Hostname: page-component-8448b6f56d-tj2md Total loading time: 0 Render date: 2024-04-24T13:31:29.974Z Has data issue: false hasContentIssue false
  • English
  • Français

Carbon dioxide flux in the ablation area of Koxkar glacier, western Tien Shan, China

Published online by Cambridge University Press:  26 July 2017

Jian Wang ,
Haidong Han  and
Shiqiang Zhang
Jian Wang
Affiliation:
State Key Laboratory of Cryosphere Science, Cold and Arid Regions Environmental and Engineering Research Institute, Chinese Academy of Sciences, Lanzhou, China E-mail: wjshuigong@lzb.ac.cn
Haidong Han
Affiliation:
State Key Laboratory of Cryosphere Science, Cold and Arid Regions Environmental and Engineering Research Institute, Chinese Academy of Sciences, Lanzhou, China E-mail: wjshuigong@lzb.ac.cn
Shiqiang Zhang
Affiliation:
Northwest University, Xi’an, China
Rights & Permissions [Opens in a new window]

Abstract

Accelerating loss of glacial mass caused by rising global temperatures has significant implications. The global cycle of the greenhouse gas CO2 is also associated with mineral weathering and glaciation. In glaciated areas, most estimates of atmospheric CO2 consumption are confined to chemical ionic mass balance or analog modeling methods. We applied the gradient method to the surface of Koxkar glacier, western Tien Shan, China, for a 5 month period during 2012. The overall net glacier-system CO2 exchange (NGE) rate was measured as -0.05 and -0.07mmol m–2 s–1 for regions of exposed ice and supraglacial moraine, respectively. This suggests that atmospheric CO2 drawdown may occur during ice melting because of consumption of H+ by CO2 hydrolysis that occurs in solutions. Using the degree-day model to calculate glacier ablation in bare-ice regions and considering characteristics of the NGE rate in the supraglacial debris region with the support of GIS, the daily NGE rate was estimated to be -1.23 ± 0.17μmmol m–2 d–1 between Julian days 125 and 268 of 2012. These findings present a new approach for modeling the dynamics of glacial CO2 sinks undergoing melting, and develop an understanding of the mechanism of atmospheric CO2 exchange.

Keywords

atmosphere/ice/ocean interactionsglacier chemistryice/atmosphere interactions
Type
Research Article
Information
Annals of Glaciology , Volume 55 , Issue 66 , 2014 , pp. 231 - 238
Creative Commons
Creative Common License - CCCreative Common License - BY
Copyright © The Author(s) 2014 This is an Open Access article, distributed under the terms of the Creative Commons Attribution license. (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited.
Copyright
Copyright © The Author(s) [year] 2014

Introduction

Global mean surface air temperature has increased by ~0.74°C over the past 100 years, and is predicted to rise an additional 1.1-6.4°C by the end of the present century (Reference SolomonSolomon and others, 2007). This warming has influenced alpine glacier fluctuation and runoff, resulting in annual mass losses of up to 3 ma–1 (e.g. the European Alps; Reference Zemp, Frauenfelder, Haeberli and HoelzleZemp and others, 2005). Glacier mass loss is expected to continue, and simulations based on climate warming from greenhouse gases predict a 20% increase in mean annual discharge of the great Arctic rivers (Reference Macdonald, Harner and FyfeMacdonald and others, 2005). In China, 82.2% of all monitored glaciers have retreated, with a total area loss of 4.5% from the 1950s to the late 1990s (Reference Liu, Ding, Li, Shangguan and ZhangLiu and others, 2006).

Because warming-induced alpine glacier melting is likely to intensify, water-rock interactions such as sulfide oxidation and carbonate dissolution are also expected to increase. Glaciation is responsible for a significant drawdown of atmospheric CO2, generating a negative feedback on climate (Reference Sharp, Tranter, Brown and SkidmoreSharp and others, 1995; Reference Tranter and BottrellTranter, 1996; Reference Hodson, Porter, Lowe and MumfordHodson and others, 2002; Reference Yde, Knudsen and NielsenYde and others, 2005; Bartoszewski, 2008). It has long been recognized that rates of terrestrial chemical erosion may influence the atmospheric concentration of CO2, a radiatively important gas contributing to mean global temperature regulation (Reference Raymo and RuddimanRaymo and Ruddiman, 1992). Because of its potential impact on climate at glacial-interglacial timescales, CO2 sequestration during episodes of deglaciation has attracted considerable attention (Reference BrownBrown, 2002).

Research on carbon dioxide drawdown in glaciated catchments has been launched in recent years (Reference Hodson, Porter, Lowe and MumfordHodson and others, 2002; Reference Yde, Knudsen and NielsenYde and others, 2005; Reference Krawczyk and BartoszewskiKrawczyk and others, 2008; Reference Roberts, Yde, Knudsen, Long and LloydRoberts and others, 2008). However, these studies have been almost entirely reliant on the ionic mass-balance method of carbon dioxide flux calculations, without direct CO2 concentration and flux monitoring systems. Moreover, eddy covariance data of CO2 flux have been collected over the horizontal surfaces of large ice bodies (Reference Mölg, Hardy and KaserMölg and others, 2003; Reference Cullen, Mölg, Kaser, Steffen and HardyCullen and others, 2007; Mac-Donell and others, 2010; Reference Jarosch, Anslow and SheaJarosch and others, 2011) and in complex terrain (Reference Rotach, Calanca, Weigel and AndrettaRotach and others, 2003; Reference Hiller, Zeeman and EugsterHiller and others, 2008; Reference GuoGuo and others, 2011; Reference JocherJocher and others, 2012). Such an approach may be unsuitable for the study of alpine glaciers, given complex terrain, frequent precipitation and fog, and other factors. The gradient method for collecting and calculating CO2 flux has been used to study net CO2 exchange with the atmosphere in a wide variety of terrains (snow, grassland, forest, bare land, and alpine) (Reference SteffenSteffen and others, 2008; Reference Bowling and MassmanBowling and Massman, 2011; Reference Pumpanen, Kulmala, Bäck, Lappalainen and NieminenPumpanen and others, 2011), including complex terrains. Thus, the gradient method may be useful for the study of processes underlying CO2 exchange between the atmosphere and a glacial surface, providing continuous data without interference from precipitation, fog and refrozen condensed water (Reference Bowling and MassmanBowling and Massman, 2011; Reference Pumpanen, Kulmala, Bäck, Lappalainen and NieminenPumpanen and others, 2011).

