Spatio-temporal patterns of energy exchange and evapotranspiration during an intense drought for drylands in Brazil

The Caatinga biome, located in the northeastern region of Brazil, is the most populated dryland region on the planet and extremely vulnerable to land degradation due to climatological and anthropogenic factors. Energy partitioning substantially influences the local climate and affects the water cycle, which is of utmost importance for the economy and livelihood of the region. Recently, eddy covariance (EC) towers were installed in the area; thus, the scientific community can thoroughly assess the water and energy fluxes over this unique biome. While EC towers have a high degree of accuracy, they only measure energy fluxes over a small land footprint. Given the biome spatial heterogeneity, the use of EC-based techniques has the limitation of not comprehensively representing water and energy fluxes profiles over the entire region. Incorporating remote sensing (RS) data into the landscape analysis is a feasible solution to overcome this issue, given that satellite data can capture the phenomena represented by the EC measurements across large spatial scales. Our research studied the capability of the Surface Energy Balance Algorithm for Land (SEBAL) and MOD16-ET products to represent the EC measurements regarding energy and mass exchange, with an ultimate objective of applying the best approach to assess these fluxes regionally. We applied the SEBAL model using only remote sensing data from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor. The MOD16-ET model uses a different approach but is also based on MODIS data. Our analysis was based on three years (2014–2016) of data, which was limited to the availability of the EC tower data. We found that for the EC-based measurements, energy balance closure (EBC) achieved an average of 0.84, which is considerably high for the region. This is possibly due to the EC tower being installed on a preserved Caatinga plot, with reduced heterogeneity and higher plant density. When analyzing RS-based products to represent ET profiles in the region, we found that the SEBAL model accurately represented water fluxes during the wet season but not the dry season, whereas the MOD16-ET showed a better agreement with EC-based water fluxes throughout all the seasons. SEBAL inaccuracy in drylands is partially due to the narrow range between the cold and hot pixels in an image, as the algorithm relies on this range for input parameters, especially in the dry season. Therefore, we concluded that MOD16-ET is capable of better-representing water fluxes in the Caatinga region. We analyzed the fluxes regionally and quantified annual ET for the three years. These results are especially relevant for local policymakers on dealing with water and landscape issues in a region where the livelihood and well-being of the population is inextricably bound to water availability.     

具有均匀协方差结构的误差方差非负二次估计的可容许性

在二次损失函数下,研究了线性模型中具有均匀协方差结构的误差方差非负二次估计的可容许性,给出了设计矩阵为1向量时,估计可容许的充要条件。     

AVO反演的不确定性分析

叠前地震数据反演可以得到比常规叠后波阻抗反演更丰富、更有效的岩性信息,但叠前数据体的噪声及其它因素严重影响了AVO反演的稳定性,如何评估AVO反演结果的可靠性显得尤为重要.本文从贝叶斯理论出发,假定均匀先验分布、高斯噪音分布,推出不确定性分析方程,利用协方差矩阵中的方差描述反演问题的不确定性,模型研究显示反演不确定性与叠前信噪比、纵横波速度比、覆盖次数及反演采用的角度范围相关,方法预测的反演误差可定量解释反演结果的可靠性,为解释人员提供有效的质量监控手段.     

测定地球引力常数GM的协方差分析

编制了在ＧｉｖｅｎｓＧｅｎｔｌｅｍｅｎ正交变换算法下的多级复弧协方差分析软件．运用到引力常数ＧＭ解算的情形中,并计算了未参加估计的台站坐标的误差对产生解算结果的影响．这种影响的直接后果是降低了解算的精度．对产生解算内符精度和真实外符精度之间差别的原因进行了初步的探讨     

Application of an error statistics estimation method to the PSAS forecast error covariance model

In atmospheric data assimilation systems, the forecast error covariance model is an important component. However, the paralneters required by a forecast error covariance model are difficult to obtain due to the absence of the truth. This study applies an error statistics estimation method to the Pfiysical-space Statistical Analysis System （PSAS） height-wind forecast error covariance model. This method consists of two components： the first component computes the error statistics by using the National Meteorological Center （NMC） method, which is a lagged-forecast difference approach, within the framework of the PSAS height-wind forecast error covariance model; the second obtains a calibration formula to rescale the error standard deviations provided by the NMC method. The calibration is against the error statistics estimated by using a maximum-likelihood estimation （MLE） with rawindsonde height observed-minus-forecast residuals. A complete set of formulas for estimating the error statistics and for the calibration is applied to a one-month-long dataset generated by a general circulation model of the Global Model and Assimilation Office （GMAO）, NASA. There is a clear constant relationship between the error statistics estimates of the NMC-method and MLE. The final product provides a full set of 6-hour error statistics required by the PSAS height-wind forecast error covariance model over the globe. The features of these error statistics are examined and discussed.     

