土壤蒸发和植被蒸腾遥感估算与验证

地表蒸散发是土壤—植被—大气系统中能量和水循环的重要环节,它包括土壤、水体和植被表面的蒸发,以及植被蒸腾。随着地表参数多源遥感产品的快速发展,利用不同地表参数遥感产品估算地表蒸散发以及其组分土壤蒸发和植被蒸腾成为日常监测越来越便利,监测尺度已从单站扩展到田块、区域乃至全球。目前地表蒸散发双层遥感估算模型按照建模机理的不同可分为:系列模型、平行模型、基于特征空间的模型、结合传统方法的模型以及数据同化方法。本文从模型构建物理机制、模型驱动数据以及模型输出结果验证等方面总结了上述模型的发展历史和现状,并指出在模型结构与参数化方案的优化、高分辨率模型驱动数据的发展、土壤蒸发和植被蒸腾像元尺度"地面真值"的获取等方面都仍需进一步完善。     

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

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.     

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

土壤热通量是地表能量平衡的重要分量,对其测算方法的研究对理解能量平衡过程具有十分重要的意义.利用2010年馆陶站土壤热通量等相关观测数据对多种测算土壤热通量的方法:实测土壤热通量和热储存量的结合方法(PlateCal)、热传导方程校正法(TDEC)、谐波分析法(HM)、平均土壤热电偶法(TCAV)、耦合热传导—对流法(ITCC)获取的地表土壤热通量进行了对比分析,并且采用最优方法计算馆陶站2008-2010年的地表土壤热通量,分析了该站土壤热通量日、季节变化特征.主要结论如下:①PlateCal和TDEC法分别为获取土壤热通量的最优观测与计算方法,而HM,TCAV和ITCC法计算结果均不理想;②PlateCal与TDEC法对地表土壤温度均不敏感,而HM法对地表土壤温度则比较敏感,各种地表土壤热通量的观测与计算方法均对土壤湿度敏感;③馆陶站冬小麦、玉米覆盖地表及地表裸露时期的地表土壤热通量均呈现典型的日、季节变化特征,与净辐射变化趋势一致;④考虑热储存后,可将馆陶站2010年各月地表能量闭合率提高4％～11％,对2008-2010年的年能量平衡闭合率提高3％～5％.     

Retrieval of Land-surface Temperature from AMSR2 Data Using a Deep Dynamic Learning Neural Network

It is more difficult to retrieve land surface temperature(LST) from passive microwave remote sensing data than from thermal remote sensing data, because the emissivities in the passive microwave band can change more easily than those in the thermal infrared band. Thus, it is very difficult to build a stable relationship. Passive microwave band emissivities are greatly influenced by the soil moisture, which varies with time. This makes it difficult to develop a general physical algorithm. This paper proposes a method to utilize multiple-satellite, sensors and resolution coupled with a deep dynamic learning neural network to retrieve the land surface temperature from images acquired by the Advanced Microwave Scanning Radiometer 2(AMSR2), a sensor that is similar to the Advanced Microwave Scanning Radiometer Earth Observing System(AMSR-E). The AMSR-E and MODIS sensors are located aboard the Aqua satellite. The MODIS LST product is used as the ground truth data to overcome the difficulties in obtaining large scale land surface temperature data. The mean and standard deviation of the retrieval error are approximately 1.4° and 1.9° when five frequencies(ten channels, 10.7, 18.7, 23.8, 36.5, 89 V/H GHz) are used. This method can effectively eliminate the influences of the soil moisture, roughness, atmosphere and various other factors. An analysis of the application of this method to the retrieval of land surface temperature from AMSR2 data indicates that the method is feasible. The accuracy is approximately 1.8° through a comparison between the retrieval results with ground measurement data from meteorological stations.     

遥感估算地表蒸散发真实性检验研究进展

地表蒸散发是连接土壤—植被—大气连续体的纽带,结合遥感技术估算地表蒸散发已成为获取区域乃至全球尺度时空连续地表蒸散发量的有效手段。由于遥感估算地表蒸散发容易受到地表空间异质性和近地层气象条件复杂性的影响,在模型机理与变量参数化方案、输入数据和时间尺度扩展等方面存在不确定性,影响了其准确度的提高和应用范围的拓展,因此需要开展真实性检验。本文综述了当前遥感估算地表蒸散发(包括植被蒸腾和土壤蒸发)真实性检验研究的相关成果,重点归纳并总结了应用于遥感估算地表蒸散发真实性检验的直接检验法和间接检法的主要原理、适用性和优缺点,在此基础上阐述了当前遥感估算地表蒸散发真实性检验研究所面临的挑战。分析表明：由于地表空间异质性的普遍存在,遥感估算地表蒸散发真实性检验研究在理论和方法方面还受到诸多挑战,今后应打破地表蒸散发遥感产品真实性检验局限在均匀地表的传统思路,发展非均匀地表遥感估算地表蒸散发真实性检验的理论框架,包括地表水热状况空间异质性的度量、非均匀地表验证场的优化布设、非均匀下垫面地表蒸散发的多尺度观测试验、卫星像元/区域尺度地表蒸散发相对真值的获取、验证过程中的不确定性分析以及遥感估算地表蒸散发的实证研究等,并构建一个多源、多尺度、多方法、多层次的真实性检验技术流程,以期把遥感估算地表蒸散发真实性检验作为突破口,提升相应遥感产品的应用水平,推动定量遥感科学的发展。     

