air temperature is Delmotte et al. [21] compiled the most complete database of the key controlling factor in the mid and high latitudes, es- Antarctic surface snow stable isotopic composition using pecially in the polar region [9,25,26]. Masson-Delmotte et the available measurements of snowfall, surface snow, snow al. [21] confirms that the spatial distribution of stable iso- pit and shallow firn cores. This database constitutes the sta- topes in Antarctica is highly associated with condensation ble isotopic observations at 1279 sites since the 1960s, in- temperature, which itself is controlled by geographical pa- 18 cluding 938 D observations, 1125  O observations, and rameters (latitude, distance from the coast and elevation). 18 794 observations for both D and  O resulting in the Among these parameters, elevation is the first driver of the calculation of d-excess. Although there are still data gaps in spatial distribution of stable isotopes in Antarctica [24]. the Antarctic coastal regions and the East Antarctic plateau, Although temperature is the key factor controlling the the spatial distribution is essentially presented, including spatial distribution of stable isotopes in Antarctic snow, Hou S G, et al. Chin Sci Bull April (2013) Vol.58 No.10 1097

18 Figure 1 Spatial distribution of  O and D in Antarctic surface snow. Data come from [24]. several other factors such as moisture origin and transport of water isotopes over Antarctica through AGCMs. Hereafter, paths [27,28], precipitation seasonality/intermittency [29,30], with the enhancement of the capability to explicitly simulate and post depositional processes [31–33], might result in the water isotopes, a number of studies have attempted to large uncertainty when reconstructing paleotemperature from use AGCMs and MICM to evaluate the spatial and temporal ice cores. Precipitation falling in a target region over Ant- variability in Antarctic precipitation isotopes to better inter- arctica usually receives moisture from several different pret the stable isotopic records in Antarctic ice cores oceanic source regions. Changes of vapor source conditions [37–44]. AGCMs [37–43] and MICM [44] well reproduce and air mass transport may produce stable isotopic variabil- the spatial distribution of stable isotopes in Antarctic pre- ity, and changes of seasonality of Antarctic snowstorm in- cipitation, especially in West Antarctica and in the coastal tensity can precipitate a large fraction of air mass moisture, areas. Stable isotopic minima are located over the East Ant- and result in 2H- and 18O-depleted precipitation. Modeling arctic Plateau where the lowest temperature is observed. attempts also highlight the importance of precipitation sea- However, the modeling 18O values over the East Antarctic sonality/intermittency on stable isotopic variation [34,35]. Plateau were overestimated by even 10‰ in relative to real Stable isotopic signals can be smoothed by diffusion in firn observations [38,39,43]. Although development in the ver- and ice during the densification process after snow deposi- tical and horizontal resolution of AGCMs largely improved tion. In addition, spatial difference in stable isotopic com- their accuracy in recent years, its simulation ability remains position may result from sublimation effects over Antarctic limited for the Antarctic inland (Figure 2(a) and (b)) [42], inland and wind-driven ablation on the flanks of the Antarctic likely due to poor representation of atmospheric boundary Ice Sheet. layer, temperature inversion, cloud microphysics, and large scale advection of water vapor [36,45]. Warm biases of

18 AGCMs could result in the insufficient estimate of the sta- 1.3 Modeling the spatial distribution of  O and D ble isotopic depletion. A Rayleigh distillation model (RM) [11,36] has the advantage of representation of key microphysical processes 2 Relationship between the stable isotopic and the fractionation along the water cycle path. Thus, this type of model simulates quite satisfyingly the dependence composition () and temperature (T) of stable isotopes in precipitation on atmospheric parame- (-T relationship) ters, moisture origin diagnostic and air mass trajectories. These simulation results provide a theoretical basis for in- The basis of paleotemperature reconstruction is the strong terpretation of the ice core stable isotopic records. However, relationship between the stable isotopic composition in the modeling air parcel trajectories are strongly simplified. Antarctic surface snow and temperature on varied temporal AGCMs and MICM has the advantage of estimating spatial scales. Picciotto et al. [46] quantified a temporal relation- 18 and temporal variation of stable isotopes. Jouzel et al. [37] ship between  O in snowfall and the corresponding cloud provides the first estimate of an annual average distribution temperature from measurements at the Roi Baudouin Station 1098 Hou S G, et al. Chin Sci Bull April (2013) Vol.58 No.10