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沙漠腹地人工绿地地表能量交换特征

运用涡度相关法开路系统对塔克拉玛干沙漠腹地人工灌溉绿地生长季地表能量交换特征以及与环境因子的关系进行测定分析。结果表明：在典型晴天条件下,无论是沙漠区还是沙漠腹地灌溉绿地,白天感热通量在净辐射通量的分配中所占的份额最大,潜热交换仅占很小的比例,人工绿地感热通量和潜热通量的峰值为230.54 W/m²和88.5 W/m²,沙漠区为220 W/m²和17.55 W/m²,沙漠腹地人工灌溉造林后潜热交换明显增加。沙漠腹地造林后,绿地波文比日变幅和日均波文比均减小,绿地日均波文比为沙漠区的15%,人工绿地的营建促使了局地气候的改变。绿地地表能量交换受气象因子和下垫面条件的影响和制约,按相关系数的高低,环境因子对感热、潜热通量的影响依次为：Rn>△Ta>△TS>v>TS,沙漠区人工造林后地表能量交换与多个环境因子有着密切的关系。这些研究结果将加深我们对沙漠地区人工灌溉造林地近地层能量交换的认识。     

新疆北部覆膜滴灌棉田的碳交换日、生长季变化特征

利用涡动相关系统测定新疆石河子棉区覆膜滴灌棉田的CO₂通量,分析2010年棉花各生育期净生态系统碳交换（NEE）的日变化特征,并将[NEE]拆分为生态系统总生产力（GEP）和生态系统呼吸（R_eco）,分析三者的生长季变化特征及其影响因素。结果表明：在播种期和苗期,棉田白天和夜间的NEE变化幅度都较小;其他生育期NEE白天呈‘V’形变化,夜间为正值且变化小。NEE的日变化主要受太阳总辐射影响。GEP、R_eco和NEE的生长季变化趋势与叶面积指数变化相对一致,最大日累积量均出现在花铃期,分别为11.8,8.0和-6.2 g C·m^-2·d^-1。播种期、苗期、蕾期、花铃期和吐絮期的日平均[NEE]分别为2.6,1.6,-1.2,-2.8和0.5 g C·m^-2·d^-1。整个生长季棉田NEE累积量为-122.2 g C·m^-2,表现为碳汇。由偏相关分析可得,GEP,R_eco和NEE的生长季变化与气温的相关系数最高,其次为饱和水汽压差,再次为太阳总辐射和土壤温度,结果表明气温是影响棉田GEP,R_eco和NEE生长季变化的主要气象因素。气温对棉田GEP,R_eco和净碳吸收起促进作用,而饱和水汽压差对其起限制作用。     

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Sensitivity of model parameterizations for simulated latent heat flux at the snow surface for complex mountain sites

The snowcover energy balance is typically dominated by net radiation and sensible and latent heat fluxes. Validation of the two latter components is rare and often difficult to undertake at complex mountain sites. Latent heat flux, the focus of this paper, is the primary coupling mechanism between the snow surface and the atmosphere. It accounts for the critical exchange of mass (sublimation or condensation), along with the associated snowcover energy loss or gain. Measured and modelled latent heat fluxes at a wind‐exposed and wind‐sheltered site were compared to evaluate variability in model parameters. A well‐tested and well‐validated snowcover energy balance model, Snobal, was selected for this comparison because of previously successful applications of the model at these sites and because of the adjustability of the parameters specific to latent heat transfer within the model. Simulated latent heat flux and snow water equivalent (SWE) were not sensitive to different formulations of the stability profile functions associated with heat transfer calculations. The model parameters of snow surface roughness length and active snow layer thickness were used to improve latent heat flux simulations while retaining accuracy in the simulation of the SWE at an exposed and sheltered study site. Optimal parameters for simulated latent heat flux and SWE were found at the exposed site with a shorter roughness length and thicker active layer, and at the sheltered site with a longer roughness length and thinner active layer. These findings were linked to physical characteristics of the study sites and will allow for adoption into other snow models that use similar parameters. Physical characteristics of wind exposure and cover could also be used to distribute critical parameters in a spatially distributed modelling domain and aid in parameter selection for application to other watersheds where detailed information is not available. Copyright © 2012 John Wiley & Sons, Ltd.