The bulk transfer coefficients in the permafrost region at the Tanggula Pass of Tibetan Plateau

LiangLei Gu , JiMin Yao , Lin Zhao , ZeYong Hu , YongPing Qiao

1. Naqu Observatory for High and Cold Climate and Environment, Cold and Arid Regions Environmental and Engineering Research Institute (CAREERI), Chinese Academy of Sciences (CAS), Lanzhou, Gansu 730000, China

2. Cryosphere Research Station on Qinghai-Xizang Plateau, State Key Laboratory of Cryospheric Science, CAREERI, CAS,Lanzhou, Gansu 730000, China

3. Key Laboratory of Land Surface Process and Climate Change in Cold and Arid Regions, CAREERI, CAS, Lanzhou, Gansu 730000, China

The bulk transfer coefficients in the permafrost region at the Tanggula Pass of Tibetan Plateau

LiangLei Gu1,3, JiMin Yao2*, Lin Zhao2, ZeYong Hu1,3, YongPing Qiao2

1.Naqu Observatory for High and Cold Climate and Environment, Cold and Arid Regions Environmental and Engineering Research Institute (CAREERI), Chinese Academy of Sciences (CAS), Lanzhou, Gansu 730000, China

2.Cryosphere Research Station on Qinghai-Xizang Plateau, State Key Laboratory of Cryospheric Science, CAREERI, CAS,Lanzhou, Gansu 730000, China

3.Key Laboratory of Land Surface Process and Climate Change in Cold and Arid Regions, CAREERI, CAS, Lanzhou, Gansu 730000, China

This paper presents research on the surface drag coefficients,CD, and the bulk transfer coefficients of sensible heat flux,CH, in the permafrost region at the Tanggula Pass of the Tibetan Plateau. The data were obtained from the Open-Path Eddy Covariance System and the 10-m Automatic Weather Station (AWS) at the TGLMS site which supported by Cryosphere Research Station (Chinese Academy of Science) on the Qinghai-Xizang Plateau (Tibetan Plateau). The characteristics ofCDandCHin relation to atmospheric instability and wind velocity are discussed, and it was found that the bulk transfer coefficients varied with air conditions and were different in different months. However, the bulk transfer coefficients obtained from the eddy covariance system did not show a significant increasing trend with increasing atmospheric instability, and the bulk transfer coefficients did not change greatly with increasing wind velocity at 10 m.

eddy covariance; permafrost; atmospheric stability; wind velocity

1. Introduction

It is important to estimate the heat fluxes from land surface to the atmosphere to understand the mechanism of the energy cycle (Tanakaetal., 2001). The surface energy budget varies with the bulk aerodynamic characteristics of the land (Kondo and Yamazawa, 1986). Usually, the fluxes can be calculated by the bulk transfer method. Therefore, the turbulent momentum drag coefficients (CD), as well as heat and vapor transfer coefficients (CHandCE), are key parameters to estimate these turbulent fluxes (Miao and Ji, 1996).Also, the bulk transfer coefficients are quite important in weather diagnosis and analysis (Lietal., 2002; Zhangetal.,2002). Many studies on the bulk transfer coefficients in the area of sea-atmosphere interactions have been conducted and have drawn some important conclusions (Hicks, 1975;Kondo and Yamazawa, 1986; Tsukamotoetal., 1991).However, sufficient research on bulk transfer coefficients in land-atmosphere interactions is still lacking (Bianetal.,2002) due to complex land surface features and thermal properties (Zuoetal., 1992; Lietal., 2000; Zhangetal., 2004).

The Tibetan Plateau has a mean elevation over 4,000 m;it plays a significant role in the Asian monsoon system (Yeh and Gao, 1979). Observations of land-atmosphere exchanges can help improving the boundary-layer parameterization schemes in numerical models (Bianetal., 2002). It is critical to study the transfer processes of mass and energy between the Tibetan Plateau and the atmosphere (Bianetal.,2002). Many researches of the bulk transfer coefficients over the Tibetan Plateau have been done, but most of them were not conducted by the direct measurements of turbulent fluxes. However, with the improvements in technology, the eddy covariance system has been used in recent research work. For example, Maetal. (2000) calculated the coefficients of the Naqu Region by analyzing the eddy covariance data in an intensive observation period and found that the coefficients had different values under different air stability conditions; moreover, the coefficients were different in different months. Lietal. (1999) reported that the drag coefficient (CD) was 2.32×10-3and the heat transfer coefficient(CH) was 3.01×10-3in the Gaize Region. The eddy covariance technique is an advanced and accurate measurement technology at present.

