Influence of North Atlantic Oscillation on anthropogenic transport ...

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JOURNAL OF GEOPHYSICAL RESEARCH, VOL. 111, D22309, doi:10.1029/2005JD006771, 2006

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Influence of North Atlantic Oscillation on anthropogenic transport recorded in northwest Greenland ice cores John F. Burkhart,1,2 Roger C. Bales,3 Joseph R. McConnell,4 and Manuel A. Hutterli5,6 Received 17 October 2005; revised 5 June 2006; accepted 10 July 2006; published 23 November 2006.

[1] Nitrate records from six Greenland ice cores covering the period 1789 to 1995 show a

significant correlation in concentration for averaging periods greater than 10 years, as well as an approximately 60% increase in average concentration during the last 75 years. Annual nitrate fluxes contain low-frequency trends driven primarily by changes in concentration, while higher-frequency variability is driven by changes in snow accumulation. Increases in concentration yield nearly 30% higher nitrate flux (2.5 to 3.2 mg m 2 yr 1) and an 11% increase in variability during the 1895 to 1994 period versus the prior 100 years. Nitrate trends in the cores during the last 100 years are also correlated with global nitrate emissions, with a highly significant average r value of 0.93 for the six cores. During the period of anthropogenic influence, nitrate is positively correlated with the North Atlantic Oscillation, while prior to that the correlation is negative, and less significant, suggesting a link between transport of anthropogenic emissions and the North Atlantic Oscillation. Significant preanthropogenic periodicities identified through singular spectrum analysis show decadal variability in the nitrate record leading to shifts as great as 30% from the mean state but none as great as the anthropogenic-driven deviation. Citation: Burkhart, J. F., R. C. Bales, J. R. McConnell, and M. A. Hutterli (2006), Influence of North Atlantic Oscillation on anthropogenic transport recorded in northwest Greenland ice cores, J. Geophys. Res., 111, D22309, doi:10.1029/2005JD006771.

1. Introduction [2] Understanding variability in the ice core nitrate record both before and after anthropogenic influence is important if such records are used to infer past atmospheric concentrations of NOx (NO + NO2) and changes in emissions sources. Adequate measures of preindustrial NOx concentrations do not exist and data on contribution from natural sources are limited. Nitrate concentration and flux measured in ice cores could be used as a proxy for NOx to constrain modeling of the past atmospheric photochemistry and hence development of future scenarios [Stewart, 1995; Thompson, 1995; Thompson et al., 1996; Thompson and Stewart, 1991]. [3] Nitrate has been measured in ice cores for over three decades [Herron, 1982; Herron et al., 1981; Herron and Langway, 1978; Koide et al., 1977; Legrand et al., 1992; 1 Department of Hydrology and Water Resources, University of Arizona, Tucson, Arizona, USA. 2 Now at School of Engineering, University of California, Merced, California, USA. 3 School of Engineering, University of California, Merced, California, USA. 4 Division of Hydrologic Sciences, Desert Research Institute, Reno, Nevada, USA. 5 British Antarctic Survey, Cambridge, UK. 6 Formerly at Climate and Environmental Physics, University of Bern, Bern, Switzerland.

Copyright 2006 by the American Geophysical Union. 0148-0227/06/2005JD006771$09.00

Mayewski et al., 1993; Yang et al., 1995], in ice cores from the Arctic [Fischer and Wagenbach, 1996; Goto-Azuma et al., 2002; Mayewski et al., 1990; Ro¨thlisberger et al., 2002], the Antarctic [Curran et al., 1998; Ro¨thlisberger et al., 2000b; Sommer et al., 2000; Wolff et al., 2002], and midlatitude mountain regions [Thompson et al., 2002; Thompson et al., 2003; Yalcin and Wake, 2001], yet to date, a definitive interpretation of preanthropogenic nitrate variability has not been developed [Ro¨thlisberger et al., 2002; Wolff and Bales, 1996]. Postdepositional processes, including both photochemical cycling of nitric acid in the surface snow layer and temperature-dependent physical ice-air partitioning, are likely a function of the average accumulation at the ice core site. While in some cases, total flux throughout a year may not be affected, the annual cycle of the nitrate recorded in the ice may be altered as a result of this exchange. While long-term increases in nitrate recorded in Greenland and several other Northern Hemisphere ice cores correlate well with one another and with anthropogenic emissions, there is considerable variability in decadal, annual, and seasonal fluxes [Alley et al., 1995] and concentrations have yet to be related to specific components of the climate system or nitrogen cycle. [4] Here we use extensive new ice core measurements from Greenland to identify components of temporal variability in ice core records of nitrate concentration and nitrate flux over the past two centuries and to develop an improved understanding of the processes driving the observed variability. The specific aims of the analysis are to (1) identify

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BURKHART ET AL.: NITRATE TIME SERIES FROM GREENLAND ICE CORES

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Figure 1. Ice core locations. One thousand meter contour intervals (gray dashed) and ice margin (gray solid) are shown. common patterns in nitrate and accumulation records from six ice cores from the central and northwestern part of Greenland, (2) relate these patterns to regional indices of climate variability and nitrogen emissions, and (3) understand how this variability is reflected in both the natural and anthropogenically influenced ice core nitrate records.

2. Data and Methods [5] Subannual nitrate records were developed from six ice cores collected as part of NASA’s Program for Arctic Regional Climate Assessment (PARCA) [Bales et al., 2001a] from the central to northwestern region of the Greenland Ice Sheet (Figure 1 and Table 1). All cores were analyzed using continuous flow analysis (CFA), allowing for multiparameter dating with accuracy of essentially zero

up to ±3 years between markers at high versus low accumulation sites, respectively, over the time periods considered in this paper [Anklin et al., 1998; Bales et al., 2001b; Ro¨thlisberger et al., 2000a]. Annual markers were defined from the distinct spring peak in calcium and the summertime peak and winter minima of hydrogen peroxide, to define individual years. Additionally, beta radiation peaks in tritium from nuclear testing during the 1960s and known volcanic events (Novarupta, 1912; Tambora, 1816; and Laki, 1783) were used as absolute age indicators. All cores except the GITS core are in the dry snow zone, above the 2000 m contour of the ice sheet; hence melt events are rare and we expect no significant alteration to the mean annual concentrations. The slight melting at the GITS site was moderated by its high accumulation such that annual dating

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Table 1. Record Information for the Six Greenland Ice Cores Core Humboldt NASAU GITS Summit D2 D3

