农田下垫面观测通量的变化特征及其气候学足迹分析

doi:10.11867/j.issn.1001-8166.2013.12.1313

利用2008#cod#x02014;2010年馆陶站涡动相关仪和自动气象站观测资料,在保证数据质量的基础上,分析了通量交换特征,并采用算术平均和通量加权2种气候学足迹计算方法,详细探讨了不同时间尺度观测通量的源区分布特征。结果表明：①感热和潜热通量全年都有相同的日变化特征,CO2通量仅在作物生长季表现出与水热通量相反的日变化趋势。各通量受作物种类及其物候特征影响,季节变化明显。在生长季以潜热通量、CO2通量交换为主,其值在生长中期也明显高于生长始末期,且夏玉米的交换量强于冬小麦的。②受风、湍流条件、下垫面状况等共同影响,日尺度的观测通量源区差异最显著,季节尺度次之,年尺度最小。③不同时间尺度下,通量加权的气候学足迹能更合理地反映观测通量源区的平均状况,其源区大小普遍小于算术平均的结果。

关键词: 观测通量, 涡动相关仪, 农田, 气候学足迹

Based on quality controlled data from eddy covariance system and automatic weather station collected at Guantao farmland site from 2008 to 2010, the characteristics of diurnal, seasonal and annual variations of turbulent flux were reported. The corresponding source areas of flux measurement at different temporal scales were analyzed in detail, using arithmetic-averaged and flux-weighted footprint climatology calculation method, respectively. The main findings are as follows. Firstly, sensible heat and latent heat flux both show consistent diurnal variation throughout the year, while CO₂ fluxes only have significant diurnal variation in growing season with an opposite trend. The seasonal variation of the turbulent flux is mainly affected by the crop type and its growth status in different phenological periods. During growing season, latent heat flux and CO₂ flux are the dominant flux exchange items whose value are significantly higher in their middle growth stage than other ones during which latent heat and CO₂ flux exchange of the summer corn is stronger than winter wheat. Secondly, with combined effects of wind, turbulence and surface condition, the source area of flux measurement change most significantly at daily scale, less obvious at seasonal scale and smallest at annual scale. Finally, compared with arithmetic-averaged footprint climatology method, flux-weighted footprint climatology is a more reasonable method to calculate the source areas of the flux measurement, in that they account for the time change of the actual turbulent flux. The arithmetic-averaged results are most likely to overestimate the size of source area during small observed flux due to its weak turbulent exchange.

Key words: Turbulent flux observations, Eddy covariance system, Farmland, Footprint climatology.

图1 随稳定度的变化图中实线为公式(2)的计算结果,虚线为ITC取0.5时对应的变化范围

Fig.1 changes with different stability Solid lines are calculated using Eq.(2),dashed lines denote the variation range when ITC equals 0.5

图2 湍流强度与水平风速的关系

Fig.2 The relationship between turbulent intensity and horizontal wind speed

图3 CO ₂通量分段平均值(Fc ₁)及累计平均值(Fc ₂)与摩擦速度的关系图中摩擦速度的阈值取为0.16m/s

Fig.3 Relationship between sub-averaged CO ₂flux(Fc ₁),cumulative-averageCO ₂ flux(Fc ₂)and friction velocity the threshold for friction velocity is 0.16m/s

图4 馆陶站(GT)2010年作物生长季与非生长季的典型天(晴天、阴天) 净辐射(Rn)、感热(H)、潜热(LE)日变化

Fig.4 Diurnal variation of net radiation, sensible heat flux and latent heat flux on clear-sky and cloudy-sky conditions in 2010 at GT station

图5 馆陶站2010年作物生长季与非生长季的典型天(晴天、阴天)CO ₂通量的日变化

Fig.5 Diurnal variation of carbon dilxide flux on clear-sky and cloudy-sky conditions in 2010 at GT station

图6 馆陶站2008#cod#x02014;2010年感热(H)、潜热(LE)和CO ₂通量月平均日变化

Fig.6 Monthly-averaged diurnal variation of sensible heat, latent heat and carbon dioxide flux from 2008 to 2010 at GT station

图7 感热通量(H)与风向(Dir)的日变化

Fig.7 Daily variation of sensible heat flux(H) and wind direction(Dir)

图8 日尺度的观测通量源区等值线绿色、蓝色和红色分别代表50%、70%、90%通量贡献率范围,x,y分别为距观测点(图中黑色圆点,即0,0点)的东西、南北距离,下同