Figure 2 (a) Spatial distribution of D simulated by ECHAM5 [41] and observations [22]; (b) a comparison of D observations and simulation by ECHAM5. at the coastal Antarctic Ice Sheet. On seasonal scale,  cor- Expedition (Table 1). Zhang et al. [53] observed different relates linearly with T at Dome F [47], Vostok [48], Dron- spatial slopes over the East and West Lambert Glacier (Ta- ning Maud Land [49] and west Antarctic ice divide [50]. ble 1). Regional difference in the spatial slopes is also ob- However, the -T temporal slopes vary significantly from served over Dronning Maund Land [54], nearby Dome C one site to another. On longer temporal scales, -T relation- [4], and along the traverse from the Zhongshan Station to ships can be hardly explored from the short instrumental Dome A [55]. Based on the most complete compile of the stable isotope and temperature measurements over Antarc- stable isotopic composition in Antarctic surface snow, Masson- tica. Also, no good independent proxy can capture the Delmotte et al. [21] explored -T relationships at continental long-term Antarctic -T relationship. Jouzel et al. [51] indi- and regional scales. For the whole continent, the spatial cated that AGCMs is regarded as a good alternative to de- slopes are 0.80±0.01‰/°C (n=745) for 18O-T, and 6.34± tect the long-term -T temporal relationships. 0.09‰/°C for D-T. However, the regional slopes vary by Lorius and Merlivat [17] firstly explored the 18O-T and 20% or more [21], which can be simulated by MICM [44] D-T spatial relationships using surface snow 18O, D, and and GCMs [56]. annual mean temperature measurements along a traverse Stable isotopes in precipitation represent not only local from the Dumont d’Urville Station to Dome C. Qin et al. [52] conditions where precipitation occurs, but also a combina- reported changes in regional -T spatial gradients by ana- tion of source conditions, rainout, and post-deposition pro- lyzing the -T relationships over the different geographic cesses. Thus, local -T temporal relationship is usually sections along the International Trans-Antarctic Scientific slowly weakened than the -T spatial relationship [29,41,57].

Table 1 Regional -T gradients in Antarctica

Area 18O-T slope (‰/°C) D-T slope (‰/°C) Reference Dumont d’Urville Station-Dome C 0.76 6.00 [17] Patrot Hills-Vostok 0.77 5.84 [52] Komsomolskaya-Mirnyy 0.90 7.00 [52] Amundsenisen 0.77±0.14  [54] Dome C 0.75±0.15 6.04 [4] Transect between Zhongshan Station and Dome A 0.84  [55] Western Lambert Glaicer Basin 0.84  [53] Eastern Lambert Glacier Basin 0.58  [53] Western Vostok region 0.89±0.11 7.00 [52] Eastern Vostok region 0.89±0.039 5.84 [52] Antarctic Ice Sheet 0.80±0.01 6.34±0.09 [21]