Latitude/Longitude, decimal degrees 78.5/ 73.8/ 77.2/ 72.8/ 71.8/ 69.8/

56.8 49.5 61.1 38 46.2 44

Elevation, m 1973 2368 1910 3208 2640 2560

Mean Temperature, °C 29 21 24 26 20 19

and average concentrations were not affected [Bales et al., 2001b; Dansgaard and Johnsen, 1969]. [6] It has been established that nitrate in ice cores is potentially affected by postdepositional processes. In particular: temperature, photochemistry in the surface snow, and physical redistribution may affect the preserved signal. However, in previous studies, Burkhart et al. [2004] have shown that with adequate accumulation the amount of nitrate lost is restricted to less than 10% at a site with accumulation greater than 20 cm per year. Furthermore, at sites which meet this accumulation criterion, nitrate losses would presumably be driven predominately by variability in temperature. We have evaluated the annual data in these records, and found no correlation between accumulation and concentration for the individual sites, indicating no relationship. The sites chosen in this study are within a climatologically similar region [see Hutterli et al., 2005, Figure 2a]; while there is certainly evidence from locations with lower annual snowfall that the losses may be greater [Ro¨thlisberger et al., 2000a; J. F. Burkhart, Geographic variability of nitrate deposition and preservation over the Greenland ice sheet, manuscript in preparation, 2006, hereinafter referred to as Burkhart, manuscript in preparation, 2006], with the exception of the Humboldt record, we are confident that the effect of postdepositional processing on these records would not significantly affect the interpretation of this analysis. [7] Time series analysis was conducted on annual records of accumulation, concentration, and flux (the product of accumulation and concentration). Accumulation was derived from a polynomial fit to field-collected density measurements and the depth-age scale for the core. For some analyses, data were normalized by subtracting the mean and dividing by the standard deviation; in other cases, a record of residuals was developed by removing long-term trends as described individually for each analysis. [8] The 1995 Humboldt core is the northernmost core of the data set. The southernmost core is the 1999 Summit core, collected 6 km east of the GISP 2 site, now the GEOSummit Observatory. The cores NASAU, D2, and D3 are spaced in a southeasterly direction from the Humboldt core at 540, 796, and 1029 km distance, respectively. The GITS core is located over a divide 180 km southwest from the Humboldt core. Despite their close proximity, the two cores represent the extremes of the data set with respect to average nitrate flux, the GITS core having the highest (5.9 mg cm 2 yr 1) and the Humboldt core the lowest (1.3 mg cm 2 yr 1). The longest time period of measurements common to all six cores is 206 years, 1789 to 1994 (Table 1). For most of the

Depth, m

Year Collected

Period

Years in Record

146.2 151.1 120.1 136.5 132.5 150.3

1995 1995 1996 1999 2000 2000

1144 – 1994 1645 – 1994 1789 – 1995 1529 – 1998 1781 – 1999 1740 – 1999

851 350 207 469 218 259

analysis, two periods were defined: 1789 to 1894, a 106-year period of preanthropogenic influences, and 1895 to 1994, a 100-year period of anthropogenically influenced records. Past results from Greenland ice cores suggest that the earliest anthropogenic increases occur after 1890, with strong anthropogenic increases in the nitrate record observed after 1940 [Fischer et al., 1998; Mayewski et al., 1990]. 2.1. Time Domain Analysis [9] Analysis in the time domain included least squares regression, Kolmogorov-Smirnov (KS) normality tests, autocorrelation, and partial-autocorrelation to describe the data [Chakravarti et al., 1967]. The purpose was to better understand the stochastic nature of the data, define trends, and identify uniqueness in the data. Along with the two primary periods chosen for this analysis, shorter periods exhibiting unique characteristics such as trend or an extreme event were analyzed more closely to evaluate climate drivers that may be causing the variability. [10] Time series plots for each of the records were generated, followed by the development of histograms and descriptive statistics. Normality tests were conducted on time series records of accumulation, concentration, and flux. Despite skew in the nitrate concentration, the data for all u/s) variables (concentration, flux, and normalized (u accumulation) were adequately distributed such that no transformations were necessary for further time series analysis. 2.2. Frequency Domain Analysis [11] In addition to traditional frequency domain tools such as fast Fourier transform (FFT) and analysis of the spectrum and periodogram, Monte Carlo singular spectrum analysis (MCSSA) was used for nonlinear trend removal and the detection of significant frequency contributions [Allen and Smith, 1996]. A Monte Carlo approach to SSA has been extensively used in time series analysis for the identification of signal structure in short noisy time series without the use of prior information (i.e., indeterminant systems) [Broomhead and Jones, 1989; Vautard et al., 1992]. Improvements in identifying periodicities that significantly contribute to the variability of the record and increased confidence in rejecting the AR(1) noise hypothesis are gained through employment of MCSSA [Ghil, 1986; Vautard and Ghil, 1989].

3. Results 3.1. Nitrate Concentration [12] Mean annual concentrations of the six ice cores during the preanthropogenic period range from 51 to

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Figure 2. Annual and five-point triangular filtered nitrate concentrations for the six cores with four trend periods shown as defined by least squares regression (see text). 138 ng g 1 (Figure 2 and Table 2). The mean of the anthropogenic period concentrations are 35% greater, ranging from 68 to 187 ng g 1. In both periods, the mean concentration of the cores relative to one another was

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consistent, suggesting that common processes drove concentration increases across the region. In detrended time series, the coefficient of variation (ratio of the standard deviation of the time series to the mean) of annual values is 20 to 50% greater in the latter period at Humboldt, NASAU, D2, and D3. Ten-year running variances in concentration showed all six cores having higher variability during the latter half of the 20th century, with four of the cores also having a period of increased variability in the earliest part of the 19th century. At the GITS site, the most coastal core, variance was higher in the preanthropogenic period. [13] Nonstandardized annual nitrate concentrations are positively skewed with a kurtosis slightly greater than three. In the anthropogenic period there were fewer outliers, consistent with higher overall observed concentrations and variability. It is likely anthropogenic signals may be masking some features of natural variability. [14] Four periods of concurrent trends were identified with least squares regression, and trend statistics calculated for each period. However, the second period (1851 to 1920), which exhibited little trend in any of the cores, was divided into two sections for direct comparison with the results of Fischer et al. [1998] (Table 3). For the first period (1789 to 1850) all cores except Humboldt show an average decreasing concentration trend with a mean decline of 1.0 ng g 1 yr 1. The second period (1851 to 1889) is relatively flat for all cores, with a maximum change of 1.1 ng g 1 yr 1 in the NASAU core; others having mixed trends. Note that the linear regression statistic will not be significant for a flat trend, and the trends are not significant in this period. During the period of 1890 to 1920 all cores have increasing trends ranging from 0.15 to 2.56 ng g 1 yr 1 with an average of 1.40 ng g 1 yr 1. The short period from 1921 to 1938 shows a strong decrease in concentration with the exception of Humboldt, averaging 2.4 ng g 1 yr 1. During the last period, 1939 to 1994, all of the cores show an increase averaging 5.1 ng g 1 yr 1. [15] To extract nonlinear trends from the annual average nitrate concentration data, Monte Carlo SSA was employed, using over 10,000 realizations of a time series with AR(1), red noise parameters, to determine the significance of the trends above red noise. The embedding dimension, M, was defined as 40, though experiments were made with larger and smaller values (30 < M < 75). M represents the maximum time lag considered for the autocorrelation function and defines the spectral resolution of the analysis, in this

Table 2. Mean and Coefficient of Variation for Ice Core Records Period

Humboldt

GITS

NASAU

Summit

1789 – 1994 1789 – 1894 1895 – 1994

98/0.33 79/0.30 110/0.37

Concentration, ng g 1/Coefficient of Variation 162/0.36 77/0.40 65/0.28 138/0.37 67/0.31 58/0.31 188/0.30 91/0.46 76/0.28