Using the mass-balance method, total solute fluxes and transient carbon dioxide sinks (which accounted for 14.2% of total solutes in bulk river water) were estimated at 791.2 kg (km 2 d)–1 and 81.0 kg (km2 d)–1 in the Koxkar glaciated basin (summer 2004), respectively (Reference Wang, Xu, Zhang, Liu and HanWang and others, 2010). Using the flux gradient method, this paper aims to estimate CO2 fluxes over bare ice and supraglacial moraine at Koxkar glacier during the 2012 melt season. These results, together with other data, may shed light on the influence of atmospheric factors on CO2 fluxes. Specifically, these data provide new insight into CO2 concentrations and fluxes in glaciated basins, which may be used for modeling CO2 change on glacial–interglacial timescales (e.g. Reference TranterTranter and others, 2002). A further aim is to seek correlations between CO2 flux and other factors across different underlying surfaces on Koxkar glacier, which may facilitate conclusions regarding the feedback relationship of glacial change to regional atmospheric CO2 circulation.

Site Description

The glaciated Koxkar basin (41842’–41853’ N, 79859’– 80810’E; Fig. 1) is on the southwest side of Toumuer mountain, northwest China. The glacier is 25.1 km long and has an area of 83.56km2. Supraglacial debris covers -15.6 km2, representing 83% of the total ablation area (Reference Han, Wang, Wei and LiuHan and others, 2010). Mean annual air temperature observed near the glacier terminus is 0.77°C, and mean summer temperature is 7.74°C (Reference HanHan and others, 2008). The main source of precipitation is water vapor from the Atlantic and Arctic Oceans (Reference Kang, Zhu and HuangKang and others, 1985). Annual precipitation, 81% of which occurs from May through September, is ~630 mm at the end of the glacier. Precipitation in the study area is in a solid state (snow and hail). A field investigation from 2003 to 2012 indicated annual discharge at the glacial terminus of >1.0 x 108m3, mainly during the warmer half of the year (94.5% of total runoff flux was from May through October).

Fig. 1. Map of the Koxkar glacier region (northwest China) sampling sites.

Two CO2 flux gradient observation stations (Fig. 1) sit atop bare ice (site A: 41°47ʹN, 808060E; 3730ma.s.l.) and supraglacial moraine (site B: 418430N, 80°09ʹE; 3212ma.s.l.). Debris thickness at site A is <0.01 m and discontinuous, while the thickness at site B is ~0.70 m. The debris is mainly gray or dark-gray granite stone powder, broken stone particles, and rock mass, which covers 83% of the total melt area. Therefore, moraine is the principal physical source of crustal dissoluble ions. The nearly horizontal surfaces at sites A and B have an average surface slope less than 28, and a fetch of several hundred meters in the direction of the prevailing wind, which most often should be a valley-mountain breeze.

Methods

During the observation period, we established two synchronous gradient observational systems to measure two-tiered CO2 concentrations, wind speed, wind direction, temperature and humidity (2.0 and 1.0 m above the surface), and a series of radiation sensors that included total solar radiation, net radiation and reflection radiation in bare-ice and supraglacial moraine regions. Supraglacial two-tiered CO2 concentrations (2.0 and 1.0 m above the surface) were determined using infrared CO2 sensors (ES-D type, Sense Air, Sweden), with a variance of ±5.4% for CO2 (Reference Rinne, Tuovinen, Laurila, Hakola, Aurela and HypénRinne and others, 2000; Lu and others, 2010; Reference Fang, Shi, Lu and ChenFang and others, 2011). Data (e.g. CO2 concentration, wind speed, wind direction, temperature, humidity, total solar radiation, net radiation, reflection radiation, and precipitation) were obtained using a PC-3 data acquisition system, and were automatically updated hourly throughout the observation period. Generally, the effective distance was less than ten times the height of the equipment probes. Our gradient observational stations were located in the central part of the glacier, away from nearby grasslands (-1.43 km away), to reduce the possibility of the grassland affecting the CO2 measurement. Unfortunately, we could not obtain synchronous data because of complications with the solar power supply.

The net glacier-system CO2 exchange (NGE) rate between the glacier surface and atmosphere for the temporally and spatially integrated net glacier system is defined as

(1)

where Fc is its vertical flux (upward flux being positive) and S is the change of CO2 storage below the CO2 infrared sensors.

We applied the gradient method, in which vertical CO2 fluxes at the glacier surface are estimated by the aerodynamic gradient method (e.g. Reference Sutton, Pitcairn and FowlerSutton and others, 1993). The flux Fc of a component with concentration c is calculated from the product of friction velocity u* , and a concentration scaling parameter c * as (Reference Rinne, Tuovinen, Laurila, Hakola, Aurela and HypénRinne and others, 2000; Reference LoubetLoubet and others, 2013)

(2)

where u, and c. are derived from the stability-corrected gradients of wind speed (u) and CO2 concentration (c) vs height (z):

(3)

where d is the zero plane displacement height, which represents the shift in aerodynamic ‘ground’ because of the presence of the glacier surface, z is the mounting height of the sensors (2 m), k is the von Kármán constant with values between 0.35 and 0.43 (usually 0.4), and m is the integrated stability correction function for momentum.