Hou S G, et al. Chin Sci Bull April (2013) Vol.58 No.10 1099

Furthermore, significant regional anomalies in stable iso- -T spatial slope as a surrogate for temporal slope. topes usually occur, resulting from atmospheric circulation variability. Though -T spatial relationship is used as a sur- 17 rogate of -T temporal relationship to quantify the past tem- 3 d-excess and O-excess in Antarctic snow perature from ice cores [58], this method is questioned for and ice the interpretation of glacial-interglacial stable isotopic vari- 3.1 Spatial distribution of d-excess and its controlling ations over Greenland likely due to the glacial-interglacial factors change in the seasonality of precipitation [59]. Due to limited topographical and geographical changes between gla- d-excess in precipitation reflects the stable isotopic kinetic cial and interglacial climates, Antarctica is less affected by fractionation when water phase changes. Jouzel and Merlivat such changes in seasonality; this gives arguments for the [11] firstly theoretically revealed the dependence of d-excess validity of temperature reconstruction on glacial-interglacial on SST controlling the saturated vapor pressure, relative scale from the Antarctic interior ice cores, such as Vostok, humidity controlling the vapor diffusion rate and wind Dome F and EPICA Dome C, with their uncertainties up to speed affecting the turbulent transport processes in the oce- 20%–30% [60], which to great extents result from the re- anic source regions. Armengaud et al. [68] further con- gional changes in -T spatial slopes [21]. Additionally, firmed the control of kinetic evaporation conditions in the changes in oceanic moisture origin conditions [27,28,60], moisture source region on d-excess. Furthermore, there are precipitation seasonality/intermittency [35,38,39,61], Ice robust correlations between d-excess in atmospheric vapor Sheet elevation [62,63], and atmospheric circulation may and SST and relative humidity in the mid-high altitude influence -T relationship, especially during the abrupt cli- Southern Oceans [69]. As a result, d-excess is considered as mate change. Jouzel et al. [60] pointed out the necessity of a good tracer for moisture origin. making corrections for the impact of ocean stable isotopic Spatial distribution of d-excess in Antarctic snow and ice change when interpreting the ice core stable isotopic records. exhibits a distinct difference between Antarctic coastal re- Lee et al. [64] quantified the influence of changes in the gions below 2000 m and Antarctic interior above 2000 m. moisture source conditions on -T correlation during the d-excess values change little for the coastal regions, while increase evidently for Antarctic interior, with the highest Last Glacial Maximum through AGCM. The -T temporal values over the East Antarctic plateau [21,70,71]. Statistic slope at East Antarctica is about 50% of the -T spatial analysis shows that d-excess correlates positively with alti- slope because of the modulation of seawater stable isotopic tude and distance from Antarctic coasts, and negatively with content in the Southern Ocean. By making use of ERA40 temperature for the whole Antarctic Ice Sheet, especially for (1980–2002) reanalysis data, Masson-Delmotte et al. [65] Antarctic interior above 2000 m [21]. Results of RM [70] calculated the difference between temperature and precipi- and AGCM [21] demonstrated that difference in moisture tation-weighted temperature to investigate the effect of pre- sources accounts for the discrepancy of d-excess spatial cipitation seasonality/intermittency on -T correlation. In distribution between the Antarctic coastal and inland re- the East Antarctic interior, biases of stable isotopic ther- gions. Antarctic coastal regions receive moisture mostly mometer result largely from precipitation seasonality. But in from offshore waters, whereas in Antarctic interior, mois- the other Antarctic regions, especially the coastal regions, ture originates mostly from open sea, which is supported by the synoptic variation in precipitation contributes more to a Lagrangian moisture source diagnostic [72] and air mass biases than precipitation seasonality. The importance of trajectory tracking model [73]. Additionally, d-excess is precipitation intermittency is also highlighted by modeling sensitive to changes in stable isotopic equilibrium fractiona- attempts [35,38,39,61]. Sime et al. [56] simulated the stabil- tion temperature. Gradual decrease in condensation temper- ity of -T correlation in response to increase in greenhouse ature during the moisture transport from the Southern Oce- gas concentrations, and showed a slowly weaker -T tem- anic regions towards Antarctica results in the increase of poral slope than -T spatial slope at Dome F and EDML, d-excess in vapor and reaches the highest value in Antarctic and a significantly weak temporal slope equivalent to 40% interior. Atmospheric vapor during polar snow formation is of the spatial slope nearby Dome C and Vostok, resulting generally supersaturated due to rather low temperature, from changes in precipitation intermittency under warmer leading to kinetic fractionation for ice crystals. The kinetic climates. Schmidt et al. [66] used a coupled ocean-atmos- fractionation is more vigorous as temperature decreases, phere model equipped with stable isotopic fractionation to resulting in increase of d-excess. Besides, depth hoar within detect the -T temporal relationship during mid-Holocene, snowpack growing from vapor sublimation may cause in- in response to changes in orbital forcing and