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Map of Greenland with NGT ice cores (B16–B23, B26– B30 crosses), deep drilling sites (crosses) and towns (black dots). The ice surface topography is according to Bamber et al. (2013), (mapping: Polar Stereographic (WGS84), Standard Parallel 71, Latitude of Projection Origin − 39).
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We present for the first time all 12 d18O records obtained from ice cores drilled in the framework of the North
Greenland Traverse (NGT) between 1993 and 1995 in northern Greenland. The cores cover an area of 680 km2317 km, 10% of the Greenland ice sheet. Depending on core length (100–175 m) and accumulation rate (90–200 kg m-2 a-1) the single reco...
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... the isotope signal is altered by post-depositional processes like wind-induced redistribution of snow, temperature gradient metamorphism and diffusion (Johnsen et al., 2000; Pinzer et al., 2012; Steen-Larsen et al., 2014). Stacked records are used to compensate for effects due to local to regional differences and to improve the signal-to-noise ratio (Fisher et al., 1985; Masson-Delmotte et al., 2015; White et al., 1997). To date, most ice core studies on the Greenland ice sheet have been carried out point-wise (e.g., Dye 3, GRIP, GISP2, NGRIP), which begs the question of how representative one single long ice core record is for deriving a comprehensive record of past climate. A study of ice cores from southern Greenland revealed that winter season stable water isotopes are largely influenced by the North Atlantic Oscillation (NAO) and are strongly related to southwestern Greenland air temperatures. On the other hand, summer season stable water isotope ratios show higher correlations with North Atlantic sea surface temperature conditions (Vinther et al., 2010). In particular, northern Greenland has been little investigated so far. The summit in Greenland’s center is the highest site and separates Greenland into a northern and southern part. Northern Greenland differs significantly from the south in terms of lower air temperatures and lower snow accumulation rates (Fischer et al., 1998c). Thus, the results from southern Greenland are not directly transferable to the northern part. Northern Greenland’s climate is influenced by different effects than the southern part. One example is the NAO effect, which is present in the southern and western part of Greenland and is discussed to be reduced in northern Greenland (Appenzeller et al., 1998). The cyclones causing the precipitation over northern Greenland originate in the Baffin Bay and bring dry and cold air masses from the central Arctic to northern Greenland (Chen et al., 1997). The dominant westerly winds are blocked by the ice divide, while the northeastern part has very low accumulation rates below 100 kg m − 1 a − 1 . The topographic situation in northern Greenland is special for δ 18 O studies. In northern Greenland going northward also means to go downward (lower altitudes). For a correct estimate of mass balances as well as the response to the ongoing climate change, knowledge of accumulation rates and the spatial distribution of δ 18 O as a temperature proxy is important for the entire Greenland ice sheet. However, due to northern Greenland’s remoteness its recent past climate has, up to now, been only scarcely investigated. Even in the 1990s little was known about northern Greenland. Only few studies had been performed before the Alfred Wegener Institute’s (AWI) North Greenland Traverse (NGT) started in 1993. There had been a traverse by Koch and Wegener in 1913 (Koch and Wegener, 1930) and one by Benson in 1952–1953 (Benson, 1962), and there was the British North Greenland Expedition in 1958 (Bull, 1958), which studied the accumulation rate in northern Greenland. How- ever, there had been no stable water isotope studies in the central part of northern Greenland. Fischer et al. (1998c) and (Schwager, 2000) present the first results from δ 18 O values of some of the NGT records. Using the updated accumulation rates of the (compared to Friedmann et al., 1995; Schwager, 2000) NGT, it was possible to show that the area of lower accumulation rates is much larger than expected before, which has an influence on the outlet glaciers (Weißbach et al., 2015). The NGT ice cores offer, for the first time, the possibility to study the spatial and temporal variability in stable oxygen isotope records from northern Greenland. Furthermore, they allow the analysis of the common spatial stable water isotope signal in northern Greenland by stacking the individual records to significantly reduce the isotopic noise that is present in a single record due to local peculiarities. The main objectives of this study are (1) to investigate the spatial variability in δ 18 O in northern Greenland using this new set of δ 18 O data and to evaluate the influence of isotopic noise on a single record, (2) to assess whether stable water isotope records from sites with low accumulation rates can be interpreted as climate signals, (3) to present a new robust stacked δ 18 O record for northern Greenland covering the past millennium, and (4) to interpret this record in terms of pale- oclimate with respect to temporal variability and relation to large-scale climate information from other proxy records. The ice cores presented here were drilled during the NGT from 1993 to 1995. In total, 13 ice cores (B16-B23, B26- B30) from 12 different sites (Table 1, Fig. 1) were drilled along the traverse route. The ice cores cover the last 500– 1000 years. The drillings were accompanied by extensive surface snow studies (e.g., Schwager, 2000). B21 and B23 as well as B26 to B30 are located on ice divides (Fig. 1), while B16–B20 were drilled east of the main ice divide. The NGRIP core (North Greenland Ice Core Project Members, 2004) was drilled 14.5 km northwest of B30 following the main ice divide and is therefore included in this study. Before analyzing the stable water isotopes, a density profile of each core was measured. To do so, the single core seg- ments (approximately 1 m long) were weighed in the field. Additional higher-depth-resolution density records were determined using gamma-absorption measurements in the AWI cold lab (Wilhelms, 1996). Finally, in 2012, density of the first 70 m of the three cores B19, B22 and B30 was analyzed by X-ray computer tomography (X-CT; Freitag et al., 2013). An exponential function fitted to the data taking into account all three types of density data with same respect was used to calculate water equivalent (w.e.) accumulation rates and to synchronize the cores. Selected parts of B30 were also analyzed for electrolytic conductivity using high-resolution continuous-flow analysis (Kaufmann et al., 2008). For the isotopic measurements the ice was cut into samples of 1–5 cm depth resolution, corresponding