1789 – 1994 1789 – 1894 1895 – 1994

130/0.30 140/0.27 150/0.31

Accumulation, kg m 370/0.26 380/0.24 360/0.27

1789 – 1994 1789 – 1894 1895 – 1994

1.29/0.42 1.11/0.37 1.57/0.43

D2

D3

63/0.32 55/0.22 71/0.31

59/0.33 51/0.24 69/0.33

yr 1/Coefficient of Variation 370/0.25 220/0.20 380/0.26 220/0.19 370/0.22 220/0.19

450/0.17 450/0.18 450/0.17

440/0.16 450/0.15 430/0.17

Flux, mg cm2 yr 1/Coefficient of Variation 5.87/0.40 2.84/0.45 1.42/0.33 5.21/0.38 2.54/0.37 1.30/0.35 6.61/0.37 3.33/0.49 1.68/0.31

2.83/0.36 2.45/0.28 3.19/0.33

2.56/0.33 2.27/0.25 2.94/0.32

2

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Table 3. Magnitude (ng g

1

yr 1) and r2 Value of the Covarying Trends Identified for the Six Ice Core Concentration Time Series

1789 – 1850

Humboldt GITS NASAU Summit D2 D3

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1851 – 1889

1890 – 1920

1921 – 1938

1939 – 1994

Magnitude, ng g 1 yr 1

r2


r2


r2


r2


r2

0.97/ 3.44/ 0.89/ 2.34/ 0.15/ 0.71/

0.56 0.73 0.34 0.79 0.09 0.78

0.47/ 0.90/ 1.11/ 0.61/ 0.25/ 0.69/

0.57 0.59 0.59 0.48 0.12 0.83

1.89/ 2.64/ 0.16/ 1.84/ 1.37/ 0.77/

0.75 0.64 0.06 0.97 0.87 0.52

2.74/ 3.98/ 3.77/ 3.63/ 1.28/ 0.09/

0.95 0.81 0.82 0.97 0.88 0.06

2.85/ 6.68/ 7.43/ 4.85/ 3.44/ 3.08/

0.71 0.86 0.89 0.98 0.98 0.97

case 40 years. The statistical dimension of the trend was two. The first two components of the SSA were significant from red noise at the 95% level, and they were summed to reconstruct the trend. [16] Similar to what we found with linear regression, GITS, NASAU, Summit, and D3 had periods of significant preanthropogenic decreases (Figure 3), but Humboldt and D2 did not. In the preanthropogenic period the nonlinear trend lines deviated up to 34% from the mean (NASAU); however, for most records, they remained within 20% of the mean and are not as strong as the trends observed during the past 100 years. [17] The nonlinear trends were removed to create a stationary data set, with an AR(1) process the best fit to the residuals of the SSA. Year-to-year variability, represented by the residuals, can be large, deviating as much as 80% from the mean (Figure 4). However, decadal shifts, based on the 10-year running means, are generally less than 15%. [18] There is a high degree of intercore covariability of the nonlinear trends over the entire 206-year period for the concentration records, with the lowest Pearson’s r value at 0.82. For the period of 1890 to 1990 the lowest r value between the concentration records and the NOx emissions is 0.85 for the Humboldt core. All other cores have r values greater than 0.93. All correlations were significant at the 95th percentile. [19] After removal of long-term trends, there are noteworthy differences in correlation for the preanthropogenic versus anthropogenic period (Table 4). Note that during the preanthropogenic period, there are no significant correlations between the sites on the annual time series, but during the anthropogenic period, there several correlations which are significant between the sites, though weak. The average correlation for all sites in the anthropogenic period is r = 0.22, which is significantly greater (student’s t test, p = 0.004) than the average during the preanthropogenic period (r = 0.09). 3.2. Accumulation [20] Mean annual accumulation over 206 years at the six sites ranged from 0.13 mweq yr 1 at the Humboldt site to 0.45 mweq yr 1 at D2 (Figure 5). There are no significant differences between the two periods in mean accumulation or coefficient of variation. Accumulation at all six sites is normally distributed. Ten-year running variance and running means were calculated for the accumulation records in the same manner as for concentration. Where necessary, the accumulation records were strain corrected for glacial flow

Figure 3. Normalized concentration time series (1789 to 1994) as fraction of mean with SSA nonlinear trends shown. Shaded lines are singular spectrum analysis (SSA) trend from 206-year analysis, dashed lines indicate preanthropogenic analysis, and solid lines indicate anthropogenic analysis. Preanthropogenic SSA trends for D2 and Humboldt were not significant and are therefore not shown.

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3 of the 6 cores have trends of less than 2% over the 206 years (Figure 6). 3.3. Nitrate Flux [22] For the 1789 to 1994 period, mean annual nitrate flux ranged between 1.3 ± 0.5 mg cm 2 yr 1 at the Humboldt site and 5.9 ± 2.3 mg cm 2 yr 1 at the GITS site (Figure 7). The 30% higher average annual flux in the anthropogenic versus preanthropogenic period (2.5 versus 3.2 mg cm 2 yr 1 averaged over all six cores) is similar to the 35% difference in concentration over the same periods. The coefficient of variation is higher in the second period, reflecting the greater variability in the concentration record. As illustrated for D3, the slight accumulation increase during the preanthropogenic period is offset by a similarly small decline in concentration, resulting in no trend in flux (Figure 8); but the strong increases in concentration in the latter half of the twentieth century are clearly driving increases in flux despite a small downward trend in accumulation at this site. Patterns are similar for the other cores. [23] The flux data, similar to the concentration data, are positively skewed, with a kurtosis greater than 3. However, once standardized, the data adequately fit a normal distribution and pass KS normality tests at the 95% confidence level. [24] Annual concentration and flux are positively correlated, with a mean r of 0.64 for all six sites over the 206-year period (Table 5). The correlation was slightly higher during the more recent 100-year period. Correlations between flux and accumulation were weaker, yet statistically significant for all cores (mean r = 0.19 for all six sites). The correlation was slightly lower during the more recent 100-year period. Three sites had significant correlations for accumulation versus concentration, however, the highest r value was only 0.07, giving no indication of a strong relationship between the two variables.

4. Discussion Figure 4. Residuals of concentration time series (1789 to 1994) from SSA as fraction of mean (vertical bars) and 10-year running means (solid lines). using a constant vertical strain rate method (e.g., Humboldt, GITS, and NASAU [Anklin and Bales, 1997]). There are no common periods of enhanced or decreased variability among the six cores. [21] No significant trends were identified in the SSA of accumulation, and therefore defining a statistical dimension of trend greater than zero in the SSA would remove potentially significant components that are contributing to a distinguishable periodicity. In general the accumulation time series are trend-free, with the exception of slight linear trends throughout the entire period of record. Therefore, to assure stationarity of the data set, trends were removed from the accumulation records with trends identified through linear least squares regression. While the trend over the 206-year period is approximately 10% in the Humboldt core, there is no consistency between the cores with respect to the trends; some show decreases and others increase, and

4.1. Sources of Trends in the Records [25] While it is generally accepted that changes in ice core nitrate concentrations reflect atmospheric changes, the multiple factors influencing atmospheric nitrate have limited the ability to make quantitative interpretations of the natural variability recorded in ice cores [Wolff and Bales, 1996]. Current understanding of the preservation of nitrate in the glaciological record is incomplete, yet shows strong dependence on accumulation, photolysis in the surface snow, and the chemistry of the snow, specifically pH [Beine et al., 2002; Ro¨thlisberger et al., 2003]. While rapid postdepositional losses of nitrate have been observed in some regions [Mulvaney et al., 1998; Wolff et al., 2002], at Summit, Greenland, nearly all of the nitrate measured in the surface snow could be accounted for in firn snow pits one year later [Burkhart et al., 2004]. For the sites studied in this analysis, accumulation is sufficient to preserve nitrate once deposited, and significant postdepositional losses in nitrate do not likely result from accumulation variability at the sites. [26] This study aims to identify natural variability in the nitrate records that are not driven by local site attributes. The multidecadal nonlinear trends and recent increases in