greenhouse gas crease of d-excess [74], while material loss during firnifica- concentrations. The -T temporal slope over eastern Antarc- tion in regions with low accumulation rate may lead to dec- tica is 0.2–0.5‰/°C lower than the present-day -T spatial rement of d-excess [32,33]. d-excess in Antarctic snow and slope. Therefore, Sime et al. [67] concluded that interglacial ice is also influenced by the stable isotopic diffusion after temperature was badly underestimated by means of modern snow deposition, generally accompanying with the stable 1100 Hou S G, et al. Chin Sci Bull April (2013) Vol.58 No.10 isotopic kinetic fractionation. Therefore, it is clear that ice could be also affected by mass-independent oxygen iso- d-excess in Antarctic snow and ice depends largely on the topic fractionation of tropospheric vapor [83] and kinetic conditions of moisture source (SST, relative humidity, sta- isotopic fractionation during ice crystal formation under the ble isotopic composition of ocean water and wind speed), supersaturation conditions [11,15]. In general, vapor in but importance of condensation temperature at precipitation cloud in East Antarctic interior is in a supersatured envi- site [75], the supersaturation of vapor [11] and post-deposi- ronment due to extreme low temperature and it could be tional processes [32,33] cannot be ignored. Moreover, the condensed directly into ice crystal. The condensation pro- degree of influence from these parameters varies from one cesses accompanying the stable isotopic kinetic fractiona- site to another [21,76]. As a result, it is not easy to obtain tion have an evident impact on 17O-excess in snow and ice. quantitative information of meteorological conditions over RM results indicate the different responses of d-excess and moisture source by d-excess. Consequently, it is required to 17O-excess to the kinetic fractionation during ice crystal take into account the disturbance of non-moisture source formation under the supersaturation conditions, with signif- conditions when retrieving moisture source information by icant d-excess increase and 17O-excess decrease with increase means of d-excess in Antarctic snow and ice. The ap- of the vapor supersaturation degree as temperature decreases proaches for the calibration of interpretation of d-excess [15]. Therefore, combination of d-excess and 17O-excess is include modeling methods (e.g. the kinetic fractionation advantageous for understanding the stable isotopic kinetic model under the supersaturation conditions during snow fractionation processes during ice crystal formation under formation [11] and the stable isotopic diffusion model [77]), the supersatured environment. The above analyses suggest empirical formula [78] and 17O-excess. that the climatic information on moisture source regions could be inferred from the ice core 17O-excess records, 3.2 17O-excess record which would provide a more direct indicator than d-excess for the climatic signature of the first vapor. However, 17O- Triple stable isotopic composition of oxygen in atmospheric excess in remote sites of East Antarctica may be highly sen- vapor collected over the Southern Oceans show that 17O- sitive to local effects and getting additional information from excess in vapor is mainly controlled by the relative humidi- this parameter is probably more reliable for coastal sites [82]. ty over moisture source [79]. In comparison with d-excess, 17O-excess is independent of SST and water 18O in oceanic regions [15] and depends hardly on the condensation tem- 4 Temperature reconstruction from stable perature during vapor transport [16]. 17O-excess is therefore isotopes in Antarctic deep ice cores not only a tracer for the relative humidity over oceanic source regions, but also can be used to make corrections for Temperature reconstruction is an essential part of past glob- the influence of non-moisture source conditions on d-excess al change research [84]. Stable isotopes archived in Antarc- in precipitation. At the NEEM (North Greenland Eemian tic deep ice cores have drawn especial attention. During the Ice Drilling) of Greenland, simultaneous measurements of past decades, several ice cores have been drilled in Antarc- 17O and 18O in atmospheric vapor vs. precipitation vali- tica (Figure 3 and Table 2). The depths of ice cores at dated firstly the theoretical coefficient of meteoric water line for 17O and 18O, and showed that seasonal variation of 17O-excess is in phase with relative humility over oceanic source regions [80]. 17O-excess is therefore regarded as a potential tool for reconstructing relative humidity over moisture source. Measurements of 17O-excess in surface snow along a transect from Terra Nova Bay to Dome C and Vostok [16] did not reveal an apparent trend along this transect. 17O-excess of the Vostok ice core increases by 20‰ from the Last Glacial Maximum (LGM) to Early Hol- ocene (EH), which could be explained by 20% decrease in the relative humidity at the oceanic source regions. Howev- er, this is not supported by AGCM simulations [81]. During the same period, 7O-excess of the Dome C ice core shows a reverse trend in comparion to the Vostok ice core, and there is no significant change in 17O-excess of the Talos Dome ice core [82]. The moisture origin diagnostic model, RM and MCIM, show that the spatial discrepancy of 17O-excess is largely associated with relative humidity over moisture source [82]. Nevertheless, 17O-excess in Antarctic snow and Figure 3 Locations of the deep ice cores in Antarctica. Hou S G, et al. Chin Sci Bull April (2013) Vol.58 No.10 1101