to 2–10 samples per year. Most of the ice was sampled with 2–2.5 cm depth resolution. Only at the uppermost parts of the core were samples cut with lower depth resolution (up to 5 cm). For some meters of special interest a resolution of 1 cm was used. After melting, δ 18 O was determined using Delta E and S mass spectrometers from Finnigan MAT in the AWI labo- ratory with uncertainties less than 0.1 ‰ as determined from long-term measurements. Cores B27 and B28 were drilled at the same site. Parts of core B27 (8.25–11.38 m w.e.), corresponding to AD 1926–1945) were lost, and these were re- placed by the record from B28. For the other parts, the mean of both dated cores was calculated to generate one isotope record for this site. Six of the NGT cores (B16, B18, B20, B21, B26 and B29) were already dated up to a certain depth by annual layer counting (using density, major ions or δ 18 O) in prior studies (e.g., Fischer and Mieding, 2005; Fischer et al., 1998a, b; Schwager, 2000). Depending on the availability of data and differences in snow accumulation rates the dating quality of these cores varies between 1- and 5-year accuracy. For the other NGT cores annual layer counting was not possible due to the very low accumulation rates (< 100 kg m − 2 a − 1 ). To achieve the same dating quality for all NGT cores for better comparison and to apply the dating on the whole core length, we used a new dating procedure for all cores. From density-corrected (w.e.) high-resolution electrical conductivity profiles (Werner, 1995; Wilhelms, 1996) and SO 2 4 − concentration profiles for B16, B18, B21 (Fischer et al., 1998a, b), B20 (Bigler et al., 2002) and an electrolytic conductivity profile (B30), distinct volcanic horizons were iden- tified and used as match points to synchronize the cores (Table 2). Some of the volcanic eruptions show a more pronounced signal in the Greenlandic ice than others. Thus not all eruptions could be identified in every record. Between match points, the annual dating was assigned assuming a constant snow accumulation rate. If a volcanic match point could not be clearly identified in an ice core, the next time marker was used to calculate the mean accumulation rate. Below the deepest volcanic match point, the last calculated accumulation rate was extrapolated until the end of the core. As the cores were drilled only in the upper part of the ice sheet (up to 100–175 m depths), layer thinning was not taken into account. The last millennium was a volcanically active time (Sigl et al., 2013). The volcanic aerosols deposited on the Greenland ice sheet can be used as time markers. The depths of peaks in conductivity and sulfate concentration attributed to certain volcanic horizons are given in Table 2 as used for our dating approach. During the last 500 years, the time period between two de- tectable eruptions at NGT sites does not exceed 100 years for any of the cores. This leads to a dating uncertainty for each core of smaller than 10 years compared to the annually counted timescales (Mieding, 2005; Schwager, 2000), which is minimal at the matching points. The three youngest volcanic reference horizons (Katmai, Tambora and Laki) and the eruptions from AD 1257 (Samalas; Lavigne et al., 2013) and AD 934 (Eldgjá) were found in all cores, whereas the other eruptions could not be clearly identified in every ice core. We could not find a common pattern (e.g., distance, strength of the eruption) regarding whether or not volcanic horizons could be observed in all records. This already indicates a high spatial variability within the study region related to significant influences of local to regional peculiarities (e.g., wind drift or sastrugi formation). An overview of the resulting mean accumulation rates for the entire core lengths for all NGT drilling sites, as ...
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... not only driven by local temperature but also affected by several factors like moisture sources and their proximity to the deposition site, the topography of the ice sheet and the seasonality of precipitation (Fisher et al., 1985). In addition the isotope signal is altered by post-depositional processes like wind-induced redistribution of snow, temperature gradient metamorphism and diffusion (Johnsen et al., 2000; Pinzer et al., 2012; Steen-Larsen et al., 2014). Stacked records are used to compensate for effects due to local to regional differences and to improve the signal-to-noise ratio (Fisher et al., 1985; Masson-Delmotte et al., 2015; White et al., 1997). To date, most ice core studies on the Greenland ice sheet have been carried out point-wise (e.g., Dye 3, GRIP, GISP2, NGRIP), which begs the question of how representative one single long ice core record is for deriving a comprehensive record of past climate. A study of ice cores from southern Greenland revealed that winter season stable water isotopes are largely influenced by the North Atlantic Oscillation (NAO) and are strongly related to southwestern Greenland air temperatures. On the other hand, summer season stable water isotope ratios show higher correlations with North Atlantic sea surface temperature conditions (Vinther et al., 2010). In particular, northern Greenland has been little investigated so far. The summit in Greenland’s center is the highest site and separates Greenland into a northern and southern part. Northern Greenland differs significantly from the south in terms of lower air temperatures and lower snow accumulation rates (Fischer et al., 1998c). Thus, the results from southern Greenland are not directly transferable to the northern part. Northern Greenland’s climate is influenced by different effects than the southern part. One example is the NAO effect, which is present in the southern and western part of Greenland and is discussed to be reduced in northern Greenland (Appenzeller et al., 1998). The cyclones causing the precipitation over northern Greenland originate in the Baffin Bay and bring dry and cold air masses from the central Arctic to northern Greenland (Chen et al., 1997). The dominant westerly winds are blocked by the ice divide, while the northeastern part has very low accumulation rates below 100 kg m − 1 a − 1 . The topographic situation in northern Greenland is special for δ 18 O studies. In northern Greenland going northward also means to go downward (lower altitudes). For a correct estimate of mass balances as well as the response to the ongoing climate change, knowledge of accumulation rates and the spatial distribution of δ 18 O as a temperature proxy is important for the entire Greenland ice sheet. However, due to northern Greenland’s remoteness its recent past climate has, up to now, been only scarcely investigated. Even in the 1990s little was known about northern Greenland. Only few studies had been performed before the Alfred Wegener Institute’s (AWI) North Greenland Traverse (NGT) started