Reference Harman and FinniganHarman and others (2008) developed an analytical transfer model for the roughness layer that includes two displacement heights; the model was extended by Reference Siqueira and KatulSiqueira and Katul (2010) to account for stomatal regulation and soil respiration. Reference Harman and FinniganHarman and others (2008) showed that these additional functions would lead to an additional integral term H in the concentration profile, which in turn would lead to a new approximation of the concentration scaling parameter c* :

(4)

Reference Siqueira and KatulSiqueira and Katul (2010) give the following expression for 𝜓H:

(5)

where Sn is the Schmidt number, (β = c*/uh, dc and dm are the scalar and momentum displacement heights, and c 2c is a constant that can be taken as 1 in the first approximation. More details of 𝜓 m, dc and dm are provided by Benjamin and others (2013).

The value for S was calculated from vertical CO2 concentration profiles (Reference Aubinet, Chermanne, Vandenhaute, Longdoz, Yernaux and LaitatAubinet and others, 2001; Reference AraújoAraújo and others, 2010

(6)

where P a is atmospheric pressure, R is the molar gas constant, T a is the air temperature (K), h m is the maximum measurement height above ground level (m), c is the CO2 concentration, t is time (s), and z is the height about ground level (m). Details of the S calculation are provided by Reference ValentiniValentini and others (2000) and Reference KowalskiKowalski (2008).

Results

CO2 fluctuations

Typical fluctuations in hourly CO2 concentration, atmospheric temperature and wind speed measured 2m above bare ice and supraglacial moraine are shown in Figure 2. Mean wind velocity during the observation periods was 2.3 ms–1 at both stations. Mean temperatures were 3.4°C and 7.6°C, and the amplitudes of dominant fluctuation in CO2 concentration were ~439.3 and 472.1 mgm–3 for sites A and B, respectively. Variations in CO2 concentration gradually decreased, followed by increasing atmospheric temperature, which otherwise only gradually increased. For example, there is strong negative correlation between CO2 concentration and atmospheric temperature at site A. The associated equation is

Fig. 2. Fluctuations of hourly CO2 concentration, atmospheric temperature and wind speed above the surface of Koxkar glacier. Data are from bare ice (site A, right of the vertical dotted line) and above supraglacial moraine (site B, left of the vertical dotted line).

(7)

where C CO2 is the CO2 concentration (mgm–3), and Tatm is atmospheric temperature (°C) measured 2 m above the ice surface.

Based on Eqns (7) and (8) for site B, the CO2 concentration was less influenced by atmospheric temperature. Equation (8) shows the relationship between CO2 concentration and atmospheric temperature at site B:

(8)

Unfortunately, data from sites A and B were not collected simultaneously during the observation period. However, we conclude that the CO2 concentration at site A was dramatically lower than at site B (Fig. 2). This can be explained by the different altitudes and underlying surface conditions at the two sites.

Net glacier-system CO2 exchange (NGE) rate

During the observation period, hourly NGE ranged from –0.74 to +0.48 mmol m–2 s–1 at site A and from –1.81 to +0.66 mmol m–2 s–1 at site B (Table 1). Amplitudes of dominant hourly NGE fluctuation were approximately –0.05 and –0.07 mmol m–2 s–1 for the bare-ice and supraglacial moraine observation points, respectively. These variance results suggest that the fluctuation range of NGE at the supraglacial moraine (site A variance = 60.70) was greater than at bare ice (site B variance = 33.07). Moreover, the maximum and minimum values of hourly NGE were both recorded at site B. Under normal conditions, upward flux (i.e. CO2 release) occurs with precipitation or at night, when ice melt decreases because of reduced air temperature.

Table 1. Hourly NGE (mmol m–2 s–1) at sites A and B on the surface of Koxkar glacier in 2012

The negative mean values of hourly NGE at the two sites imply that the glacial surface was a sink for atmospheric CO2 during the melt season because of the hydrochemical conditions and mineralogical reactions existing under the ice-melt water (Reference Hodson, Porter, Lowe and MumfordHodson and others, 2002 ; Reference TranterTranter and others, 2002; Reference Yde, Knudsen and NielsenYde and others, 2005; Reference Krawczyk and PetterssonKrawczyk and others, 2007, 2008; Reference Lerman, Wu and MackenzieLerman and others, 2007). In glaciated regions, these chemical reactions are primarily carbonate and silicate dissolution, for example:

(9)

(10)

Although there was a little cryoconite at the bare-ice site, there were limited amounts of carbonate, silicate and other soluble materials, which could inhibit chemical reactions such as those described by Eqns (9) and (10). Substantial glacial debris at the supraglacial moraine site, including abundant carbonate, silicate and potash/soda feldspar, generated ample chemical hydrolysis under precipitation or ice/snow meltwater conditions. Such mineral differences between sites can account for the differences in hourly NGE rates.

Discussion

Errors in the NGE calculation

In the past, errors in the aerodynamic gradient method used to calculate the atmospheric H2O/CO2 flux have been extensively studied for sites in such locations as grassland, forest, tundra and farmland (Reference Wenzel, Kalthoff and HorlacherWenzel and others, 1997; Reference De RidderDe Ridder, 2010). In the Koxkar glaciated area, the main factors that influenced NGE accuracy were as follows:

  1. 1. The variance, ±5.4%, of CO2 measured by infrared sensors was an objective value, which might cause 4.8-7.2% error in the NGE result, with a mean value of 5.3%. The sequential sampling of gas concentrations, sourced from ice melting, at various heights above the ice showed a variability in the gradients due to the non-stationarity of the concentrations. These were obviously not an issue for u *, but might be an issue for CO2 flux (Benjamin and others, 2013).