Fig.8 Source areas of flux measurement at daily scale contour : green, blue, red denotes 50%、70%、90% footprint contribution, x,y represents the east-west and north-north distance from the observation station, respectively

图9 2010年1月13日白天与夜间的观测通量源区

Fig.9 Source areas of flux measurement during day and night on January 13

图10 2009年算术平均的季节尺度观测通量源区

Fig.10 Arithmetic-averaged seasonal source areas of flux measurement in 2009

图11 2009年加权平均的季节尺度观测通量源区

Fig.11 Flux-weighted seasonal source areas of flux measurement in 2009

图12 年尺度的观测通量源区

Fig.12 Annual-averaged source areas of flux measurement

[1]	Ciais P, Reichstein M, Viovy N, et al.Europe-wide reduction in primary productivity caused by the heat and drought in 2003[J]. Nature, 2005, 437(7 058): 529-533
[2]	Dabberdt W F, Lenschow D H, Horst T W, et al.Atmosphere-surface exchange measurements[J]. Science, 1993, 260(5 113): 1 472-1 481.
[3]	Betts A K, Ball J H, Beljaars A C M, et al. The land surface-atmosphere interaction: A review based on observational and global modeling perspectives[J]. Journal of Geophysical Research: Atmospheres, 1996, 101(D3): 7 209-7 225.
[4]	Valentini R, Matteucci G, Dolman A J, et al. Respiration as the main determinant of carbon balance in European forests[J]. Nature, 2000, 404(6 780): 861-865.
[5]	Kaimal J C, Finnigan J J. Atmospheric Boundary Layer Flows: Their Structure and Measurement[M]. New York: Oxford University Press, 1994: 304.
[6]	Wang Jiemin, Wang Weizhen, Ao Yinhuan, et al. Turbulence flux measurements under complicated conditions[J]. Advances in Earth Science, 2007, 22(8): 791-797.
	[王介民, 王维真, 奥银焕, 等.复杂条件下湍流通量的观测与分析[J]. 地球科学进展, 2007, 22(8): 791-797.]
[7]	Chen Jiayi, Fan Shaohua, Zhao Chuanfeng, et al. The underestimation of the turbulent fluxes in eddy correlation techniques[J]. Chinese Journal of Atmospheric Science, 2006, 30(3): 423-432.
	[陈家宜, 范邵华, 赵传峰, 等.涡旋相关法测定湍流通量偏低的研究[J]. 大气科学, 2006, 30(3): 423-432.]
[8]	Foken T, Mauder M, Liebethal C, et al. Energy balance closure for the LITFASS-2003 experiment[J]. Theoretical and Applied Climatology, 2010, 101(1): 149-160.
[9]	Mahrt L.Computing turbulent fluxes near the surface: Needed improvements[J]. Agricultural and Forest Meteorology, 2010, 150(4): 501-509.
[10]	Schmid H P. Footprint modeling for vegetation atmosphere exchange studies:A review and perspective[J]. Agricultural and Forest Meteorology, 2002, 113(1/4): 159-183.
[11]	Cai Xuhui. Footprint analysis in micrometeorology and its extended applications[J]. Chinese Journal of Atmospheric Science, 2008, 32(1): 123-132.
	[蔡旭晖.湍流微气象观测的印痕分析方法及其应用拓展[J]. 大气科学, 2008, 32(1): 123-132.]
[12]	Neftel A, Spirig C, Ammann C. Application and test of a simple tool for operational footprint evaluations[J]. Environmental Pollution, 2008, 152(3): 644-652.
[13]	Flesch T K, Wilson J D, Yee E. Backward-time lagrangian stochastic dispersion models and their application to estimate gaseous emissions[J]. Journal of Applied Meteorology, 1995, 34(6): 1 320-1 332.
[14]	Sogachev A, Menzhulin G V, Heimann M, et al. A simple three-dimensional canopy-planetary boundary layer simulation model for scalar concentrations and fluxes[J]. Tellus B, 2002, 54(5): 784-819.
[15]	Horst T W, Weil J C. Footprint estimation for scalar flux measurements in the atmospheric surface layer[J]. Boundary-Layer Meteorology, 1992, 59(3): 279-296.
[16]	Hsieh C I, Katul G, Chi T W. An approximate analytical model for footprint estimation of scalar fluxes in thermally stratified atmospheric flows[J]. Advances in Water Resources, 2000, 23(7): 765-772.