Table 2 Basic information of the deep ice cores in Antarctica

Distance from Accumulation rate Air temperature Ice core depth Sites Latitude Longitude Altitude (m) Reference coast (m) (mm a1) (°C) (m) Vostok 78°28′S 106°48′E 3490 1260 23 55.5 3623 [1] Taylor Dome 77°48′S 158°43′E 2365 120 50 to 70 43 554 [85] Byrd 80°01′S 119°31′W 1530 620 100 to 120 28 2164 [86] Law Dome 66°46′S 112°48′E 1370 90 700 22 1195.6 [87] Dome F 77°19′S 39°40′E 3810 1000 23 57 3035.2 [2] Talos Dome 72°47′S 159°04′E 2315 250 80 40.1 1620 [88] EPICA Dome C 75°6′S 123°21′E 3233 912 25 54.5 3259.7 [4] EDML 75°00′S 00°04′E 2822 577 64 44.6 2774 [89] Siple Dome 81°40′S 148°49′W 621 439 124 24.5 1003 [90]

Vostok, EPICA Dome C and Dome F are over 3000 m, with concentration and air temperature over the MIS (Marine their bottom ice ages over hundreds of thousands of years. Isotope Stage) 5e recorded in the Vostok ice core could not These ice cores are uniquely advantageous for the determi- be explained by the Milankovitch theory. Furthermore, nation of climatic evolution on the millennial to orbital Laepple et al. [94] argued that the temperature retrieved timescales. Ice cores recovered from the Antarctic coastal from the stable isotopic records of the Vostok, Dome C and regions with relatively higher snow accumulation could Dome F ice cores tends to reflect changes of the winter provide high resolution records, which can be used to deci- temperature in the southern hemisphere because of season- pher details of climate change on the decadal to millennial ality of the Antarctic snow accumulation, and that the glacial- timescales. interglacial cycle of local changes in the solar radiation play a decisive role, regardless the summer solar radiation at 4.1 Temperature change at orbital timescale high latitude in northern hemisphere. The most prominent feature of the glacial-interglacial cy- Four complete glacial-interglacial temperature cycles were cle is the shift of the dominant cycles from 40 ka to 100 ka identified by the stable isotopic records (18O and D) of the occurring around 900 ka. This climatic shift event is called Vostok ice core [1]. This record is extended back to the past the Mid-Pleistocene climate transition (MPT), which has been 800 ka by the EPICA Dome C ice core, with eight glacial- found in the benthic stable oxygen isotopic records [95] and interglacial cycles [3,4]. Both ice cores decipher the 100 ka, verified by the loess-paleosoil stable isotopic profiles [96]. 40 ka and 19–23 ka cycles driven by the earth orbital pa- The MPT seems to be reflected in the stable isotopic record rameters, and the 100 ka periodicity is dominant. Neverthe- of the EPICA Dome C ice core [4]. Although many as- less, the fluctuation magnitude and the duration of the peri- sumptions concerning to the greenhouse effect were used to odicities show a little decrease during the period 800–430 explain MPT, its intrinsic mechanism has not been clarified ka BP compared with those during the period 0–430 ka BP. so far. Because of ice cores as a unique medium that can be Within each glacial-interglacial cycle, the duration of the used to retrieve directly the ancient atmospheric composi- glacial condition accounts generally for more than 80% of tion, together with its precise dating, high temporal resolu- the glacial-interglacial cycle, whereas the interglacial condition and good continuity, ice cores with an age more than tion for less than 20%. The duration for the interglacial is one million years are extremely crucial for verifying MPT. about 10–30 ka. The stable isotopic records of the ice cores Consequently, seeking such kind of old ice cores from Ant- at EPICA Dome C [3], Dome F [2] and Vostok [1] show a arctica is of vital importance, which is also one of the pri- synchronous climate change during the past 400 ka over the mary goals of the International partnership Ice Core Sci- East Antarctica (Figure 4). Records of Loess [91] and ma- ences (IPICS). Dome A, the highest point of the Antarctic rine [92] sediments also show a similar glacial-interglacial ice sheet, is characterized by the lowest annual average tem- cycle, suggesting a synchronization of global climate change perature (58°C) [97], low accumulation rates (<25 mm/a on orbital timescale, reflecting the periodic variations of the water equivalent) [98,99], neglectable ice flow velocity and earth’s orbital parameters. According to Milankovitch the- exceeding 3000 m ice thickness [100], meets the necessary ory, the main driving factor for the glacial-interglacial cycle conditions for retrieving such very old ice cores [101]. of climate is the amount of summer solar radiation received by the Earth at high northern latitude [93]. The signal of the 4.2 Temperature change at millennial to sub-millennial summer solar radiation is conveyed through variations of timescales greenhouse gas concentration and thermohaline circulation intensity. Nevertheless, the synchronous increase of CO2 Because millennial to sub-millennial climate change and 1102 Hou S G, et al. Chin Sci Bull April (2013) Vol.58 No.10