  2. 2. A roughness sub-layer correction has been proposed previously (Reference Wenzel, Kalthoff and HorlacherWenzel and others, 1997; Reference Siqueira and KatulSiqueira and others, 2010; Benjamin and others, 2013). In this work, the roughness sub-layer correction was evaluated based mainly on the approaches of Reference GarrattGarratt (1978), Reference Cellier and BrunetCellier and Brunet (1992) and Reference De RidderDe Ridder (2010). In general, the error most attributed to the geometric correction for the measurement height of the monitoring equipment was <15%.

  3. 3. The concentration and flux footprint errors are mainly the result of local advection error (Reference Marcolla, Cescatti, Montagnani, Manca, Kerschbaumer and MinerbiMarcolla and others, 2005; Reference Feigenwinter, Montagnani and AubinetFeigenwinter and others, 2010; Reference Novick, Brantley, Ford Miniat, Walker and VoseNovick and others, 2014). Usually, the values of horizontal advection and vertical advection were opposite, and their sums were approximately zero (Reference Feigenwinter, Montagnani and AubinetFeigenwinter and others, 2010; Reference Novick, Brantley, Ford Miniat, Walker and VoseNovick and others, 2014). Calculating the horizontal advection should include at least two flux towers. Hence, the flux footprint error is ignored in this paper.

  4. 4. In recent years, englacial gas release has been widely mentioned (Reference Jaworowski, Segalstad and OnoJaworowski and others, 1992; Reference SmellieSmellie, 2006; Reference Ryu and JacobsonRyu and Jacobson, 2012). Many studies have suggested that characteristic gases (including CO2) from various historical periods may be released from air bubbles within ice (Reference Jaworowski, Segalstad and OnoJaworowski and others, 1992; Reference Anderson, Drever, Frost and HoldenAnderson and others, 2000; Reference Ryu and JacobsonRyu and Jacobson, 2012). This raises the possibility that future atmospheric CO2 levels will increase as glaciers retreat or disappear. Although this result appears to conflict with the CO2 consumption of negative total NGE as a result of the chemical reactions described here, the total volume will actually decrease by -10% during ice melt. If we suppose that the CO2 concentration of glacial air bubbles maintains the higher value of AD 1100 (295 ppmv; Reference Barnola, Anklin, Porcheron, Raynaud, Schwander and StaufferBarnola and others, 1995) and that gas pressure inside the bubbles was that of the standard atmosphere, CO2 release was 2.30 mmol m–2 at the bare-ice observation site. This is only ~1.16% of the NGE rate between Julian days 223 and 268 in 2012. As a result, CO2 release from glacial ice was ignored, whereas the NGE in the glacier region was analyzed. However, released CO2 dissolves in water and participates in chemical reactions between ice-melt water and rocks (Reference BrownBrown, 2002; Jacob and others, 2005).

CO2 storage term

The CO2 storage term (S) is an important component in the statistical inference of net ecosystem CO2 exchange (NEE) rates (Reference FinniganFinnigan, 2006, Reference Finnigan2009; Reference KowalskiKowalski, 2008; Araujo and others, 2010). There has been little study of S in glacial regions. During the observation period, daily S values ranged from -1.74 to +1.43 and -1.19 to +1.55 mmol m–2 d–1 at sites A and B, respectively (Fig. 3), with mean values of +0.06 and -0.03 mmol m–2d–1 (about 1.36% and 0.51% of total NGE rates). These data demonstrate that CO2 storage (S) rates had little effect on NGE rates in this glaciated area. Given the rapidly increasing glacial surface temperature during daylight hours, S may be positive, resulting in atmospheric CO2 releases below the CO2 detection limit of the infrared sensors. Glacial meltwater was shown to be a fundamental carrier of chemical reactions, producing transient CO2 drawdown and decreasing air temperature caused by precipitation. The maximum S (1.55 mmol m–2 d–1) was caused by sustained heavy rainfall between Julian days 194 and 196 (total precipitation 44.6 mm), leading to a decrease in air temperature and a reduction of ice melt, thereby inhibiting chemical reactions.

Fig. 3. Study area variations of daily Fc and S at sites A and B (right and left sides of vertical dotted line, respectively).

NGE rates affected by ice-melt intensity (IMI)

The most obvious characteristic of the NGE rate was that glacial meltwater was the fundamental carrier of carbonate and silicate hydrolysis but was not a determining factor in the daily NGE rates at site B (Fig. 4). Moreover, there were no significant changes in IMI, with daily NGE rates fluctuating around -6.26 mmol m–2 d–1 at that site (Table 1). For example, NGE rates at the site were -179.17 and -30.40 mmol m–2 between Julian days 125 (4 May) and 153 (1 June), and 215 (2 August) and 220 (7 August), respectively. The IMI was consistent across the same periods (Table 2). This suggests that the daily NGE rates are relatively stable with abundant soluble substances, and therefore not remarkably affected by IMI. At site A, however, there was correlation between IMI and NGE rates (Eqn (11)), while daily precipitation was <2 mm, demonstrating that the daily NGE rates, including those caused by the dissolution of carbonate and silicate, depended on ice melting. A mass of ice-melt water accelerated the strong chemical reactions, leading to a decrease in NGE rate:

(11)

where IMI is in mm and n is the number of days.

Fig. 4. Relationships of NGE rates, IMI and precipitation at (a) site B and (b) site A.