The land-surface process in permafrost regions is one of the focal problems for the climate modeling. The World Climate Research Program (WCRP) Climate and Cryosphere Project (CliC) has proposed that the land-surface process in permafrost regions should be studied further (Yaoetal., 2010). However, long serial and continuous eddy covariance data in typical permafrost region on Tibetan Plateau are few, as the researches ofCDandCHbased on such data are fewer.

In this paper, the study area is in a typical continuous permafrost region at the Tanggula Pass of the Tibetan Plateau. The long serial fluxes data were obtained by the Open-Path Eddy Covariance System for the calculation of the bulk transfer coefficients. The aim of the work was to obtain more accurate parameters and to contribute to the research of the land-surface process in the permafrost region over the Tibetan Plateau.

In addition, it should be noted that when the wind velocity is less than 10 m/s, the heat transfer coefficientCHis equal to the vapor transfer coefficientCE(Miao and Qian, 1996); because it is very difficult to obtain the specific humidity of the ground surface, theCEis not discussed in this paper.

2. Data and methods

2.1. Site and instruments description

The monitoring site belongs to the Cryosphere Research Station (Chinese Academy of Science) on the Qinghai-Xizang Plateau (Tibetan Plateau). The site, coded TGLMS, was set up in June of 2004. It is located at 91°56′E,33°04′N, 5,100 m elevation, and lies on a gentle slope near the Qinghai-Xizang Highway in the Tanggula Region. The underlying surface is low-temperature permafrost and the annual mean air temperature at 2-m height is -4.9 °C. The typical vegetation is alpine grassland distributed in clusters with heights less than 10 cm, and the coverage is about 40%to 50%.

The observation systems include the Open-Path Eddy Covariance System and a 10-m Automatic Weather Station(AWS). The Open-Path Eddy Covariance System consists of a three-dimensional anemometer, sonic virtual temperature,CO2and H2O probes, and also includes a data logger for data acquisition and storage. The eddy covariance system is 3-m high, with a sampling frequency of 10 HZ. The measurements of the 10-m AWS include air temperature, wind velocity, and radiations. The data were recorded once every 30 minutes. The specifications of the main observation instruments are presented in Table 1.

Table 1 Specification of several observation instruments

2.2. Data processing

The formula of the drag coefficient is:

The bulk transfer coefficient of sensible heat flux is:

The formula of the ground surface temperature is (Shengetal., 2003; Jiangetal., 2006):

where σ is the Stefan-Blotzmann constant, σ = 5.6697×10-8(W/(m2·K4)); ε is the specific radiation ratio, 0.95;Ruis the upward long-wave radiation from the ground surface;Rdis the downward long-wave radiation (Jiangetal., 2006).

The atmospheric stabilityZ/Lwas obtained from the Open-Path Eddy Covariance System, whereLis the Monin-Obukhov length andZis the observation height.

3. Results analysis

3.1. Unstable air conditions (Z/L＜0)

Considering November of 2005 as an example (the method was the same in other months), the solutions ofCDandCHunder unstable air conditions are shown in Figure 1,whereRis the correlation coefficient andNis the statistical sample number.

Figure 1 The solutions of CD (a) and CH (b) under unstable air conditions (Z/L＜0) in November of 2005

Figure 2a shows that the monthly variations ofCDunder unstable air conditions were small, but theRchanged greatly.TheRis related to the quality of the observation data. Because theCDandCHresults were derived statistically, they are credible only when the correspondingRis high. TheCHwas lower in winter than in other seasons, and all theRvalues ofCHwere more than 0.5 (Figure 2b); this meant that the air turbulence in winter was weak. The monthlyCDandCHvalues under unstable air conditions were variable.