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Table 4. Intersite Correlation Coefficients (Pearson’s r) for Residuals of Concentration and Accumulation During 1789 to 1894 (Upper Quadrants) and 1895 to 1994 (Lower Quadrants)a Humboldt Humboldt GITS NASAU Sum99 D2 D3 Humboldt GITS NASAU Sum99 D2 D3

GITS 0.01

0.11 0.16 0.04 0.14 0.05

0.32 0.45 0.26 0.19 0.11

0.04 0.01 0.06 0.09 0.05

0.19 0.13 0.00 0.00

NASAU Concentration 0.00 0.02 0.41 0.20 0.05

Summit99 0.14 0.20 0.09 0.44 0.38

Accumulation 0.10 0.06 0.07 0.42 0.20

0.06 0.05 0.13 0.10 0.12

D2 0.08 0.08 0.04 0.05

D3 0.06 0.17 0.07 0.20 0.26

0.49 0.01 0.34 0.11 0.10

0.04 0.22 0.16 0.23 0.63

0.56

a

Values in bold are statistically significant with a confidence greater than 90%.

nitrate concentration (Figure 3) are strongly correlated in all of the cores, while decadal and annual variability (Table 4 and Figure 4) is less correlated. Lower-frequency linear trends in nitrate fluxes from the different cores also track each other (Table 3). As these common trends in concentration cover the entire northwest region of the ice sheet, we argue they are representative of large-scale changes in atmospheric concentrations from source regions for northwest Greenland nitrate. The common concentration trends cannot be attributed to any postdepositional processes alone, which also depend on trends in accumulation and temperature, but which would vary across the six cores. [27] While variability in regional concentration sources ostensibly play a significant role in the natural variability of the individual record, these regional concentration shifts are masked in the anthropogenic period by the global atmospheric increases in concentration. For nitrate, correlations between sites (Table 4) during the preanthropogenic period are not significant. In the anthropogenic period, r values are as high as 0.49 and many are significant above 90%. For nearby sites accumulation covariability was consistent between the two periods and there was no systematic shift in overall correlation. We note that dating errors, which likely increase with record length, may introduce altered correlations between the two periods. However, the consistency of the results for the various sites provides confidence that the shifts in correlation are driven by Earth system processes rather than analytical errors. [28] Mayewski et al. [1990] and Legrand and Mayewski [1997] argue that the enhanced emissions of reactive nitrogen are not clearly recorded in the glaciological record from Greenland until after 1940 while Fischer et al. [1998] demonstrate that three cores from north Greenland show both increased covariability and enhanced concentrations as early as 1890. The evidence from the six cores shown here is similar to the findings of Fischer et al. [1998], having characteristics they identified in three northern Greenland cores: (1) overall increases from 1890 to 1920, (2) a period of decrease from 1920 to 1940, (3) strong increases during the period of 1940 to 1990, and (4) a slight decrease after 1990. Unique to this analysis are the nonlinear trends during the preanthropogenic which show a period of overall

Figure 5. Annual and five-point triangular filtered accumulation for the six cores.

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food production. Prior to 1890 most of the alteration of the N cycle resulted from biofuel combustion (e.g., fossil fuel combustion, biofuel, slash and burn agriculture, and annual savanna burns). Around 1890, the importance of biological nitrogen fixation for food production was discovered, and shortly thereafter in 1913, the Haber-Bosch process was created to transform atmospheric N2 to NH3. After this point, as food was readily produced without limited N for fertilization, global populations grew rapidly [Galloway and Cowling, 2002]. [30] There are few records of variability in the natural cycle of N on the centennial and decadal scale, particularly records showing predictable or periodic cycling that would result in the decreases observed in the ice core record. Our records here show decadal variability in the early nineteenth century having concentration deviations as high as 30% from the mean.

Figure 6. Normalized accumulation time series as fraction of mean and 10-year running means (solid lines). Linear trends are plotted (shaded lines) but removed from time series. decreasing concentrations and enhanced variability prior to 1850, particularly in the GITS, NASAU, and Summit cores. [29] While the trends in nitrate concentration after 1940 are commonly accepted as resulting from increased human activity [Goto-Azuma and Koerner, 2001; Kekonen et al., 2002; Yalcin and Wake, 2001], there is less understanding of anthropogenic influence for the period 1890 to 1940, or what controls the variability in the record prior to that point. Galloway et al. [2004] demonstrate that while anthropogenic contributions to reactive nitrogen (N) in the global N cycle were only 16% of the total by 1860, there was already an observable effect on the reactive N cycle in the atmosphere. Further, there were identifiable alterations in the spatial variability of reactive N resulting from energy and

Figure 7. Annual and five-point triangular filtered nitrate flux for the six cores.

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Figure 8. Linear trends for the first 106-year and second 100-year periods for D3, showing the degree to which small accumulation changes offset concentration changes. [31] During the period of 1890 to 1920, there are increases in the annual concentration in some cores (Figure 2, GITS, Summit, D2, and D3, and Table 3), though the trends are not consistent among all cores. However, linear trend analysis for this period does show common increases; begging the question, is this period recording anthropogenic or natural variability? The strong 1920 to 1940 decreasing trend common to all cores except Humboldt is arguably a result of the economic downturn and significant drop in productivity during this time. McConnell et al. [2002] have shown that this period is well reflected in a 250-year record of lead flux to the Summit, Greenland, region (Figure 9). Nitrate concentration shows a similar decrease, yet lagged by a period of a few years. This suggests that nitrate increases prior to 1920 are evidence of slowly increasing reactive N inputs to the atmosphere resulting from human activity which also slowed during the depression. [32] Our records undeniably show anthropogenic increases well correlated with known inventories (Figure 10). For the period of the van Aardenne et al. [1999] record, the trend in the cores is strongly correlated with the emissions data at the 95% level. The weakest correlation with the van Aardenne data set is from the Humboldt record (r = 0.85), whereas all other cores have r values exceeding 0.93. These trends yield anthropogenic increases that uniformly exceed 60% of the mean in all six records through 1990. [33] A final point to note is the decrease in nitrate concentration evident at the end of the record in the six cores presented here as well as the three records examined by Fischer et al. [1998]. It is believed that these decreases are related to reductions in emissions of reactive NOx, primarily from automobiles. In the United States, NOx emissions have been reduced by 15% during the period 1983 to 2002 [Environmental Protection Agency, 2003]. European emissions have also been significantly reduced including NOx by as much as 29% from 1990 to 2000 [Gugele and Ritter, 2002]. Despite direct emission reduc-