Table 2. Relationship between IMI and NGE rates at site B in 2012

Based on these results, it would not be possible to use the ice-melting and NGE rates to calculate the yearly flux of atmospheric CO2 consumption in the Koxkar glaciated region. To estimate the NGE rate for the whole glacial area, we used the degree-day model (Reference Singh, Kumar and AroraSingh and others, 2000; Reference Sicart, Hock and SixSicart and others, 2008; Reference MourshedMourshed, 2012; Reference Tennant, Menounos, Ainslie, Shea and JacksonTennant and others, 2012; Reference Mayr, Hagg, Mayer and BraunMayr and others, 2013) to calculate the IMI in the bare-ice region, and considered the characteristics of the NGE rate in the supraglacial debris region with the support of GIS, resulting in a daily NGE rate of about -1.23 ± 0.17 mmol m–2 d–1 between Julian days 125 (4 May) and 268 (24 September) in 2012. This estimate is less than the 1.84 mmol m–2 d–1 that was calculated in terms of ionic mass balance by Reference Wang, Xu, Zhang, Liu and HanWang and others (2010) in 2004, likely by ignoring the chemical reactions that follow glacier surface runoff in englacial conduit geometry. The NGE rate in the Koxkar glaciated area is greater than the CO2 drawdown of the Rhone and Oberaar glacial catchment in the Swiss Alps (Reference Hosein, Arn, Steinmann, Adatte and FöllmiHosein and others, 2004), and also higher than that of the Scottbreen glaciated basin in the Arctic (Reference Krawczyk and BartoszewskiKrawczyk and others, 2008). Substantial glacial debris might be the main reason for the higher chemical erosion and NGE rates in the Koxkar glacier area (Giles, 2002; Reference Hosein, Arn, Steinmann, Adatte and FöllmiHosein and others, 2004; Reference Krawczyk and BartoszewskiKrawczyk and others, 2008; Reference Zhang, Jin, Li, Yu and XiaoZhang and others, 2013).

Conclusions

At Koxkar glacier, atmospheric CO2 concentrations have gradually decreased as atmospheric temperatures have increased. The average values of hourly NGE were approximately –0.05 and –0.07 mmol m–2 s–1 for bare ice and supraglacial moraine, respectively. This implies that the basin is a sink for atmospheric CO2 above the glacial surface during melting seasons because of existing hydrochemical conditions and mineralogical reactions under ice-melting water. The CO2 storage (S) rates had little effect on NGE rates in the glaciated area, accounting for only 1.36% and 0.51% of the total NGE rate at sites A and B, respectively. A NGE rate was analyzed in the glacier region. Using the degree-day model to calculate glacial ablation in a bare-ice region, and considering the characteristics of the NGE rate in a region of supraglacial debris with the support of GIS, the daily NGE rate was calculated as approximately -1.23±0.17mmolm–2d-1 between Julian days 125 and 268 in 2012. This could be lower than the actual value, because chemical reactions that follow the process of glacier surface runoff in englacial conduit geometry are not considered.

Acknowledgements

The work was supported by the China National Natural Science Foundation (grant Nos. 41001039, 41130638 and 41130641). We appreciate the comments of two anonymous reviewers.