3.2. Stable air conditions (Z/L＞0)

Considering November of 2005 as an example again(the method was the same in other months), Figure 3 presents the solutions ofCDandCHunder stable air conditions,whereRandNhave the same meanings as above.

Figure 2 The monthly variations of CD (a), CH (b) and R under unstable air conditions from November of 2005 to December of 2006

In the data processing under stable air conditions, the wind velocity data at 10-m height less than 5 m/s were rejected for two reasons: (1) the data of the wind velocity at 10-m height more than 5 m/s was less influenced by the instrument sensitivity, and the wind velocity values were more accurate; (2) when the atmosphere was in almost neutral status, it was favorable for concentrating the scattered points and obtaining more accurate bulk transfer coefficientsCDandCH.

信息技術(shù)是一門(mén)特殊的、新興的學(xué)科，它的教學(xué)思想，教學(xué)方法以及教學(xué)模式也應(yīng)隨著技術(shù)的發(fā)展進(jìn)行變革和創(chuàng)新。然而傳統(tǒng)的聾校教學(xué)方法和教學(xué)模式顯然跟不上這樣的發(fā)展速度，致使信息技術(shù)課堂教學(xué)沉悶、缺乏生機(jī)與樂(lè)趣，課堂教學(xué)效率不高、與聾啞學(xué)生的實(shí)際情況有一定差距。

Figure 4 shows the monthlyCDandCHvalues under stable air conditions. Compared to the unstable air conditions, theCDandCHvalues under stable air conditions were lower; this means the atmosphere transfer capacity of fluxes is stronger under unstable air conditions, and such phenomena accord with reality. Maetal. (2000) drew the same conclusions from observations at the Amdo and north PAM stations.

Figure 3 The solutions of CD (a) and CH (b) under stable air conditions (Z/L＞0) in November of 2005

Figure 4 The monthly variations of CD (a), CH (b) and R under stable air conditions from November of 2005 to December of 2006

3.3. Brief summary

ForR＞0.5, the values ofCDandCHare listed in Tables 2 and 3. These Tables show that the seasonal variation ofCDis not regular, but the seasonal variation ofCHis clear. Under both stable and unstable air conditions, theCHvalues are higher in summer and autumn than in winter and spring,which means the transfer capacity of sensible heat fluxes in summer and autumn is stronger. This coincides with the results observed in the Amdo and north PAM stations (Maet al., 2000).

The bulk transfer coefficients (CD,CH) obtained by the Eddy Covariance Method over different underlying surfaces on Tibetan Plateau are listed in Table 4. TheCDandCHvalues at the Changdu station are the largest because the station lies in the river valley grassland, where has greater surface dynamic roughness. TheCDandCHvalues in the three alpine grassland stations are similar and larger than those at the Dangxiong and the Gaize station, which lie in an open dry river valley and in gobi sand respectively, where have smaller surface dynamic roughnesses.

4. Discussions

4.1. CD and CH in relation to the atmospheric instability

From Figure 5, theCDandCHvalues obtained from the Eddy Covariance Method do not show a significant increasing trend with increasing atmospheric instability. This agrees with Tsukamotoetal. (1991), who calculated theCDusing the eddy covariance data and obtained similar conclusions that the coefficients did not increase with increasing atmosphere instability. Other studies using eddy covariance data drew the same conclusion, for example, in a study of Hefner Lake in Oklahoma (USA), Emmanuel (1975) did not find any correlation of bulk transfer coefficients with atmosphere stability.Similar results were also found in a study by Smith and Banke at Sable Island near Nova Scotia (1975); they did not find any significant correlation between the drag coefficient and atmosphere stability by eddy covariance data.