in 1993. There had been a traverse by Koch and Wegener in 1913 (Koch and Wegener, 1930) and one by Benson in 1952–1953 (Benson, 1962), and there was the British North Greenland Expedition in 1958 (Bull, 1958), which studied the accumulation rate in northern Greenland. How- ever, there had been no stable water isotope studies in the central part of northern Greenland. Fischer et al. (1998c) and (Schwager, 2000) present the first results from δ 18 O values of some of the NGT records. Using the updated accumulation rates of the (compared to Friedmann et al., 1995; Schwager, 2000) NGT, it was possible to show that the area of lower accumulation rates is much larger than expected before, which has an influence on the outlet glaciers (Weißbach et al., 2015). The NGT ice cores offer, for the first time, the possibility to study the spatial and temporal variability in stable oxygen isotope records from northern Greenland. Furthermore, they allow the analysis of the common spatial stable water isotope signal in northern Greenland by stacking the individual records to significantly reduce the isotopic noise that is present in a single record due to local peculiarities. The main objectives of this study are (1) to investigate the spatial variability in δ 18 O in northern Greenland using this new set of δ 18 O data and to evaluate the influence of isotopic noise on a single record, (2) to assess whether stable water isotope records from sites with low accumulation rates can be interpreted as climate signals, (3) to present a new robust stacked δ 18 O record for northern Greenland covering the past millennium, and (4) to interpret this record in terms of pale- oclimate with respect to temporal variability and relation to large-scale climate information from other proxy records. The ice cores presented here were drilled during the NGT from 1993 to 1995. In total, 13 ice cores (B16-B23, B26- B30) from 12 different sites (Table 1, Fig. 1) were drilled along the traverse route. The ice cores cover the last 500– 1000 years. The drillings were accompanied by extensive surface snow studies (e.g., Schwager, 2000). B21 and B23 as well as B26 to B30 are located on ice divides (Fig. 1), while B16–B20 were drilled east of the main ice divide. The NGRIP core (North Greenland Ice Core Project Members, 2004) was drilled 14.5 km northwest of B30 following the main ice divide and is therefore included in this study. Before analyzing the stable water isotopes, a density profile of each core was measured. To do so, the single core seg- ments (approximately 1 m long) were weighed in the field. Additional higher-depth-resolution density records were determined using gamma-absorption measurements in the AWI cold lab (Wilhelms, 1996). Finally, in 2012, density of the first 70 m of the three cores B19, B22 and B30 was analyzed by X-ray computer tomography (X-CT; Freitag et al., 2013). An exponential function fitted to the data taking into account all three types of density data with same respect was used to calculate water equivalent (w.e.) accumulation rates and to synchronize the cores. Selected parts of B30 were also analyzed for electrolytic conductivity using high-resolution continuous-flow analysis (Kaufmann et al., 2008). For the isotopic measurements the ice was cut into samples of 1–5 cm depth resolution, corresponding to 2–10 samples per year. Most of the ice was sampled with 2–2.5 cm depth resolution. Only at the uppermost parts of the core were samples cut with lower depth resolution (up to 5 cm). For some meters of special interest a resolution of 1 cm was used. After melting, δ 18 O was determined using Delta E and S mass spectrometers from Finnigan MAT in the AWI labo- ratory with uncertainties less than 0.1 ‰ as determined from long-term measurements. Cores B27 and B28 were drilled at the same site. Parts of core B27 (8.25–11.38 m w.e.), corresponding to AD 1926–1945) were lost, and these were re- placed by the record from B28. For the other parts, the mean of both dated cores was calculated to generate one isotope record for this site. Six of the NGT cores (B16, B18, B20, B21, B26 and B29) were already dated up to a certain depth by annual layer counting (using density, major ions or δ 18 O) in prior studies (e.g., Fischer and Mieding, 2005; Fischer et al., 1998a, b; Schwager, 2000). Depending on the availability of data and differences in snow accumulation rates the dating quality of these cores varies between 1- and 5-year accuracy. For the other NGT cores annual layer counting was not possible due to the very low accumulation rates (< 100 kg m − 2 a − 1 ). To achieve the same dating quality for all NGT cores for better comparison and to apply the dating on the whole core length, we used a new dating procedure for all cores. From density-corrected (w.e.) high-resolution electrical conductivity profiles (Werner, 1995; Wilhelms, 1996) and SO 2 4 − concentration profiles for B16, B18, B21 (Fischer et al., 1998a, b), B20 (Bigler et al., 2002) and an electrolytic conductivity profile (B30), distinct volcanic horizons were iden- tified and used as match points to synchronize the cores (Table 2). Some of the volcanic eruptions show a more pronounced signal in the Greenlandic ice than others. Thus not all eruptions could be identified in every record. Between match points, the annual dating was assigned assuming a constant snow accumulation rate. If a volcanic match point could not be clearly identified in an ice core, the next time marker was used to calculate the mean accumulation rate. Below the deepest volcanic match point, the last calculated accumulation rate was extrapolated until the end of the core. As the cores were drilled only in the upper part of the ice sheet (up to 100–175 m depths), layer thinning was not taken into account. The last millennium was a volcanically active time (Sigl et al., 2013). The volcanic aerosols deposited on the Greenland ice sheet can be used as time markers. The depths of peaks in conductivity and sulfate concentration attributed to certain volcanic horizons are given in Table 2 as used for our dating approach. During the last 500 years, the time period between two de- tectable eruptions at NGT sites does not exceed 100 years for any of the cores. This leads to a dating uncertainty for each core of smaller than 10 years compared to the annually counted timescales (Mieding, 2005; Schwager, 2000), which is minimal at the matching points. The three youngest volcanic reference horizons (Katmai, Tambora and Laki) and the eruptions from AD 1257 (Samalas; Lavigne et al., 2013) and AD 934 (Eldgjá) were found in all cores, whereas the other eruptions could not be clearly identified in every ice core. We could not find a common pattern (e.g., distance, strength of the eruption) regarding whether or not volcanic horizons could be observed in all records. This already indicates a high spatial variability ...