Figure 4 Records of the stable isotopic profiles of Dome F [2], Dome C [3] and Vostok [1] ice cores and their corresponding reconstructed temperature time series. abrupt climate change events are particularly important to Phase relationship of the bipolar climate events is essen- the prediction of future climate, they attract great concerns tial for understanding the climate system coupling of the even beyond the earth science community, especially for the northern and southern hemispheres and its interaction climate change during the last glacial-interglacial cycle. mechanism. A series of abrupt climate change events lasting A comparison of climate between the last interglacial and several centuries to several thousand years were identified the Holocene was made by Massion-Delmotte et al. [65] by the Greenland ice cores, from which standing out the 18 from six deep Antarctic ice core  O records. They identi- Dansgaard/Oeschger (DO) [102,103] and the Younger Dry- fied a similar pattern of the stable isotopic records of these as (YD) [104] events. On the contrary, Antarctic climate is ice cores during the last interglacial and the Holocene, sug- relatively moderate, with a certain climate warming events gesting a consistent Antarctic temperature change on mil- of 1–3°C, called the Antarctic Isotope Maxima events (AIM) lennial scale. However, there are regional magnitude dif- [2,3,105]. Although the YD event was not observed in the ferences of the stable isotopic variation, probably due to Antarctic ice core reocrds, the Antarctic Cold Reversal difference in moisture sources, altitude evolutionary history (ACR) was identified before the occurrence of the YD event of the local ice sheet, seasonal changes in precipitation or [106,107]. In order to ascertain the phase relationship of intermittent precipitation. During the last deglaciation, the these events over the bipolar regions, the age scale of the synthetic 18O record [87] from the Antarctic coastal Law Greenland and the Antarctic ice cores were synchronized by Dome [87], Talos Dome[88], Simple Dome [90], EDML their corresponding CH4 records, demonstrating a biploar [89] and Byrd [86] ice cores is rather accordant with the seesaw between the millennial ACR events observed in 18O record of the EPICA Dome C ice core (Figure 5(a)), Antarctica and the DO events in Greenland during the MIS further confirming the uniformity of Antarctic temperature 2–4 periods [86]. During MIS 3, all the AIM events corre- change on millennial scale. However, regional difference in spond one-to-one to the DO stadials of Greenland [89] the warming rate from the last glacial to Holocene is signif- (Figure 5(b)). The coldest ACR event occurred during 14.4– icant [88]. It’s interesting to point out that the stable isotop- 12.9 ka BP, corresponding to the Bølling warm event in ic record of the Taylor ice core from the Coast of Ross Sea Greenland, and an Antarctic warming is in response to the [85] during the last deglaciation corresponds reversely to timing of Allerød cold event in Greenland [87] (Figure 5(c)). that of the ice cores mentioned above, but Stenni et al. [88] The bipolar seesaw of climate change was suggested to be indicated the dating lethality of the Taylor core [88]. related to the ocean’s Meridional Overturning Circulation Hou S G, et al. Chin Sci Bull April (2013) Vol.58 No.10 1103