tions resulting from stricter controls and more efficient vehicles, the van Aardenne data set indicate that global NOx emissions have not decreased; this apparent discrepancy between global emissions and the ice core records provides evidence that Greenland may be recording European and North American sources where reductions are in effect. 4.2. Sources of Periodicity in the Records [34] Prior investigations have found that the NAO signal can explain up to one third of the interannual variability in accumulation recorded in ice cores [Appenzeller et al., 1998a; Bales et al., 2001b]. This variability is most strongly indicated in records smoothed with a 5-year triangular filter, in essence removing higher-frequency annual variability specific to the ice core site possibly resulting from glaciological processes (e.g., wind redistribution of surface snow) [Fisher et al., 1985]. The accumulation time series showed substantial high-frequency noise, with peak periodicities in the range of 2.9 to 6.8 years. Concurrent spikes were identified at 2.4, 4.5, 5.5, and 7.7 years, similar to wellknown NAO periodicities. [35] Repeating the analysis with four well known NAO indices, those of Jones et al. [1997], Luterbacher et al. [1999], Rogers [1990], and Hurrell [1995], showed concurrent peaks in the frequency response at 2.4, 4.8, 5.5, 7.8 years, in agreement with the ice core analyses. The relation between the NAO and accumulation identified in this study are consistent with previous findings, providing further evidence that for northwestern Greenland ice cores (GITS, NASAU, D2, and D3), NAO may account for as much as one third of the variability in the record [Bales et al., 2001b]. For example, for this set of cores, the Roger’s NAO index may account for 16 to 43% of the decadal variability (Table 6). Appenzeller et al. [1998b] found the relationship to be strongest with cores closer to the coast (westward) and southward over the divide separating the northeastern portion of the ice sheet from the southwestern.

Table 5. Intracore Comparison of Concentration, Accumulation, and Flux (Pearson’s r Values)a Concentration Versus Flux

Accumulation Versus Flux

Core

1789 – 1894

1895 – 1994

1789 – 1994

1789 – 1894

1895 – 1994

1789 – 1994

Humboldt GITS NASAU Sum99 D2 D3 Mean

0.40 0.62 0.46 0.70 0.54 0.66 0.56

0.35 0.42 0.74 0.63 0.69 0.75 0.60

0.45 0.55 0.69 0.70 0.69 0.77 0.64

0.46 0.16 0.38 0.25 0.39 0.15 0.30

0.33 0.36 0.11 0.20 0.17 0.05 0.21

0.33 0.19 0.15 0.18 0.21 0.05 0.19

a

All values are statistically significant with a confidence greater than 95%.

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Figure 9. Lead from the Summit core [McConnell et al., 2002] shown with nitrate from the same core. Note the decreases during the 1920 – 1940 period, resulting from decreased industrial activity during the 1930s. Also note the lag in nitrate concentrations. In a modeling study of precipitation over Greenland, Bromwich et al. [1999] found an increased correlation to NAO ( 0.80) when comparing only southern Greenland precipitation, which has greater variability than in the north. However, it is important to note that ice core records span a much longer time period than the reanalysis data used by Bromwich et al. (1979 to 1993). The Bromwich et al. [1999] finding, and the lower correlation with the centrally located Summit core (Table 6), may be explained in part by the timing of accumulation. At Summit, there is some seasonality in accumulation, with rates slightly elevated during the late summer and early autumn [Burkhart et al., 2004], and winter months least well represented in the ice core record owing to high winds [McConnell et al., 1997]. Another explanation for higher correlation found in the Bromwich study could be the result of the NAO being in an active or ‘‘coherent’’ state possibly related to anthropogenic climate forcing during this period [Appenzeller et al., 1998b; Ga´miz-Fortis et al., 2002]. [36] Prior to this study, nitrate proxies have not been analyzed for an NAO signal. The frequency analysis was repeated using nitrate records to identify periodic components and identified a range of peak frequencies in the spectrum, however, a distinctly concurrent peak exists in all the records with a periodicity of three years. Comparing all the available NAO indices with concentration, the D2 record consistently exhibited the strongest correlation with the spring (Mar to May) index. For the Roger’s (Table 6) and Luterbacher (Table 7) indices, this appears to be driven by strong correlations with the month of March. Examining the other monthly indices (when available), March was found to consistently give the strongest correlation.

[37] In Humboldt, the northernmost core, the correlations were often opposite to what was found at the other ice core locations. Humboldt is separated from the other core sites by an elevation divide, thus sampling air that is more greatly influenced by the Arctic Ocean rather than the North Atlantic. This is further seen by the positive correlation of the Humboldt site accumulation record to the AO record, which provides a measure of the Arctic vortex strength (Table 6). [38] Recent studies of the NAO climate anomaly demonstrate a strong influence on the transport of pollution to the Arctic [Li et al., 2002]. Eckhardt et al. [2003] found that during strongly positive NAO periods, enhanced poleward transport of pollutants led to a uniform 10% increase in observed carbon monoxide at Arctic stations. Using the

Figure 10. Decadal average SSA nonlinear trends of nitrate concentration during the anthropogenic period compared to the van Aardenne et al. [1999] total N emissions data set.

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Table 6. Correlation Coefficients for North Atlantic Oscillation Analysisa Rogers Spring Humboldt GITS NASAU Summit D2 D3

0.48 0.28 0.52 0.58 0.52

March Correlation 0.43 0.41 0.55 0.61 0.55

Annual 0.31 0.32 0.36 0.22

AO Annual 0.23 0.22 0.29 0.31

Accumulation Humboldt GITS NASAU Summit D2 D3

0.54 0.54 0.28 0.32 0.42

0.35 0.50 0.27 0.27 0.38

0.40 0.66 0.50 0.48

0.26 -

a Correlation coefficients for 5-year triangular filtered time series of accumulation and concentration with climate indices. When available, monthly, seasonal, and annual index time series were considered. The period of comparison for the indices was 1874 to 1994 and 1899 to 1994 for the Rogers and AO indices, respectively. All values are significant at the 95% level, bold values are significant at the 99% level, insignificant coefficients are not shown. Spring is defined as March, April, and May.

Luterbacher index, which extends to 1658, the influence of NAO on concentration during the anthropogenic (1895 to 1994) versus preanthropogenic (1789 to 1894) period (Table 7) was evaluated. The correlations during the anthropogenic were found to be stronger, while during the preanthropogenic period the correlations were negative, except for Humboldt. During the anthropogenic period, the correlations were consistently positive with the exception of Humboldt, and again, the March monthly index was strongest. There are several explanations for this pattern assuming the reconstructions are reliable for both periods. During the preanthropogenic period, NAO was in a predominantly ‘‘incoherent’’ state [Appenzeller et al., 1998b], therefore having less influence over climate and atmospheric transport processes. The NAO has been in a strongly positive phase during the recent decades and it has been suggested that the climate anomaly may be anthropogenically influenced [Eckhardt et al., 2003]. [39] Anthropogenic influences on the nitrogen cycle, and particularly reactive N in the atmosphere, are well established [Galloway and Cowling, 2002; Galloway et al., 2002, 2004; Howarth et al., 2002; van Aardenne et al., 1999, 2001], and we show here the seasonal cycle of nitrate deposition has been greatly influenced, losing what previously was a predominant early summer peak, and now having higher wintertime and spring values, in many records, creating a bimodal distribution throughout the year (Figure 11). Using the nonparametric Spearman’s rank sum statistic [Hill and Lewicki, 2006], for all cores except Humboldt, the null hypothesis that the anthropogenic wintertime deviations from the annual mean were not significantly different from the preanthropogenic wintertime deviations (P 0.01) was rejected. For summertime deviations, there was no significant difference. The sites most affected are D3, D2, and Summit, which are further south and in a region that is more significantly influenced by enhanced transport since 1940 than the other three cores