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... Variability in δ 18 O is dependent on local (e.g., wind), regional (e.g., position on the ice sheet) and large-scale (e.g., circulation patterns) processes. Even adjacent cores may dif- fer considerably according to snow drift (Fisher et al., 1985). One further reason for the rather low correlations may be attributed to dating uncertainties. From Fig. 2, we compare our individual NGT δ 18 O records to other published central to northern Greenland (GRIP, GISP2, NGRIP) δ 18 O time series. Prominent decadal-scale maxima and minima occurred mostly isochronally. However, specific events such as warm periods around AD 1420 or AD 1920–1930 or a cold period in the 17th century are more pronounced in the NGT cores compared to summit records. In Fig. 2 is also obvious that some records show faster changes between warmer and colder events (e.g., GRIP, B30 and B26), while others (e.g., B17–B21) remain longer at values higher or lower than their mean (Fig. 2). The longest warm period (compared to the mean of whole core length) is found in B19 (with 37 subsequent years warmer than the mean), while B17 has the longest cold period (28 subsequent years colder than mean). GRIP, B26, and B27/28 show a higher frequency with a maximum of about 10 subsequent warmer or colder years. A frequency analysis of 11-year running mean smoothed data supports these findings. B18–B21 and B29 show much longer main periods (117–248 a) than B16–B17 and B22–B30 (besides B29, 81–39 a). In general, the first half of the last millennium was characterized by longer warm or cold anomalies than the second half and records with more rapid fluctuations are from the summit and the main ice divide, while those cores drilled east of the divide have longer periods of positive or negative anomalies. We conclude that, east of the divide, the climate conditions are not as variable and therefore the annual δ 18 O signal is of greater persistence. The east-to-west difference is also expressed by the de- pendency of δ 18 O values on longitude (Fig. 4). This is in line with results from Box (2002), who found that there is often an opposite trend in air temperatures in east and west Greenland. The antiphase of temperature records from east and west Greenland is possibly explained by the importance of different weather regimes (e.g., Ortega et al., 2014). The range in δ 18 O in the different cores is different, too. Cores drilled in the northeast that are characterized by the lowest accumulation rates have the highest standard deviations (SD) in δ 18 O, which can be partly explained by the fact that a smaller number of accumulation events scatter more easily. We investigated the relationship between the altitude, latitude and longitude of the drilling sites and the mean δ 18 O values (Fig. 4a, b, c), which are, when considering all records, statistically significant ( p < 0.05) only for longitude and latitude. Regarding their snow accumulation rate we differentiate between two groups: (i) cores with accumulation rates lower than 145 kg m − 2 a − 1 mainly located east of the main ice divide (B16–B21 and B23) and (ii) cores with higher accumulation rates (B22, B26–B30 and NGRIP). We find higher δ 18 O ratios for sites with higher accumulation rates (Fig. 4d). The relationship is weak but becomes stronger for higher accumulation rates. Buchardt et al. (2012) noted that the relationship between accumulation rate and δ 18 O is not distinct for Greenland. Furthermore, Buchardt et al. (2012) found that the sensitivity of δ 18 O changes to accumulation rate is smallest in northeastern Greenland (North Central and North 1972), which is in agreement with our findings. Among the factors influencing the mean isotopic composition, longitude has the strongest impact ( R 2 = 0.56), which becomes clearest when looking only at the data of group I ( R 2 = 0.93). Figure 4c shows the clear east-to-west gradient in the mean δ 18 O values in northern Greenland. If separating between group I (“East”) and group II (“Divide”) there is a strong altitude effect ( R 2 = 0.93 and 0.78) in the data, too. These patterns may be explained by different atmospheric circulation conditions allowing additional moisture from other sources to reach the region east of the ice divide. This is supported by the finding of Friedmann et al. (1995), who suppose, based on data from B16 to B19, that northeastern Greenland receives more moisture from local sources as the Greenland Sea, Atlantic Ocean and the Canadian wetlands, in particular during summer. We found lower δ 18 O values in the southern and eastern part of northern Greenland in contrast to the general ideas of Dansgaard (1954), who expected lower values northward. That we do not find the lowest values north is a consequence of different factors in northern Greenland that balance each other out. More to the north, where we would expect lower δ 18 O values, the altitude in northern Greenland is decreasing, which causes higher δ 18 O values (Fig. 1). A multiple linear regression becomes necessary, as Johnsen et al. (1989) did before. Applying this approach to our data, we find δ ( δ 18 O)/( δ (latitude) = − 0 . 30 ( ± 0.40) ‰ degree − 1 and δ ( δ 18 O)/ δ (altitude) = − 0 . 0035 ( ± 0.0024) ‰ m − 1 . The regression residuals are linearly related to longitude as well as accumulation rate. In general, we found correlations with altitude, latitude and longitude, but the balancing-out effects because of the special topography in northern Greenland have to be taken into account. To study the regional-scale patterns of common variability in all annual δ 18 O records, we performed a principal compo- nent analysis (PCA). All calculations are done for the largest common time frame of all cores (AD 1505–1953). Other time periods were used as well, and they show similar results. Only the first two principal components (PC1 and PC2) are above the noise level. The first two eigenvectors of the isotopic time series explain 34.1 % of the total variance (PC1: 21.8 %; PC2: 12.3 %). PC1 is similar to the mean of all records ( r = 0.97, p 0 . 