References

Anderson, SP, Drever, JI, Frost, CD and Holden, P (2000) Chemical weathering in the foreland of a retreating glacier. Geochim. Cosmochim. Acta, 64(7), 1173–1189 (doi: 10.1016/S0016-7037 (99)00358-0)CrossRefGoogle Scholar
Araújo, AC and 11 others (2010) The spatial variability of CO2 storage and the interpretation of eddy covariance fluxes in central Amazonia. Agric. Forest Meteorol., 150(2), 226–237 (doi: 10.1016/j.agrformet.2009.11.005)CrossRefGoogle Scholar
Aubinet, M, Chermanne, B, Vandenhaute, M, Longdoz, B, Yernaux, M and Laitat, E (2001) Long term carbon dioxide exchange above a mixed forest in the Belgian Ardennes. Agric. Forest Meteorol., 108(4), 293–315 (doi: 10.1016/S0168-1923(01)00244-1)CrossRefGoogle Scholar
Barnola, JM, Anklin, M, Porcheron, J, Raynaud, D, Schwander, J and Stauffer, B (1995) CO2 evolution during the last millennium as recorded by Antarctic and Greenland ice. Tellus, 47B(1–2), 264–272 CrossRefGoogle Scholar
Bowling, DR and Massman, WJ (2011) Persistent wind-induced enhancement of diffusive CO2 transport in a mountain forest snowpack. J. Geophys. Res., 116(G4), G04006 (doi: 10.1029/ 2011JG001722)Google Scholar
Brown, GH (2002) Glacier meltwater hydrochemistry. Appl. Geochem., 17(7), 855–883 (doi: 10.1016/S0883-2927(01)00123-8)CrossRefGoogle Scholar
Cellier, P and Brunet, Y (1992) Flux-gradient relationships above tall plant canopies. Agric. Forest Meteorol., 58(1–2), 93–117 (doi: 10.1016/0168-1923(92)90113-I)CrossRefGoogle Scholar
Cullen, NJ, Mölg, T, Kaser, G, Steffen, K and Hardy, DR (2007) Energy balance model validation on the top of Kilimanjaro, Tanzania, using eddy covariance data. Ann. Glaciol., 46, 227–233 (doi: 10.3189/172756407782871224)CrossRefGoogle Scholar
De Ridder, K (2010) Bulk transfer relations for the roughness sublayer. Bound.-Layer Meteorol., 134(2), 257–267 (doi: 10.1007/s10546-009-9450-y)CrossRefGoogle Scholar
Fang, R, Shi, Y, Lu, C and Chen, X (2011) Effects of elevated CO2 and O3 and N fertilization on amount of soil microbial biomass carbon in spring wheat growing season. Procedia Environ. Sci., 8, 34–39 (doi: 10.1016/j.proenv.2011.10.008)CrossRefGoogle Scholar
Feigenwinter, C, Montagnani, L and Aubinet, M (2010) Plot-scale vertical and horizontal transport of CO2 modified by a persistent slope wind system in and above an alpine forest. Agric. Forest Meteorol., 150(5), 665–673 (doi: 10.1016/j.agrformet.2009.05.009)CrossRefGoogle Scholar
Finnigan, J (2006) The storage term in eddy flux calculations. Agric. Forest Meteorol., 136(3–4), 108–113 (doi: 10.1016/j.agrformet.2004.12.010)CrossRefGoogle Scholar
Finnigan, J (2009) Response to comment by Dr. A.S. Kowalski on ‘The storage term in eddy flux calculations’. Agric. Forest Meteorol., 149(3–4), 725–729 (doi: 10.1016/j.agrformet.2008.10.012)CrossRefGoogle Scholar
Garratt, JR (1978) Flux profile relations above tall vegetation. Q. J. R. Meteorol. Soc., 104(439), 199–211 (doi: 10.1002/qj.49710443915)CrossRefGoogle Scholar
Guo, X and 7 others (2011) Critical evaluation of scalar roughness length parametrizations over a melting valley glacier. Bound.-Layer Meteorol., 139(2), 307–332 (doi: 10.1007/s10546-010-9586-9)CrossRefGoogle Scholar
Han, H and 13 others (2008) Near-surface meteorological characteristics on the Koxkar Baxi Glacier, Tianshan. J. Glaciol. Geocryol., 30(6), 967–975 Google Scholar
Han, H, Wang, J, Wei, J and Liu, S (2010) Backwasting rate on debris-covered Koxkar glacier, Tuomuer mountain, China. J. Glaciol., 56(196), 287–296 (doi: 10.3189/002214310791968430)CrossRefGoogle Scholar
Harman, IN and Finnigan, JJ (2008) Scalar concentration profiles in the canopy and roughness sublayer. Bound.-Layer Meteorol., 129(3), 323–351 (doi: 10.1007/s10546-008-9328-4)CrossRefGoogle Scholar
Hiller, R, Zeeman, MJ and Eugster, W (2008) Eddy-covariance flux measurements in the complex terrain of an Alpine valley in Switzerland. Bound.-Layer Meteorol., 127(3), 449–467 (doi: 10.1007/s10546-008-9267-0)CrossRefGoogle Scholar
Hodson, A, Porter, P, Lowe, A and Mumford, P (2002) Chemical denudation and silicate weathering in Himalayan glacier basins: Batura Glacier, Pakistan. J. Hydrol., 262(1–4), 193–208 (doi: 10.1016/S0022-1694(02)00036-7)CrossRefGoogle Scholar
Hosein, R, Arn, K, Steinmann, P, Adatte, T and Föllmi, KB (2004) Carbonate and silicate weathering in two presently glaciated, crystalline catchments in the Swiss Alps. Geochim. Cosmochim. Acta, 68(5), 1021–1033 (doi: 10.1016/S0016-7037(03)00445-9)CrossRefGoogle Scholar
Jarosch, AH, Anslow, FS and Shea, J (2011) A versatile tower platform for glacier instrumentation: GPS and Eddy Covariance Measurements. In. Extended abstracts and recommendations from the IASC Workshop on the Use of Automatic Measuring Systems on Glaciers, 23–26 March 2011, Pontresina, Switzerland. Institute for Marine and Atmospheric Research, University of Utrecht, Utrecht, 52–55 Google Scholar
Jaworowski, Z, Segalstad, TV and Ono, N (1992) Do glaciers tell a true atmospheric CO2 story? Sci. Total Environ., 114, 227–284 (doi: 10.1016/0048-9697(92)90428-U)CrossRefGoogle Scholar
Jocher, G and 7 others (2012) The near-surface small-scale spatial and temporal variability of sensible and latent heat exchange in the Svalbard region: a case study. ISRN Meteorol., 2012, 357925 (doi: 10.5402/2012/357925)CrossRefGoogle Scholar