Table 2 Monthly values of surface drag coefficients CD (×10-3) from November of 2005 to December of 2006 (R＞0.5)

Table 3 Monthly values of bulk transfer coefficients of sensible heat fluxes CH (×10-3) from November of 2005 to December of 2006 (R＞0.5)

Table 4 The bulk transfer coefficients (CD, CH) obtained by the Eddy Covariance Method over different underlying surfaces on Tibetan Plateau

However, these results are different from the traditional results derived from profile data (Joffre, 1982; Zuoetal.,1992).In traditional studies of coefficients using profile data,the relationships between the coefficients and the thermal stability were very strong and accorded with the Monin-Obukhov similarity theory (Joffre, 1982). Analysis of profile measurements in desert and Gobi regions by Zuoet al. (1992) also showed that bulk transfer coefficients tend to increase with increasing atmospheric instability.

Based on such phenomena, Tsukamotoetal. (1991) indicated that such results may be related to the different data sources. The theoretical prediction of Deardorff was supported by the experimental data in the stability ranges of-0.02＜RiB＜0.02 (Deardorff, 1968), and it was based on estimations from profile data rather than direct measurements of turbulent fluxes. In our study, the bulk transfer coefficients obtained from the eddy correlation did not show a significant dependence on increasing atmospheric instability.However, such an explanation is not sufficient; this needs much more research in the future.

Figure 5 Relationships between the bulk transfer coefficients and atmospheric stability Z/L under unstable air conditions as U＞5 m/s(a) indicates drag coefficients CD; (b) indicates the bulk transfer coefficients of the sensible heat flux CH.

4.2. CD and CH in relation to the wind velocity

Figure 6 shows the variations of the bulk transfer coefficients in relation to the wind velocity at 10-m height. The bulk transfer coefficients did not change much with wind velocity and they exhibited an approximately flat-straight relation. This result is similar to those of Zuoetal. (1992) in desert and Gobi regions. This is different from the sea surface, where the bulk transfer coefficients increase with increasing wind velocity as the wind would cause variation of sea waves and then lead to an increase of the surface roughness with increasing wind velocity. On bare land, the surface roughness does not change with wind velocity and it can be viewed as a constant (Zuoetal., 1992). Therefore, on bare land the bulk transfer coefficients do not change significantly with wind velocity.

Figure 6 The variations of the bulk transfer coefficients with wind velocity at 10-m height under unstable air conditions as U＞5 m/s.(a) indicates drag coefficients CD; (b) indicates the bulk transfer coefficients of the sensible heat flux CH.

5. Conclusions

In this paper, eddy covariance data and meteorological data from November of 2005 to December of 2006 were used to calculate the bulk transfer coefficients (CD,CH) in the permafrost region at the Tanggula Pass of the Tibetan Plateau. The conclusions are:

(1) The bulk transfer coefficientsCDandCHvaried seasonally, and they were higher under unstable air conditions than under stable air conditions. The obtainedCDandCHvalues (Tables 2 and 3) varied from 1.74×10-3to 3.39×10-3and from 1.28×10-3to 3.09×10-3respectively. They can be used to estimate the energy fluxes of the permafrost region by using the bulk transport method. The variation ofCDwas not regular, butCHwas higher in summer and autumn than in winter and spring.

(2) TheCDandCHvalues obtained from the Open-Path Eddy Observation System with direct turbulent measurement did not show a significant increasing trend with increasing atmospheric instability, which was different from the traditional results from profile data. The reason may be related to the characteristics of the data itself, and this needs much more research in the future.

(3) TheCDandCHvalues did not change much with increasing wind velocity at 10-m height, and they exhibited near a flat-straight relation.

This work was supported by the Major State Basic Research Development Program (973 Project: No.2007CB411505,No.2010CB951701-2), the State Key Program of National Natural Science of China (No.40830533), the Basic Research Program of Ministry of Science and Technology of China (No.2008FY110200), the CAS Knowledge Innovation Project (No.KZCX2-YW-Q11-01).

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10.3724/SP.J.1226.2011.00366

*Correspondence to: Dr. JiMin Yao, Cold and Arid Regions Environmental and Engineering Research Institute, Chinese Academy of Sciences. No. 320, West Donggang Road, Lanzhou, Gansu 730000, China. Email: yjm@lzb.ac.cn

10 February 2011 Accepted: 15 May 2011