[17]	Kormann R, Meixner F. An analytical footprint model for non-neutral stratification[J]. Boundary-Layer Meteorology, 2001, 99(2): 207-224.
[18]	Finnigan J. The footprint concept in complex terrain[J]. Agricultural and Forest Meteorology, 2004, 127(3/4): 117-129.
[19]	Jia Z Z, Liu S M, Xu Z W, et al. Validation of remotely sensed evapotranspiration over the Hai River Basin, China[J]. Journal of Geophysical Research: Atmospheres, 2012, 117: D13113, doi: 10.1029/2011JD017037.
[20]	Liu S M, Xu Z W, Wang W Z, et al. A comparison of eddy-covariance and large aperture scintillometer measurements with respect to the energy balance closure problem[J]. Hydrology and Earth System Sciences, 2011, 15: 1 291-1 306.
[21]	Xu Ziwei, Liu Shaomin, Xu Tongren, et al. The observation and calculation method of soil heat flux and its impact on the energy balance closure[J]. Advances in Earth Science, 2013, 28(8): 875-889.
	[徐自为, 刘绍民, 徐同仁, 等. 不同土壤热通量测算方法的比较及其对地表能量平衡闭合影响的研究[J]. 地球科学进展, 2013, 28(8): 875-889.]
[22]	Cai Xuhui, Zhu Mingjia, Liu Shaomin, et al. Flux footprint analysis and application for the large aperture scintillometer[J]. Advances in Earth Science, 2010, 25(11): 1 166-1 174.
	[蔡旭晖, 朱明佳, 刘绍民, 等.大孔径闪烁仪的通量印痕分析与应用[J]. 地球科学进展, 2010, 25(11): 1 166-1 174.]
[23]	Zhao Xiaosong, Guan Dexin, Wu Jiabing, et al. Distribution of footprint and flux source area of the mixed forest of broad-leaved and Korean pine in Changbai Mountain[J]. Journal of Beijing Forestry University, 2005, 27(3): 17-23.
	[赵晓松, 关德新, 吴家兵, 等.长白山阔叶红松林通量观测的footprint及源区分布[J]. 北京林业大学学报, 2005, 27(3): 17-23.]
[24]	Mi Na, Yu Guirui, Wen Xuefa, et al. Preliminary study of spatial representativeness for surface flux measurement in ChinaFlux[J]. Science in China (Series D), 2006, 36(Suppl.I): 22-33.
	[米娜, 于贵瑞, 温学发, 等.中国通量观测网络(ChinaFlux)通量观测空间代表性初步研究[J]. 中国科学:D辑, 2006, 36(增刊1): 22-33.]
[25]	Ma Di, L#cod#x000fc; Shihua, Chen Shiqiang, et al. Distribution of source area and footprint of Jinta Oasis in summer[J]. Plateau Meteorology, 2009, 28(1): 28-35.
	[马迪, 吕世华, 陈世强, 等.夏季金塔绿洲近地层通量足迹及源区分布特征分析[J]. 高原气象, 2009, 28(1): 28-35.]
[26]	Liu S M, Xu Z W, Zhu Z L, et al. Measurements of evapotranspiration from eddy-covariance systems and large aperture scintillometers in the Hai River Basin, China[J]. Journal of Hydrology, 2013, 487: 24-38.
[27]	Foken T, Gckede M, Mauder M, et al. Post-field data quality control[M]//Lee X H, Massman W J, Law B E, eds. Handbook of Micrometeorology:A Guide for Surface Flux Measurements. Boston: Kluwer Academic Publishers, 2004: 181-208.
[28]	Willis G E, Deardorff J W. On the use of Taylor#cod#x02019;s translation hypothesis for diffusion in the mixed layer[J]. Quarterly Journal of the Royal Meteorological Society, 1976, 102(434): 817-822.
[29]	Panofsky H, Tennekes H, Lenschow D, et al. The characteristics of turbulent velocity components in the surface layer under convective conditions[J]. Boundary-Layer Meteorology, 1977, 11(3): 355-361.
[30]	Zhu Zhilin, Sun Xiaomin, Wen Xuefa, et al. Study on the processing method of nighttime CO2 eddy covariance flux data in ChinaFLUX[J]. Science in China (Series D),2006, 36(Supp.#cod#x02161;): 36-46.
	[朱治林, 孙晓敏, 温学发, 等.中国通量网(ChinaFlux)夜间CO2涡动相关通量数据处理方法研究[J]. 中国科学:D辑, 2006, 36(增刊I): 34-44.]

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摘要

Analysis of the Characteristics of Turbulent Flux and Its Footprint Climatology at An Agricultural Site