01). It was not possible to assign PC2 to any climatic relevant signal. The other PCs are dominant in one or two records but are not significant for the total variance of the entire data set. The loading patterns show a homogeneous pattern for EOF1 and a bipolar (west–east) result for EOF2. To summarize, the spatial differences in mean δ 18 O values in northern Greenland can be largely explained by the influence of the topography of the ice sheet on the regional climate system. The main ice divide influences the pathways of air masses, causing lower accumulation rates in the east. We assume that the temporal variability in a stacked NG δ 18 O record represents past temperature development. Stable water isotope ratios in ice are widely used as a proxy for air temperature (Dansgaard, 1964; Johnsen et al., 1995; Jouzel et al., 1997b). The comparison to direct air- temperature observation data and proxy data allows for as- sessment of the quality of the proxy in terms of paleoclima- tological interpretation. To reduce the noise in the single δ 18 O records, we calculated a stacked record by averaging the 13 annual NG δ 18 O records in their overlapping time periods (NG stack, Fig. 5). Before stacking, all records were centered and normalized regarding their common time frame (AD 1505–1953). The SD of the NG stack (0.44 for AD 1505–1953) is less than half of the SD in annual δ 18 O records of the individual cores. Vinther et al. (2010) also point out that stacking is important to improve the signal-to-noise ratio in areas with low accumulation rate. Local drift noise accounts for half of the total variance in single-site annual series (Fisher et al., 1985). As the NG stack before AD 1000 is based on only four records (< 25 % of the total core numbers), we decided to focus in the following only on the time period after AD 1000. As the NG stack is a result of 13 ice cores over a large area, we assume it is regionally representative. To investigate the relationship of the NG stack with air temperature, we used monthly meteorological observations from coastal southwestern Greenland sites and Stykkishólmur in northwestern Iceland available from the Danish Me- teorological Institute (DMI; ; AD 1784– 1993) and the Icelandic Met Office ( back to AD 1830), respectively. We selected only the Greenlandic temperature records longer than 200 years for our study even though they are at a large distance to the NGT drill sites (706–2206 km). The correlation coefficients between the NG stack and these air-temperature records are shown in Table 5. Dat- ing uncertainties are taken into account by comparing 5- year running means. The NG stack shows low but significant ( p < 0.001) correlations with the air temperatures at all sites (Table 5). The strongest correlation with annual mean temperature was found for the merged station data at Greenland’s south- east coast ( r = 0.51), and the temperature reconstruction for the North Atlantic Arctic boundary region of Wood et al. (2010) ( r = 0.55); the lowest was also found for Qaqortoq ( r = 0.39) in the south of Greenland (Table 5). For Stykkishólmur the correlation is in the range of the Greenlandic ones ( r = 0.41). Slightly higher correlations are obtained by comparing the NG stack to seasonal data. Except for Ilulissat, winter months (DJF) show weaker correlations; spring (MAM) and summer (JJA) months show stronger correlations with the NG stack. Comparably low correlations between annual δ 18 O means and measured temperatures from coastal stations are also reported for the NEEM record (Steen-Larsen et al., 2011). However, the rather low correlation coefficients might un- derestimate the real regional δ 18 O–temperature relations because of different reasons. We expect that the most important reasons are the large distances and the difference in altitude (i.e., more than 2000 m) between drill ...
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... 36.40°E, 150.4 m depth, 2234 m a.s.l.) 87 . All data from these four ice cores were obtained through continuous flow analysis (CFA) coupled to two inductively coupled plasma mass spectrometers (ICP-MS, Element2, Thermo Scientific) at the Desert Research Institute, USA (DRI), providing a simultaneous determination of a broad spectrum of elements at a sub-annual resolution 23 . ...
Existing global volcanic radiative aerosol forcing estimates portray the period 700 to 1000 as volcanically quiescent, void of major volcanic eruptions. However, this disagrees with proximal Icelandic geological records and regional Greenland ice-core records of sulfate. Here, we use cryptotephra analyses, high-resolution sulfur isotope analyses, and glaciochemical volcanic tracers on an array of Greenland ice cores to characterise volcanic activity and climatically important sulfuric aerosols across the period 700 to 1000. We identify a prolonged episode of volcanic sulfur dioxide emissions (751–940) dominated by Icelandic volcanism, that we term the Icelandic Active Period. This period commences with the Hrafnkatla episode (751–763), which coincided with strong winter cooling anomalies across Europe. This study reveals an important contribution of prolonged volcanic sulfate emissions to the pre-industrial atmospheric aerosol burden, currently not considered in existing forcing estimates, and highlights the need for further research to disentangle their associated climate feedbacks.