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(Burkhart, manuscript in preparation, 2006). For most sites in this study, accumulation is high enough throughout the year to preserve the annual signal in the records. Humboldt may be a possible exception. [40] It is unlikely that the NAO influence over accumulation drives the pattern of correlation to concentration. While the results here show an opposite response to the NAO between the variables (concentration being positively correlated and accumulation being negatively correlated), which could provide evidence of a ‘‘dilution’’ effect [Herron, 1982], they also indicate, as do those of Burkhart et al. [2004], that there is no pattern of correlation between accumulation and concentration when examined temporally within an individual ice core time series. Nitrogen deposition over the Greenland Ice Sheet is dominated by wet deposition [Burkhart et al., 2004; Fischer et al., 1998], recent increases in anthropogenic emissions significantly enhance winter and spring atmospheric concentrations during Arctic Haze events while natural sources are low [Scheuer et al., 2003]. During this period the NAO influence over atmospheric transport processes is greatest [Eckhardt et al., 2003; Li et al., 2002]. Likewise, NAO has been demonstrated to most actively influence climate during the winter and early spring [Bromwich et al., 1999, 2001; Dickson et al., 2000; Wanner et al., 2001], which in turn would most strongly influence the anthropogenically affected component of the global nitrogen cycle recorded in Greenland ice cores. The fact that nitrate concentration and accumulation rate both correlate with the NAO index, but not with each other, suggests that the source regions and transport patterns to Greenland of moisture and nitrate are decoupled. This clearly is the case for the source region, which is continental for nitrate and marine for moisture. Thus the nitrate and accumulation variability associated with the NAO represent different manifestations of the latter. Finally, geographical variability and changes in the source regions concurrent with the Northern Hemisphere increases in nitrate emissions needs to be considered. It is possible that as a result of shifted source regions, the NAO correlations are more significant.

5. Conclusions [41] Over the past 75 years, nitrate concentration has increased over 60% on the northwestern portion of the

Table 7. Correlation Coefficients for Concentration With the Luterbacher North Atlantic Oscillation for Preanthropogenic Versus Anthropogenic Periodsa 1789 – 1894 Humboldt GITS NASAU Summit D2 D3

1895 – 1994

Spring

March

Spring

March

-

0.28 0.23 0.33 -

0.23 0.34 0.30 0.31 0.36 -

0.41 0.65 0.63 0.64 0.54

0.21 0.21 0.35

a Correlation coefficients for 5-year triangular filtered time series of concentration with Luterbacher index. All values are significant at the 95% level, bold values are significant at the 99% level, and insignificant coefficients are not shown.

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Figure 11. Seasonal cycle of nitrate from 15 years of preanthropogenic data (dashed) and 15 years of anthropogenic (shaded) data. Seasonal timing was developed from linear interpolations between the wintertime hydrogen peroxide minimum, the calcium spring peak (when available), and the hydrogen peroxide summertime maximum. Error bars are one standard deviation of measurements from within the 15 years of data used for each period. Note the increase during the wintertime period (0.7).

Greenland Ice Sheet. Anthropogenic activities have influenced the recorded nitrate signal as early as 1890, with the influence increasing significantly after 1940. Nitrate flux is affected by climate-driven oscillations in both concentration and accumulation, and by recent anthropogenic increases in concentration. These consistent increases in ice core nitrate concentrations, which reflect European and North American concentration changes resulting from human activity, are strongly covarying in all six records during the anthropogenic, while preanthropogenic correlations are less significant. [42] Periodicity in the nitrate concentration record is positively correlated with the NAO, with as much as 43% of the variability attributable to the climate index during the last 100 years. Correlations during the prior, preanthropogenic 100-year period are of opposite sign and weaker, indicating the climate anomaly is in an active state and acting predominantly on the winter and early spring atmospheric concentrations, which are presumably influenced most by anthropogenic sources. This is identified in subannual records of nitrate concentration that show the wintertime concentrations are most significantly affected by the anthropogenic increases. The NAO is anticorrelated to accumulation variability, though equivalent in magnitude as the relation to concentration during the anthropogenic period. Nonetheless, there does not appear to be a relationship between accumulation and nitrate within an individual ice core time series when sufficient accumulation is present to preserve nitrate as indicated by annual intracore studies of the two variables. Thus the observed nitrate and accumulation variability associated with the NAO seem to represent unrelated manifestations of the latter consistent

with the different source regions and transport pattern for pollutants and moisture. [43] During the preanthropogenic period the correlation between nitrate and NAO is on the order of about half that for accumulation versus NAO, and of lower significance. During the anthropogenic the relationship to the NAO is significantly stronger, providing further evidence of an NAO influence on atmospheric pollutant transport. Still, further investigations using transport model simulations and high-resolution records and measurements will likely be required to resolve the relationship. While the data demonstrate an increased relationship between the NAO and concentration during the anthropogenic, they do not explain the direction of the relationship. The question as to whether or not anthropogenic influences are driving the NAO into its present, more coherent state through changes in the atmospheric composition needs to be explored. [44] Acknowledgments. This research was supported in part by NASA research grants NNG04GB26G, NAG5-10264, and NAG5-12752 and the National Science Foundation grants OPP-0133204, OPP-0221515, and OPP-9813442, as well as a NASA Earth System Science Fellowship awarded to J. Burkhart. Research on the Greenland Ice Sheet is made possible with the generous permission of the Danish Polar Centre and Greenland Home Rule Ministry of Environment and Nature. M. Hutterli was partly funded by the EC project PACLIVA (EVR1-2002-000413). The authors would also like to thank M. Allen for his comments and input regarding the SSA analysis and M. Frey and D. Belle-Oudrey for their contribution to the PARCA ice core analysis.

References Allen, M. R., and L. A. Smith (1996), Monte Carlo SSA: Detecting irregular oscillations in the presence of colored noise, J. Clim., 9, 3373 – 3404.

