涡动相关通量观测的不确定性 (王介民,HiWATTER2014年会)

1、涡动相关通量的不确定性王介民中科院寒旱所HiWATER 2014年会 2014年11月29-30日 兰州21. 引言2. 观测事实3. 不确定性估算方法4. 结果例5. 结论J Wang, 14112933观测误差真值系统误差随机误差观测n系统误差由传感器的精度、采样及取平均时间的设置、资料处理方法及环境因素的局限等引起。n随机误差则由大气湍流的内在特征 ( 采样误差 ) 、系统噪音、及非均匀下垫面上通量源区的变化等引起。J Wang, 14112944通量观测的不确定性问题n涡动相关方法是当前生态系统尺度上观测热量、水汽和CO2等通量的最准确最可靠方法。其系统误差可以随精细的观测设计等达到最

2、小 (如10%以内)。n通量的随机误差则可能达到10%以上 (对感热) 甚至25%-30% (对CO2等)。n了解通量误差或不确定性对资料的解释、分析及有关时空扩展研究有重要意义。 n通量资料的不确定性直接进入模式-数据融合(MDF) 过程，影响模式检验及其改进。nEC通量不确定性的评价比较复杂。 HiWATER实验为此提供了最佳契机。 J Wang, 14112955The flux matrix in the Zhangye oasisIncluding 17 EC sites and 4 LAS lines in a 5.5 km by 5.5 km area5Super station

3、Other EC sitesJ Wang, 14112966Flux data are noisy6Heat fluxes measured by EC at 2 levels, 4.5 m & 34 m, on the 40 m tower of HiWATER Superstation, Zhangye oasis, Jun 29-30, 2012. Net radiation is shown for comparison.Hi-WATER, Super stationn晴天静稳情况下，逐时的湍流通量有随机起伏。n同在近地层中的4.5米和30米的通量输送可能不受同一个湍流状态控制

4、J Wang, 1411297Uncertaintiesn Whether a specific flux measurements is significantly different from others?n How to compare a model result with these flux observations?Sensible heatLatent heatNEEn是否某一个站的通量观测比其它站更有意义？n如何用这样的观测结果来检验模式预测？J Wang, 14112988Eddy Covariance8Surface flux exchanges are control

5、led by atmospheric turbulenceJ Wang, 14112999 涡动相关通量不确定性的估算多EC戈壁对比观测9Assuming the 20 EC observing independently, the mean F being regarded as the true flux, then, the basic error analysis method can be used：J Wang, 141129101010Errors Errors and Uncertainties for the and Uncertainties for the Gobi Go

6、bi Intercomparison Intercomparison 02468101214012345678910 11 12 13 14 15 16 17 18 19 20 21 S & r of HEC No.sS1sR1sS2sR2s1r2s2r1J Wang, 1411291111l采样序列内部有相关性。定义 Integral Turbulence Time-Scale f , 对垂直风速 w 和标量 c: 1101=( ) fwcRdw c( )= ( ) ( + )wcRwc tCross-correlation 涡动相关通量不确定性的估算基于湍流原始数据的统计分析lMe

7、thod by Mann & Lenschow (1994) Method by Mann & Lenschow (1994) Relative flux uncertainty from pure random sampling errorlMethod by Finkelstein & Sims (2001)Method by Finkelstein & Sims (2001) Calculation of the variance of covariance=-=-1=+mmFpppppmpmw wc cw cc wn -=1-=11=-1=-n pptt

8、ptn ppttptw ww wwwnw cw wccn Auto- & cross-covariances：1/21/22221+=fwcFwcrFTrAveraging period T cov( , )=wcwcwcr CorrelationJ Wang, 141129121212(Hollinger & Richardson , 2005; Richardson et al, 2012)1,2,()( )2tttxx 涡动相关通量不确定性的估算基于通量计算结果的分析J Wang, 141129131313Errors and Uncertainties for the

9、Flux Matrix on Oasis Selections:14 corn field sites (2, 3, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15 and 16) ;10 continuous days (June 7 to 16), no rain or irrigation in the plots;Method: ML94, Paird towerResults:Random uncertainties, H, 18%LE, 16% Fc, 21%Site No.r (H)r (LE)r (Fc)210.56 (17.6%)31.85 (13

10、.7%)2.59 (18.1%)314.37 (18.9%)33.86 (15.4%)2.40 (21.7%)59.98 (16.0%)26.45 (14.3%)2.00 (20.4%)613.66 (16.1%)30.53 (15.9%)2.13 (27.7%)79.26 (21.2%)33.57 (14.3%)2.59 (18.7%)810.31 (17.6%)29.48 (14.9%)2.10 (21.3%)913.47 (16.6%)28.82 (15.4%)3.03 (20.7%)1012.62 (17.7%)30.9 (15.2%)3.12 (19.3%)1112.21 (15.2

11、%)26.94 (14.8%)2.48 (20.0%)1210.34 (20.3%)32.62 (16.1%)2.40 (22.2%)1310.33 (25.0%)43.13 (17.8%)3.11 (29.9%)1414.62 (17.8%)35.96 (16.6%)2.58 (25.8%)1510.60 (21.1%)33.78 (16.2%)2.49 (21.8%)1611.43 (16.3%)22.17 (16.7%)2.18 (22.8%)J Wang, 141129141414Flux uncertainty scales with the magnitude of fluxpdf

12、 of the residuals from mean uA key knowledge in the evaluation of model uncertaintyuA Laplace distribution is more suitable than GaussianJ Wang, 1411291515Concluding RemarksnUncertainties of the EC fluxes should be evaluated for data interpretation and analysis, for scaling up spatially or temporall

13、y, and, for model validation.nThe uncertainties of EC fluxes are usually the result of the stochastic nature of turbulence. Surface heterogeneity (e.g., on oasis) may induce more active turbulence, particularly, of larger scales, consequently, larger flux uncertainties.nFlux uncertainty estimation, incl. the separation of random and systematic ef