Kang, ES, Zhu, SS and Huang, MM (1985) Hydrological characteristics of the glaciers in Mount Tuomuer, Tien Shan. In. Glaciology and meteorology in Mount Tuomuer region, Tien Shan. Academia Sinica. Xijiang People’s Press, Ürümqi, 99–119 [in Chinese with English summary]Google Scholar
Kowalski, AS (2008) Comment on ‘the storage term in eddy flux calculations’. Agric. Forest Meteorol., 148(4), 691–692 (doi: 10.1016/j.agrformet.2007.10.010)CrossRefGoogle Scholar
Krawczyk, WE and Bartoszewski, SA (2008) Crustal solute fluxes and transient carbon dioxide drawdown in the Scottbreen Basin, Svalbard in 2002. J. Hydrol., 362(3–4), 206–219 (doi: 10.1016/ j.jhydrol.2008.08.025)CrossRefGoogle Scholar
Krawczyk, WE and Pettersson, L-E (2007) Chemical denudation rates and carbon dioxide drawdown in an ice-free polar karst catchment: Londonelva, Svalbard. Permafrost Periglac. Process., 18(4), 337–350 (doi: 10.1002/ppp.599)CrossRefGoogle Scholar
Lerman, A, Wu, L and Mackenzie, FT (2007) CO2 and H2SO4 consumption in weathering and material transport to the ocean, and their role in the global carbon balance. Mar. Chem., 106(1–2), 326–350 (doi: 10.1016/j.marchem.2006.04.004)CrossRefGoogle Scholar
Liu, S, Ding, Y, Li, J, Shangguan, D and Zhang, Y (2006) Glaciers in response to recent climate warming in western China. Quat. Sci., 26(5), 762–771 [in Chinese with English summary]Google Scholar
Loubet, B and 15 others (2013) Investigating discrepancies in heat, CO2 fluxes and O 3 deposition velocity over maize as measured by the eddy-covariance and the aerodynamic gradient methods. Agric. Forest Meteorol., 169, 35–50 (doi: 10.1016/j.agrformet. 2012.09.010)CrossRefGoogle Scholar
Lu, C, Shi, Y and Niu, M (2010) Effects of elevated CO2 and O 3 on soil amino sugar from wheat straw decomposition in a meadow brown soil of Northeast China. In. Soil Solutions for a Changing World, Proceedings of the 19th World Congress of Soil Science, 1–6 August 2010, Brisbane, Australia. International Union of Soil Sciences, 29–32 Google Scholar
Macdonald, RW, Harner, T and Fyfe, J (2005) Recent climate change in the Arctic and its impact on contaminant pathways and interpretation of temporal trend data. Sci. Total Environ., 342(1–3), 5–86 (doi: 10.1016/j.scitotenv.2004.12.059)CrossRefGoogle ScholarPubMed
MacDonell, S, Cullen, N, Nicholson, L, Mölg, T and Kinnard, C (2010) The behaviour of turbulent heat fluxes on Guanaco glacier, upper Huasco valley, Chile, using eddy covariance data and energy balance modeling. In. Abstract Book. International Glaciological Conference (VICC 2010) Ice and Climate Change: A View from the South, 1–3 February 2010, Valdivia, Chile. Centro de Estudios Científicos, Valdivia Google Scholar
Marcolla, B, Cescatti, A, Montagnani, L, Manca, G, Kerschbaumer, G and Minerbi, S (2005) Importance of advection in the atmospheric CO2 exchanges of an alpine forest. Agric. Forest Meteorol., 130(3–4), 193–206 (doi: 10.1016/j.agrformet.2005.03.006)CrossRefGoogle Scholar
Mayr, E, Hagg, W, Mayer, C and Braun, L (2013) Calibrating a spatially distributed conceptual hydrological model using runoff, annual mass balance and winter mass balance. J. Hydrol., 478, 40–49 (doi: 10.1016/j.jhydrol.2012.11.035)CrossRefGoogle Scholar
Mölg, T, Hardy, DR and Kaser, G (2003) Solar-radiation-maintained glacier recession on Kilimanjaro drawn from combined ice-radiation geometry modelling. J. Geophys. Res., 108(D23), 4731 (doi: 10.1029/2003JD003456)Google Scholar
Mourshed, M (2012) Relationship between annual mean temperature and degree-days. Energy Build., 54, 418–425 (doi: 10.1016/ j.enbuild.2012.07.024)CrossRefGoogle Scholar
Novick, K, Brantley, S, Ford Miniat, C, Walker, J and Vose, JM (2014) Inferring the contribution of advection to total ecosystem scalar fluxes over a tall forest in complex terrain. Agric. Forest Meteorol., 185, 1–13 (doi: 10.1016/j.agrformet.2013.10.010)CrossRefGoogle Scholar
Pumpanen, J and others (2011) Application of CO2 concentration gradient method for determining soil respiratory fluxes and time delays between photosynthesis and soil respiration. In Kulmala, M, Bäck, J, Lappalainen, HK and Nieminen, T eds. Proceedings of the Annual Workshop ‘Physics, Chemistry, Biology and Meteorology of Atmospheric Composition and Climate Change’, 18–20 May 2011, Helsinki, Finland. (Report Series in Aerosol Science 126) Finnish Center of Excellence and Graduate School, Helsinki http://www.atm.helsinki.fi/faar/reportseries/rs-126.pdf Google Scholar
Raymo, ME and Ruddiman, WF (1992) Tectonic forcing of late Cenozoic climate. Nature, 359(6391), 117–122 (doi: 10.1038/ 359117a0)CrossRefGoogle Scholar
Rinne, J, Tuovinen, J-P, Laurila, T, Hakola, H, Aurela, M and Hypén, H (2000) Measurements of hydrocarbon fluxes by a gradient method above a northern boreal forest. Agric. Forest Meteorol., 102(1), 25–37 (doi: 10.1016/S0168-1923(00)00088-5)CrossRefGoogle Scholar
Roberts, DH, Yde, JC, Knudsen, NT, Long, AJ and Lloyd, JM (2009) Ice marginal dynamics during surge activity, Kuannersuit Glacier, Disko Island, West Greenland. Quat. Sci. Rev., 28(3–4), 209–222 (doi: 10.1016/j.quascirev.2008.10.022)CrossRefGoogle Scholar
Rotach, MW, Calanca, P, Weigel, AH and Andretta, M (2003) On the closure of the surface energy balance in highly complex terrain. In. Proceedings of the International Conference on Alpine Meteorology (ICAM) and Annual Mesoscale Alpine Programme (MAP) Meeting, 19–23 May 2003, Brig, Switzerland, Volume B. (Publications of MeteoSwiss 66) MeteoSwiss, Locarno Monti, 247–250 http://www.map.meteoswiss.ch/map-doc/icam2003/ProceedingsB.pdf Google Scholar