12 of 14

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Alley, R. B., A. J. Gow, S. J. Johnsen, J. Kipfstuhl, D. A. Meese, and T. Thorsteinsson (1995), Comparison of deep ice cores, Nature, 373, 393 – 394. Anklin, M., and R. C. Bales (1997), Recent increase in H2O2 concentration at Summit, Greenland, J. Geophys. Res., 102, 19,099 – 19,104. Anklin, M., R. C. Bales, E. Mosley-Thompson, and K. Steffen (1998), Annual accumulation at two sites in northwest Greenland during recent centuries, J. Geophys. Res., 103, 28,775 – 28,783. Appenzeller, C., J. Schwander, S. Sommer, and T. F. Stocker (1998a), The North Atlantic Oscillation and its imprint on precipitation and ice accumulation in Greenland, Geophys. Res. Lett., 25, 1939 – 1942. Appenzeller, C., T. F. Stocker, and M. Anklin (1998b), North Atlantic Oscillation dynamics recorded in Greenland ice cores, Science, 282, 446 – 449. Bales, R. C., J. R. McConnell, E. Mosley-Thompson, and G. Lamorey (2001a), Accumulation map for the Greenland Ice Sheet: 1971 – 1990, Geophys. Res. Lett., 28, 2967 – 2970. Bales, R. C., E. Mosley-Thompson, and J. R. McConnell (2001b), Variability of accumulation in northwest Greenland over the past 250 years, Geophys. Res. Lett., 28, 2679 – 2682. Beine, H. J., F. Domine, W. Simpson, R. E. Honrath, R. Sparapani, X. L. Zhou, and M. King (2002), Snow-pile and chamber experiments during the Polar Sunrise Experiment ‘Alert 2000’: Exploration of nitrogen chemistry, Atmos. Environ., 36, 2707 – 2719. Bromwich, D. H., Q. S. Chen, Y. F. Li, and R. I. Cullather (1999), Precipitation over Greenland and its relation to the North Atlantic Oscillation, J. Geophys. Res., 104, 22,103 – 22,115. Bromwich, D. H., Q. S. Chen, L. S. Bai, E. N. Cassano, and Y. F. Li (2001), Modeled precipitation variability over the Greenland ice sheet, J. Geophys. Res., 106, 33,891 – 33,908. Broomhead, D. S., and R. Jones (1989), Time-series analysis, Proc. R. Soc., Ser. A, 423, 103 – 121. Burkhart, J. F., M. Hutterli, R. C. Bales, and J. R. McConnell (2004), Seasonal accumulation timing and preservation of nitrate in firn at Summit, Greenland, J. Geophys. Res., 109, D19302, doi:10.1029/ 2004JD004658. Chakravarti, I., R. Laha, and J. Roy (1967), Handbook of Methods of Applied Statistics, vol. 1, pp. 392 – 394, John Wiley, Hoboken, N. J. Curran, M. A. J., T. D. van Ommen, and V. Morgan (1998), Seasonal characteristics of the major ions in the high-accumulation Dome Summit South ice core, Law Dome, Antarctica, Ann, Glaciol., 27, 385 – 390. Dansgaard, W., and S. J. Johnsen (1969), A flow model and a time scale for the ice core from Camp Century, Greenland, J. Glaciol., 8, 215 – 223. Dickson, R. R., T. J. Osborn, J. W. Hurrell, J. Meincke, J. Blindheim, B. Adlandsvik, T. Vinje, G. Alekseev, and W. Maslowski (2000), The Arctic Ocean response to the North Atlantic Oscillation, J. Clim., 13, 2671 – 2696. Eckhardt, S., et al. (2003), The North Atlantic Oscillation controls air pollution transport to the Arctic, Atmos. Chem. Phys., 3, 1769 – 1778. Environmental Protection Agency (2003), Latest Findings on National Air Quality: 2002 Status and Trends, Rep. 454/K-03-001, Off. of Air Qual. and Stand., Research Triangle Park, N. C. Fischer, H., and D. Wagenbach (1996), Large-scale spatial trends in recent firn chemistry along an east-west transect through central Greenland, Atmos. Environ., 30, 3227 – 3238. Fischer, H., D. Wagenbach, and J. Kipfstuhl (1998), Sulfate and nitrate firn concentrations on the Greenland ice sheet: 2. Temporal anthropogenic deposition changes, J. Geophys. Res., 103, 21,935 – 21,942. Fisher, D. A., N. Reeh, and H. B. Clausen (1985), Stratigraphic noise in time-series derived from ice cores, Ann. Glaciol., 7, 76 – 83. Galloway, J. N., and E. B. Cowling (2002), Reactive nitrogen and the world: 200 years of change, Ambio, 31, 64 – 71. Galloway, J. N., E. B. Cowling, S. P. Seitzinger, and R. H. Socolow (2002), Reactive nitrogen: Too much of a good thing?, Ambio, 31, 60 – 63. Galloway, J. N., et al. (2004), Nitrogen cycles: Past, present, and future, Biogeochemistry, 70, 153 – 226. Ga´miz-Fortis, S. R., D. Pozo-Va´zquez, M. J. Esteban-Parra, and Y. CastroDı´ez (2002), Spectral characteristics and predictability of the NAO assessed through Singular Spectral Analysis, J. Geophys. Res., 107(D23), 4685, doi:10.1029/2001JD001436. Ghil, M. (1986), Mathematical problems in climate dynamics, J. Stat. Phys., 44, 1026 – 1032. Goto-Azuma, K., and R. M. Koerner (2001), Ice core studies of anthropogenic sulfate and nitrate trends in the Arctic, J. Geophys. Res., 106, 4959 – 4969. Goto-Azuma, K., R. M. Koerner, and D. A. Fisher (2002), An ice core record over the last two centuries from Penny Ice Cap, Baffin Island, Canada, Ann. Glaciol., 35, 29 – 35.