Figure 5 (a) Comparisons of the 18O records of the GRIP, Law Dome, Siple Dome, EDML and Talos Dome ice cores since LGM. The dataset are from reference [87]. (b) A one-to-one coupling of the Antarctic warming events (AIM) vs. the Greenland DO events [89]. (c) A comparison between the Antarctic δ18O composite from the Law Dome, Siple Dome, EDML and Talos Dome ice cores and the North Greenland (NGRIP) 18O record [87].

(MOC) [108,109]. sea interface and during the vapor transport would help to understand the dynamic mechanism of the stable isotopic fractionation processes in vapor at the air-sea interface, 5 Summary and outlook changing conditions over water vapor source and the influence of vapor transport on the stable isotopes in snow and In summary, temperature is the main controlling factor for ice. Additionally, simultaneous observations of stable iso- 18 the spatial distribution of the stable isotopes (D and 18O) topes (D and  O) in atmospheric vapor above the land- in Antarctic surface snow and ice. However, the distribution atmosphere interface (near ground) and in surface snow are can be influenced, to a certain degree, by precipitation sea- helpful to understand the impact of post-depositional pro- sonality, moisture source, vapor transport, and post-deposi- cesses on the stable isotopes. tional processes, resulting in uncertainty to reconstruct past Progress in paleoclimatology depends largely on the climate change by the stable isotopic records of the Antarc- quality and applicability of the paleoclimate proxies. Due to tic ice cores. To discern the disturbance of these factors, the complexity of the stable isotopic fractionation, the re- further monitoring and modeling efforts on the modern sponse of the stable isotopes in Antarctic snow and ice to processes of the stable isotopes are very important, espe- temperature differs spatially and temporally, resulting in cially the observation of the stable isotopic composition in uncertainties of the temperature reconstruction based on the atmospheric vapor and its variation during transport towards Antarctic ice cores. Such uncertainties may be partly solved Antarctica. Evaporation from the ocean surface is the first by understanding the mechanisms of spatial and temporal stage for the Antarctic precipitation, with the initial stable variabilities in -T relationship through in-situ observations isotopic fractionation in vapor over the moisture source. and numerical simulations. Quantitative comparison of the Precipitation gradually falls during vapor transport towards -T relationship variabilities driven by variable forcings, Antarctica under a certain conditions of temperature, pres- such as changes in greenhouse gas concentration, orbital sure and humidity, together with regular stable isotopic parameters, freshwater infiltration and changes in ice sheet fractionation. In-situ and real-time measurements of the elevation is beneficial. On the East Antarctic Plateau, in stable isotopic composition in atmospheric vapor at the air- addition to the conventional snow precipitation, ice crystal 1104 Hou S G, et al. Chin Sci Bull April (2013) Vol.58 No.10

(diamond dust) or clear-sky precipitation is another im- The stable isotopic records of Antarctic ice cores reveal a portant type of precipitation, which is related to the degree homogeneity of temperature variation on millennial time- of vapor supersaturation under the very low temperature scale but with regional differences in the magnitude of vari- conditions. Though this type of precipitation may have an ations. High resolution ice core records and simulations are impact on -T relationship, this has not attracted much at- urgently needed to decipher the spatial discrepancy and its tention. driving mechanism. Additionally, ice cores from both Ant- 17O-excess and d-excess are two important tracers for arctica and Greenland with sound chronology quality and identifying conditions over moisture source. In comparison enough high resolution are crucial for studying the phase with d-excess, 17O-excess is mainly controlled by the rela- relationship of bipolar climate change. tive humidity over moisture source and has different response manner to the stable isotopic kinetic fractionation under the supersaturation conditions. 17O-excess in snow This work was supported by the National Natural Science Foundation of China (41171052, 40825017, 41206175 and 41176165), the State Oceanic and ice shows great potential for quantitative recovery of Administration (CHINARE2012-02-02) and Ministry of Education single meteorological information about vapor source. It (20110091110025 and 1082020904). 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