... Weather stations show that the coastal regions are warming 2 , but the imprint of global warming in the central part of the ice sheet is unclear, owing to missing long-term observations. Current ice-core-based temperature reconstructions [3][4][5] are ambiguous with respect to isolating global warming signatures from natural variability, because they are too noisy and do not include the most recent decades. By systematically redrilling ice cores, we created a high-quality reconstruction of central and north Greenland temperatures from ad 1000 until 2011. ...
... The only available multisite stacked climate record, originating from the North Greenland Traverse (NGT), did not indicate signatures of warming but ended in ad 1995 (ref. 5 ). ...
The Greenland Ice Sheet has a central role in the global climate system owing to its size, radiative effects and freshwater storage, and as a potential tipping point¹. Weather stations show that the coastal regions are warming², but the imprint of global warming in the central part of the ice sheet is unclear, owing to missing long-term observations. Current ice-core-based temperature reconstructions3–5 are ambiguous with respect to isolating global warming signatures from natural variability, because they are too noisy and do not include the most recent decades. By systematically redrilling ice cores, we created a high-quality reconstruction of central and north Greenland temperatures from ad 1000 until 2011. Here we show that the warming in the recent reconstructed decade exceeds the range of the pre-industrial temperature variability in the past millennium with virtual certainty (P < 0.001) and is on average 1.5 ± 0.4 degrees Celsius (1 standard error) warmer than the twentieth century. Our findings suggest that these exceptional temperatures arise from the superposition of natural variability with a long-term warming trend, apparent since ad 1800. The disproportionate warming is accompanied by enhanced Greenland meltwater run-off, implying that anthropogenic influence has also arrived in central and north Greenland, which might further accelerate the overall Greenland mass loss.
... Sampling the cryosphere While various glacial coring programs are ongoing in the Arctic, primarily targeting climate reconstruction (e.g., Weißbach et al. 2016), there are currently no land-based cryosphere coring campaigns for microplastic (i.e., glaciers, Arctic Science Downloaded from cdnsciencepub.com by University of Toronto on 10/12/22 ...
The atmosphere and cryosphere have recently garnered considerable attention due to their role in transporting microplastics to and within the Arctic, and between freshwater, marine, and terrestrial environments. While investigating either in isolation provides valuable insight on the fate of microplastics in the Arctic, monitoring both provides a more holistic view. Nonetheless, despite the recent scientific interest, fundamental knowledge on microplastic abundance and consistent monitoring efforts are lacking for these compartments. Here, we build upon the work of the Arctic Monitoring and Assessment Programme's Monitoring Guidelines for Litter and Microplastic to provide a roadmap for multicompartment monitoring of the atmosphere and cryosphere to support our understanding of the sources, pathways, and sinks of plastic pollution across the Arctic. Overall, we recommend the use of existing standard techniques for ice and atmospheric sampling and to build upon existing monitoring efforts in the Arctic to obtain a more comprehensive pan-Arctic view of microplastic pollution in these two compartments.
... BP (1724 CE), representing a single site but with glacial noise suppressed (Masson-Delmotte et al., 2015). Weißbach et al. (2016) made a stacked record reaching back one millennium and covering a larger area of North Greenland, including twelve North Greenland Traverse ice core records and the NGRIP ice core record. Here, two separate sub-stacks of the North Greenland records; one stack for cores located in Northeast Greenland, shielded from the westerly winds, and another for cores located on the ice divide. ...
In the Northern Hemisphere, an insolation driven Early to Middle Holocene Thermal Maximum was followed by a Neoglacial cooling that culminated during the Little Ice Age (LIA). Here, we review the glacier response to this Neoglacial cooling in Greenland. Changes in the ice margins of outlet glaciers from the Greenland Ice Sheet as well as local glaciers and ice caps are synthesized Greenland-wide. In addition, we compare temperature reconstructions from ice cores, elevation changes of the ice sheet across Greenland and oceanographic reconstructions from marine sediment cores over the past 5,000 years. The data are derived from a comprehensive review of the literature supplemented with unpublished reports. Our review provides a synthesis of the sensitivity of the Greenland ice margins and their variability, which is critical to understanding how Neoglacial glacier activity was interrupted by the current anthropogenic warming. We have reconstructed three distinct periods of glacier expansion from our compilation: two older Neoglacial advances at 2,500 – 1,700 yrs. BP (Before Present = 1950 CE, Common Era) and 1,250 – 950 yrs. BP; followed by a general advance during the younger Neoglacial between 700-50 yrs. BP, which represents the LIA. There is still insufficient data to outline the detailed spatio-temporal relationships between these periods of glacier expansion. Many glaciers advanced early in the Neoglacial and persisted in close proximity to their present-day position until the end of the LIA. Thus, the LIA response to Northern Hemisphere cooling must be seen within the wider context of the entire Neoglacial period of the past 5,000 years. Ice expansion appears to be closely linked to changes in ice sheet elevation, accumulation, and temperature as well as surface-water cooling in the surrounding oceans. At least for the two youngest Neoglacial advances, volcanic forcing triggering a sea-ice /ocean feedback, could explain their initiation. There are probably several LIA glacier fluctuations since the first culmination close to 1250 CE (Common Era) and available data suggests ice culminations in the 1400s, early to mid-1700s and early to mid-1800s CE. The last LIA maxima lasted until the present deglaciation commenced around 50 yrs. BP (1900 CE). The constraints provided here on the timing and magnitude of LIA glacier fluctuations delivers a more realistic background validation for modelling future ice sheet stability.