D22309

Gugele, B. B., and M. Ritter (2002), Annual European Community CLRTAP emission inventory 1990 – 2000, Tech. Rep. 91, Eur. Environ. Agency, Copenhagen, Denmark. Herron, M. M. (1982), Impurity sources of F-, Cl-, NO3 – and SO24 in Greenland and Antarctic precipitation, J. Geophys. Res., 87, 3052 – 3060. Herron, M. M., and C. C. Langway (1978), Seasonal variations in Ross Ice Shelf precipitation chemistry (abstract), Eos Trans. AGU, 59, 308. Herron, M. M., S. L. Herron, and C. C. Langway (1981), Climatic signal of ice melt features in southern Greenland, Nature, 293, 389 – 391. Hill, T., and P. Lewicki (2006), STATISTICS: Methods and Applications, StatSoft, Tulsa, Okla. Howarth, R. W., E. W. Boyer, W. J. Pabich, and J. N. Galloway (2002), Nitrogen use in the United States from 1961 – 2000 and potential future trends, Ambio, 31, 88 – 96. Hurrell, J. W. (1995), Decadal trends in the North Atlantic Oscillation: Regional temperatures and precipitation, Science, 269, 676 – 679. Hutterli, M. A., C. C. Raible, and T. F. Stocker (2005), Reconstructing climate variability from Greenland ice sheet accumulation: An ERA40 study, Geophys. Res. Lett., 32, L23712, doi:10.1029/2005GL024745. Jones, P. D., T. Jonsson, and D. Wheeler (1997), Extension to the North Atlantic Oscillation using early instrumental pressure observations from Gibraltar and south-west Iceland, Int. J. Climatol., 17, 1433 – 1450. Kekonen, T., J. C. Moore, R. Mulvaney, E. Isaksson, V. Pohjola, and R. S. W. Van de Wal (2002), A 800 year record of nitrate from the Lomonosovfonna ice core, Svalbard, Ann. Glaciol., 35, 261 – 265. Koide, M., E. D. Goldberg, M. M. Herron, and C. C. Langway (1977), Transuranic depositional history in south Greenland firn layers, Nature, 269, 137 – 139. Legrand, M., and P. Mayewski (1997), Glaciochemistry of polar ice cores: A review, Rev. Geophys., 35, 219 – 243. Legrand, M., M. Deangelis, T. Staffelbach, A. Neftel, and B. Stauffer (1992), Large perturbations of ammonium and organic-acids content in the Summit-Greenland ice core, fingerprint from forest-fires?, Geophys. Res. Lett., 19, 473 – 475. Li, Q., et al. (2002), Transatlantic transport of pollution and its effects on surface ozone in Europe and North America, J. Geophys. Res., 107(D13), 4166, doi:10.1029/2001JD001422. Luterbacher, J., C. Schmutz, D. Gyalistras, E. Xoplaki, and H. Wanner (1999), Reconstruction of monthly NAO and EU indices back to AD 1675, Geophys. Res. Lett., 26, 2745 – 2748. Mayewski, P. A., W. B. Lyons, M. J. Spencer, M. S. Twickler, C. F. Buck, and S. Whitlow (1990), An ice-core record of atmospheric response to anthropogenic sulfate and nitrate, Nature, 346, 554 – 556. Mayewski, P. A., L. D. Meeker, M. C. Morrison, M. S. Twickler, S. I. Whitlow, K. K. Ferland, D. A. Meese, M. R. Legrand, and J. P. Steffensen (1993), Greenland ice core signal characteristics: An expanded view of climate change, J. Geophys. Res., 98, 12,839 – 12,847. McConnell, J. R., R. C. Bales, J. R. Winterle, H. Kuhns, and C. R. Stearns (1997), A lumped parameter model for the atmosphere-to-snow transfer function for hydrogen peroxide, J. Geophys. Res., 102, 26,809 – 26,818. McConnell, J. R., G. W. Lamorey, and M. A. Hutterli (2002), A 250-year high-resolution record of Pb flux and crustal enrichment in central Greenland, Geophys. Res. Lett., 29(23), 2130, doi:10.1029/2002GL016016. Mulvaney, R., D. Wagenbach, and E. W. Wolff (1998), Postdepositional change in snowpack nitrate from observation of year-round near-surface snow in coastal Antarctica, J. Geophys. Res., 103, 11,021 – 11,031. Rogers, J. C. (1990), Patterns of low-frequency monthly sea-level pressure variability (1899 – 1986) and associated wave cyclone frequencies, J. Clim., 3, 1364 – 1379. Ro¨thlisberger, R., M. Bigler, M. Hutterli, S. Sommer, B. Stauffer, H. G. Junghans, and D. Wagenbach (2000a), Technique for continuous highresolution analysis of trace substances in firn and ice cores, Environ. Sci. Technol., 34, 338 – 342. Ro¨thlisberger, R., M. A. Hutterli, S. Sommer, E. W. Wolff, and R. Mulvaney (2000b), Factors controlling nitrate in ice cores: Evidence from the Dome C deep ice core, J. Geophys. Res., 105, 20,565 – 20,572. Ro¨thlisberger, R., et al. (2002), Nitrate in Greenland and Antarctic ice cores: A detailed description of post-depositional processes, Ann. Glaciol., 35, 209 – 216. Ro¨thlisberger, R., R. Mulvaney, E. W. Wolff, M. A. Hutterli, M. Bigler, M. de Angelis, M. E. Hansson, J. P. Steffensen, and R. Udisti (2003), Limited dechlorination of sea-salt aerosols during the last glacial period: Evidence from the European Project for Ice Coring in Antarctica (EPICA) Dome C ice core, J. Geophys. Res., 108(D16), 4526, doi:10.1029/2003JD003604. Scheuer, E., R. W. Talbot, J. E. Dibb, G. K. Seid, L. DeBell, and B. Lefer (2003), Seasonal distributions of fine aerosol sulfate in the North American Arctic basin during TOPSE, J. Geophys. Res., 108(D4), 8370, doi:10.1029/2001JD001364.

13 of 14

D22309


Sommer, S., D. Wagenbach, R. Mulvaney, and H. Fischer (2000), Glaciochemical study spanning the past 2 kyr on three ice cores from Dronning Maud Land, Antarctica: 2. Seasonally resolved chemical records, J. Geophys. Res., 105, 29,423 – 29,433. Stewart, R. W. (1995), Reply to comment by XXX on ‘‘Multiple steadystates in atmospheric chemistry’’, J. Geophys. Res., 100, 11,703. Thompson, A. M. (1995), Measuring and modeling the tropospheric hydroxyl radical (Oh), J. Atmos. Sci., 52, 3315 – 3327. Thompson, A. M., and R. W. Stewart (1991), How chemical-kinetics uncertainties affect concentrations computed in an atmospheric photochemical model, Chemom. Intell. Lab. Syst., 10, 69 – 79. Thompson, A. M., et al. (1996), Ozone over southern Africa during SAFARI-92 TRACE A, J. Geophys. Res., 101, 23,793 – 23,807. Thompson, L. G., et al. (2002), Kilimanjaro ice core records: Evidence of Holocene climate change in tropical Africa, Science, 298, 589 – 593. Thompson, L. G., E. Mosley-Thompson, M. E. Davis, P. N. Lin, K. Henderson, and T. A. Mashiotta (2003), Tropical glacier and ice core evidence of climate change on annual to millennial time scales, Clim. Change, 59, 137 – 155. van Aardenne, J. A., G. R. Carmichael, H. Levy, D. Streets, and L. Hordijk (1999), Anthropogenic NOx emissions in Asia in the period 1990 – 2020, Atmos. Environ., 33, 633 – 646. van Aardenne, J. A., F. J. Dentener, J. G. J. Olivier, C. G. M. Klein Goldewijk, and J. Lelieveld (2001), A 1° 1° resolution data set of historical anthropogenic trace gas emissions for the period 1890 – 1990, Global Biogeochem. Cycles, 15(4), 909 – 928.

D22309

Vautard, R., and M. Ghil (1989), Singular Spectrum Analysis in nonlinear dynamics, with applications to paleoclimatic time-series, Physica D, 35, 395 – 424. Vautard, R., P. Yiou, and M. Ghil (1992), Singular-Spectrum Analysis—A toolkit for short, noisy chaotic signals, Physica D, 58, 95 – 126. Wanner, H., S. Bronnimann, C. Casty, D. Gyalistras, J. Luterbacher, C. Schmutz, D. B. Stephenson, and E. Xoplaki (2001), North Atlantic Oscillation—Concepts and studies, Surv. Geophys., 22, 321 – 382. Wolff, E. W., and R. C. Bales (1996), Chemical Exchange Between the Atmosphere and Polar Snow, 675 pp., Springer, New York. Wolff, E. W., A. E. Jones, T. J. Martin, and T. C. Grenfell (2002), Modelling photochemical NOX production and nitrate loss in the upper snowpack of Antarctica, Geophys. Res. Lett., 29(20), 1944, doi:10.1029/ 2002GL015823. Yalcin, K., and C. P. Wake (2001), Anthropogenic signals recorded in an ice core from Eclipse Icefield, Yukon Territory, Canada, Geophys. Res. Lett., 28, 4487 – 4490. Yang, Q. Z., P. A. Mayewski, S. Whitlow, M. Twickler, M. Morrison, R. Talbot, J. Dibb, and E. Linder (1995), Global perspective of nitrate flux in ice cores, J. Geophys. Res., 100, 5113 – 5121. R. C. Bales and J. F. Burkhart, School of Engineering, University of California, Merced, CA 95301, USA. ([email protected]) M. A. Hutterli, British Antarctic Survey, Cambridge CB3 0ET, UK. J. R. McConnell, Division of Hydrologic Sciences, Desert Research Institute, Reno, NV 89512, USA.

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