Ryu, J-S and Jacobson, AD (2012) CO2 evasion from the Greenland Ice Sheet: a new carbon–climate feedback. Chemical Geol., 320–321, 80–95 (doi: 10.1016/j.chemgeo.2012.05.024)CrossRefGoogle Scholar
Sharp, M, Tranter, M, Brown, GH and Skidmore, M (1995) Rates of chemical denudation and CO2 drawdown in a glacier-covered alpine catchment. Geology, 23(1), 61–64 (doi: 10.1130/00917613(1995)023<0061:ROCDAC>2.3.CO;2)2.3.CO;2>CrossRefGoogle Scholar
Sicart, JE, Hock, R and Six, D (2008) Glacier melt, air temperature, and energy balance in different climates: the Bolivian Tropics, the French Alps, and northern Sweden. J. Geophys. Res., 113(D24), D24113 (doi: 10.1029/2008JD010406)Google Scholar
Singh, P, Kumar, N and Arora, M (2000) Degree-day factors for snow and ice for Dokriani Glacier, Garhwal Himalayas. J. Hydrol., 235(1–2), 1–11 (doi: 10.1016/S0022-1694(00)00249-3)CrossRefGoogle Scholar
Siqueira, MB and Katul, GG (2010) An analytical model for the distribution of CO2 sources and sinks, fluxes, and mean concentration within the roughness sub-layer. Bound.-Layer Meteorol., 135(1), 31–50 (doi: 10.1007/s10546-009-9453-8)CrossRefGoogle Scholar
Smellie, JL (2006) The relative importance of supraglacial versus subglacial meltwater escape in basaltic subglacial tuya eruptions: an important unresolved conundrum. Earth-Sci. Rev., 74(3–4), 241–268 (doi: 10.1016/j.earscirev.2005.09.004)CrossRefGoogle Scholar
Solomon, S and 7 others eds. (2007) Climate change 2007: the physical science basis. Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge Google Scholar
Steffen, A and 20 others (2008) A synthesis of atmospheric mercury depletion event chemistry in the atmosphere and snow. Atmos. Chem. Phys., 8(6), 1445–1482 (doi: 10.5194/acp-8-1445-2008)CrossRefGoogle Scholar
Sutton, MA, Pitcairn, CER and Fowler, D (1993) The exchange of ammonia between the atmosphere and plant communities. Adv. Ecol. Res., 24, 301–393 (doi: 10.1016/S0065-2504(08)60045-8)CrossRefGoogle Scholar
Tennant, C, Menounos, B, Ainslie, B, Shea, J and Jackson, P (2012) Comparison of modeled and geodetically-derived glacier mass balance for Tiedemann and Klinaklini glaciers, southern Coast Mountains, British Columbia, Canada. Global Planet. Change, 82–83, 74–85 (doi: 10.1016/j.gloplacha.2011.11.004)CrossRefGoogle Scholar
Tranter, M (1996) Glacial runoff as a sink for atmospheric CO2 during the last glacial/interglacial transition. In Bottrell, SH ed. Proceedings of the 4th International Symposium on the Geochemistry of the Earth’s Surface, 22–28 July 1996, Ilkley, Yorkshire. University of Leeds, Leeds, 709–713 Google Scholar
Tranter, M and 8 others (2002) Direct effect of ice sheets on terrestrial bicarbonate, sulphate and base cation fluxes during the last glacial cycle: minimal impact on atmospheric CO2 concentrations. Chem. Geol., 190(1–4), 33–44 (doi: 10.1016/ S0009-2541(02)00109-2)CrossRefGoogle Scholar
Valentini, R and 29 others (2000) Respiration as the main determinant of carbon balance in European forests. Nature, 404(6780), 861–865 (doi: 10.1038/35009084)CrossRefGoogle ScholarPubMed
Wang, J, Xu, JL, Zhang, SQ, Liu, SY and Han, HD (2010) Chemical denudation rates and carbon dioxide sink in Koxkar glacierised region at the south slope of Mt. Tianshan, China. Environ. Sci. (China), 31(4), 903–910 [in Chinese]Google ScholarPubMed
Wenzel, A, Kalthoff, N and Horlacher, V (1997) On the profiles of wind velocity in the roughness sublayer above a coniferous forest. Bound.-Layer Meteorol., 84(2), 219–230 (doi: 10.1023/ A:1000444911103)CrossRefGoogle Scholar
Yde, JC, Knudsen, NT and Nielsen, OB (2005) Glacier hydrochemistry, solute provenance, and chemical denudation at a surgetype glacier in Kuannersuit Kuussuat, Disko Island, West Greenland. J. Hydrol., 300(1–4), 172–187 (doi: 10.1016/ j.jhydrol.2004.06.008)CrossRefGoogle Scholar
Zemp, M, Frauenfelder, R, Haeberli, W and Hoelzle, M (2005) Worldwide glacier mass balance measurements: general trends and first results of the extraordinary year 2003 in Central Europe. Mater. Glyatsiol. Issled./Data Glaciol. Stud. 99, 3–12 Google Scholar
Zhang, F, Jin, Z, Li, F, Yu, J and Xiao, J (2013) Controls on seasonal variations of silicate weathering and CO2 consumption in two river catchments on the NE Tibetan Plateau. J. Asian Earth Sci., 62, 547–560 (doi: 10.1016/j.jseaes.2012.11.004)CrossRefGoogle Scholar
Figure 0

Fig. 1. Map of the Koxkar glacier region (northwest China) sampling sites.

Figure 1

Fig. 2. Fluctuations of hourly CO2 concentration, atmospheric temperature and wind speed above the surface of Koxkar glacier. Data are from bare ice (site A, right of the vertical dotted line) and above supraglacial moraine (site B, left of the vertical dotted line).

Figure 2

Table 1. Hourly NGE (mmol m–2 s–1) at sites A and B on the surface of Koxkar glacier in 2012

Figure 3

Fig. 3. Study area variations of daily Fc and S at sites A and B (right and left sides of vertical dotted line, respectively).

Figure 4

Fig. 4. Relationships of NGE rates, IMI and precipitation at (a) site B and (b) site A.

Figure 5

Table 2. Relationship between IMI and NGE rates at site B in 2012