... Nainwal et al. (2007), have also reported that conical heaps in the neighborhood of the present-day snout at SPG are most possibly associated with the LIA. The LIA is widely varying from the period CE 1400-1900 (which is also notable for the worldwide glacier expansion) (Grove, 2004;Weissbach et al., 2016;Kennedy and Lindsey, 2015). The maximum depletion in stable isotopic composition of ice is seen at around 4500 m asl elevation, hence, the age of ice at this elevation is calculated using Eg.1. ...
This study focuses on the isotopic characterization of cryospheric water and quantification of different components contributing to Alaknanda River (major tributary of the Ganges River system) at its place of origin near snout of the Satopanth Glacier. A detailed understanding of various sources/flow components contributing to the river is useful for water resource management under changing climate scenario and helpful in risk assessment due to natural hazards in the headwater catchments, Extensive fieldwork was conducted, and water samples were collected from the river, snow, glacial ice, rain, lakes, and supraglacial channels of Satopanth Glacier Basin during the ablation period of 2017 and analysed for δ18O, δ2H, and 3H along with electrical conductivity. The results helped to establish the spatio-temporal and altitudinal variability in isotopic signatures of rain, snow, and ice in Satopanth Glacier Basin. The altitudinal effect in δ18O of pre-monsoon and monsoon rainfall is -0.13‰ and -0.41‰ per 100 m rise in elevation, respectively. Snow samples show depleting isotopic trend with an altitude effect of -0.43‰ in δ18O per 100 m rise in altitude. However, snowpack samples show an enrichment with time indicating post-depositional isotopic fractionation. The contrasting isotopic gradient in debris covered and non-debris covered ice are -0.9‰ and +3.4‰ per 100 m rise in elevation, respectively. These results divulge the spatial as well as temporal variation in cryospheric waters and these variations are used to derive the isotopic signatures of snow melt, glacier melt, and rain water. The results of hydrograph separation show that the snow melt, ice melt and rain water contribute about 33%, 49% and 18% respectively, to the discharge of Alaknanda River during the ablation period. Tracer based hydrograph separation indicates that the snow melt contribution dominates in river discharge during the initial ablation period. River discharge is a mixture of snow melt, glacier melt and rain water during July and August, while there is a dominance of glacier melt during end of the ablation period. The results of the present study highlight the importance of accounting the spatial and temporal variability in tracer signatures of cryospheric water for quantifying the contributions of snow and ice melt in a river originating from glacerised area.
... Henceforth, we will, however, treat these variables as constants due to the lack of a better knowledge and because climate conditions changed only little over the last centuries. In particular, the average snow accumulation of the B17 ice core has been determined by Weißbach et al. (2016) and shows little variation over time 25 (A = 11.4 ± 0.1 cm water equivalent a -1 , N = 630). Unfortunately, the other deposition parameters are not as well-known. ...
Ice nucleating particles (INPs) affect the microphysics in cloud and precipitation processes. Hence, they modulate the radiative properties of clouds. However, atmospheric INP concentrations of the past are basically unknown. Here, we present INP measurements from an ice core in Greenland, which dates back to the year 1370. In total 135 samples were analyzed with the FRIDGE droplet freezing assay in the temperature range from −14 °C to −35 °C. The sampling frequency was set to 1 in 10 years from 1370 to 1960. From 1960 to 1990 the frequency was increased to 1 sample per year. Additionally, a number of special events were probed, including volcanic episodes. The typical time coverage of a sample was on the order of a few months. Historical atmospheric INP concentrations were estimated with a conversion factor, which depends on the snow accumulation rate of the ice core, particle dry deposition velocity and the wet scavenging ratio. Typical atmospheric INP concentrations were on the order of 0.1 L−1 at −25 °C. The INP variability was found to be about 1–2 orders of magnitude. Yet, the short-term variability from samples over a seasonal cycle was considerably lower. INP concentrations were significantly correlated to chemical tracers derived from continuous flow analysis (CFA) and ion chromatography (IC) over a broad range of nucleation temperatures. The highest correlation coefficients were found for the particle concentration (dp > 1.2 μm). The correlation is higher for the seasonal samples, where INP concentrations follow a clear annual pattern, highlighting the importance of the annual dust input in Greenland from East Asian deserts during spring. Scanning electron microscopy (SEM) of single particles retrieved from selected samples found particles of soil origin to be the dominant fraction, verifying the significance of mineral dust particles as INPs. Overall, the concentrations compare reasonably well to present day INP concentrations, albeit they are on the lower side. However, we found that the INP concentration at medium supercooled temperatures differed before and after 1960. Average INP concentrations at −23 °C, −24 °C, −25 °C, −26 °C and −28 °C were significantly higher (and more variable) in the modern day period, which could indicate a potential anthropogenic impact or some post-coring contamination of the topmost, very porous firn.
... Andersen and others, 2006;Rasmussen and others, 2013, respectively), (2) the firn cores collected during the PARCA (Program for Arctic Regional Climate Assessment) campaigns and summarized by Bales andothers (2001, 2009) and (3) the ice cores drilled during the NGT (North Greenland Traverse) where accumulation rates have been reconstructed by Weißbach and others (2016). We note that the datasets do not always overlap in time and interpretations of the comparisons should bear this in mind. ...
The internal stratigraphy of snow and ice as imaged by ground-penetrating radar may serve as a source of information on past accumulation. This study presents results from two ground-based radar surveys conducted in Greenland in 2007 and 2015, respectively. The first survey was conducted during the traverse from the ice-core station NGRIP (North Greenland Ice Core Project) to the ice-core station NEEM (North Greenland Eemian Ice Drilling). The second survey was carried out during the traverse from NEEM to the ice-core station EGRIP (East Greenland Ice Core Project) and then onwards to Summit Station. The total length of the radar profiles is 1427 km. From the radar data, we retrieve the large-scale spatial variation of the accumulation rates in the interior of the ice sheet. The accumulation rates range from 0.11 to 0.26 m a ⁻¹ ice equivalent with the lowest values found in the northeastern sector towards EGRIP. We find no evidence of temporal or spatial changes in accumulation rates when comparing the 150-year average accumulation rates with the 321-year average accumulation rates. Comparisons with regional climate models reveal that the models underestimate accumulation rates by up to 35% in northeastern Greenland. Our results serve as a robust baseline to detect present changes in either surface accumulation rates or patterns.
... s1), whereas the variability of each species is inversely proportional to accumulation rate ( fig. s2 and Weißbach et al., 2016). We here define the variability as the average amplitude of the residuals from baseline correction achieved via asymmetric least square smoothing (ALSQ) as in (Peng et al., 2010) and performed for each individual time series . ...
... The chronology for both cores was refined by multiple-proxies layer counting performed on the basis of the year-counting presented in Weißbach et al. (2016). Figure 2 shows the original bromine record of B17 and B26 while figure 3 presents the bromine enrichment for both cores whereby the B17 record has been down-sampled from the original resolution to annual resolution to match the B26 ice core record. ...
... Both profiles present then a rise in the second part of the 20 th century where fluxes rise 235 back to 50 pg/m 2 a, before significantly decrease again from 1985 AD. The B17 ice core present a first minimum around the years 1420 AD, which may be related to a period of relative warming in the Arctic (Weißbach et al., 2016). This is followed by a period of relative high fluxes in the B17 ice core, between 1450 and 1520 AD, and a century of relatively lower values between 1520 and 1620 AD for both B17 and B26. ...
Sea ice is a key component of the climate system, since it modifies the surface albedo, the radiation balance, as well as the exchange of heat, moisture and gases between the ocean and the overlying atmosphere. Hence, the reconstruction of sea ice cover before the instrumental era and the industrial times is crucial to understand the evolution of Arctic climate in the last millennium and better predict its future evolution. However, identifying relevant paleo proxies in climate archives related to sea ice cover is not straightforward. Ice cores from polar regions offer great potential to provide high-resolution records of Arctic sea ice variability from chemical impurities such as Bromine species, which were recently proposed as indicators of sea ice extent, although their variability might be modulated by regional influences. We here use Bromine and Bromine enrichment of two ice cores form North Greenland (B17 & B26) and investigate its potential as proxy to reconstruct sea ice extent over the period 1363–1993 AD. Across the instrumental period, a good correlation is observed with the Baffin Bay and the Greenland Sea for B26 and B17 respectively, with both record showing minima corresponding to known Artic warming events such as the 1420 AD (for B17) and 1920–1940 (Early century warming, B17 & B26), together with a strong decline starting in the late 19th century. We simultaneously derived a chemical classification of sea ice-related contributors of ionic species (i.e. blowing snow, frost flowers, open water) utilizing the depletion of SO42− compare to Ca²⁺, K⁺ and Mg²⁺ characterizing sea ice brines and blowing snow as well the excess of Br− and Cl−, characterizing frost flowers, to elucidate the evolution of the different sources. In both B17 and B26 records we observe a strong contribution of blowing snow in the earliest part of the datasets, gradually declining in recent years in favour of open water sources.
... The annual site mean ± σ [MSA] values for the period of common overlap between records are shown as indicated for ad 1821-1985 (n = 165 years). The homogenous correlations (Pearson r) and significance level 55 This table cites refs 15,16,18,31,33,34,60,61 from this study. ...
Marine phytoplankton have a crucial role in the modulation of marine-based food webs¹, fishery yields² and the global drawdown of atmospheric carbon dioxide³. However, owing to sparse measurements before satellite monitoring in the twenty-first century, the long-term response of planktonic stocks to climate forcing is unknown. Here, using a continuous, multi-century record of subarctic Atlantic marine productivity, we show that a marked 10 ± 7% decline in net primary productivity has occurred across this highly productive ocean basin over the past two centuries. We support this conclusion by the application of a marine-productivity proxy, established using the signal of the planktonic-derived aerosol methanesulfonic acid, which is commonly identified across an array of Greenlandic ice cores. Using contemporaneous satellite-era observations, we demonstrate the use of this signal as a robust and high-resolution proxy for past variations in spatially integrated marine productivity. We show that the initiation of declining subarctic Atlantic productivity broadly coincides with the onset of Arctic surface warming⁴, and that productivity strongly covaries with regional sea-surface temperatures and basin-wide gyre circulation strength over recent decades. Taken together, our results suggest that the decline in industrial-era productivity may be evidence of the predicted⁵ collapse of northern Atlantic planktonic stocks in response to a weakened Atlantic Meridional Overturning Circulation6–8. Continued weakening of this Atlantic Meridional Overturning Circulation, as projected for the twenty-first century9,10, may therefore result in further productivity declines across this globally relevant region.