海河流域不同下垫面土壤水分动态模拟研究

针对海河流域不同的下垫面类型,选取密云(果园林地)、大兴(城郊农田)、馆陶(平原农田)3个观测站,建立垂直方向上以含水率θ为因变量、含根系吸水项的非饱和土壤水分运动数值计算模型。该模型以一维Richards方程为基础(以下简称RE模型),采用实测的降水和蒸散数据作为模型的上边界条件,运用全隐式有限差分法,分别对不同生长期内的土壤水分进行数值模拟,得到时间序列的土壤水分廓线,并分别采用成熟软件HYDRUS-1D的模拟结果和各观测站实测土壤水分对RE模型进行交叉验证和直接验证。结果表明RE模型能够很好地模拟海河流域不同下垫面土壤水分动态变化过程,3个站模拟结果与实测土壤水分数据的均方根误差(RMSE)分别为0.03127,0.0359和0.0409 cm3/cm3。与HYDRUS-1D软件模拟结果(其与观测值的RMSE分别为0.03759,0.0647和0.0467 cm3/cm3)相比,RE模型模拟的土壤水分具有更高的精度,也显示出RE模型的可靠性。探讨3个站土壤水分的时空变异规律及其影响因子并以大兴站为例,通过优化RE模型参数,探讨犁底层对土壤水分模拟结果的影响,进一步改善RE模型的模拟精度。     

Regional and Global Land Data Assimilation Systems: Innovations,Challenges, and Prospects

Since the North American and Global Land Data Assimilation Systems(NLDAS and GLDAS) were established in2004, significant progress has been made in development of regional and global LDASs. National, regional, projectbased, and global LDASs are widely developed across the world. This paper summarizes and overviews the development, current status, applications, challenges, and future prospects of these LDASs. We first introduce various regional and global LDASs including their development history and innovations, and then discuss the evaluation, validation, and applications(from numerical model prediction to water resources management) of these LDASs. More importantly, we document in detail some specific challenges that the LDASs are facing: quality of the in-situ observations, satellite retrievals, reanalysis data, surface meteorological forcing data, and soil and vegetation databases; land surface model physical process treatment and parameter calibration; land data assimilation difficulties; and spatial scale incompatibility problems. Finally, some prospects such as the use of land information system software, the unified global LDAS system with nesting concept and hyper-resolution, and uncertainty estimates for model structure,parameters, and forcing are discussed.     

涡动相关涡动相关仪观测蒸散量的插补方法比较

涡动相关仪在长时间连续观测中,观测数据会有不同程度的缺失。应用6种不同的插补方法（平均昼夜变化法MDV,非线性回归方法NLR,动态线性回归方法DLR,查表法LUT,FAO PM方法,HANTS方法）对北京密云站2007年涡动相关仪观测蒸散量数据进行了插补。结果表明： LUT方法在不同数据缺失时均得到较好结果（均方差小于8 W/m²）;MDV和NLR方法更适合于短时间数据缺失的插补; DLR和FAO PM方法在观测数据出现连续波动时插补结果较差。由LUT、DLR、NLR、HANTS、FAO PM方法得到的年蒸散量分别为395.8 mm、409.9 mm、393.5 mm、390.7 mm、399.4 mm,差异在2.3~19.2 mm之间变化。对比分析了LUT方法得到的年蒸散量（潜热通量）与净辐射、降水量以及LAS观测潜热通量间的变化规律,表明插补结果合理。     

铜仁地区旅游气候资源特征及舒适度分析

利用1961～2010年的气候资料,对铜仁地区的气候特征进行分析,并计算全区各县市1～12月的特吉旺气候舒适度指数。结果表明:铜仁地区的年平均气温在13.5～17.6℃之间,年平均降水量为1110～1400mm,降水多集中在4～6月;日平均日照时数为2.9h～3.6h;年平均相对湿度在77%～83%之间,年平均风速在0.8～2.3m/s之间。铜仁地区全年中除7月、8月略显闷热外,其余月份均适宜开展户外旅游活动,尤其5月、6月、9月、10月是一年中旅游的最佳时节。     

涡动相关仪观测蒸散量的插补方法比较

涡动相关仪在长时间连续观测中,观测数据会有不同程度的缺失.应用6种不同的插补方法(平均昼夜变化法MDV,非线性回归方法NLR,动态线性回归方法DLR,查表法LUT,FAO-PM方法,HANTS方法)对北京密云站2007年涡动相关仪观测蒸散量数据进行了插补.结果表明:LUT方法在不同数据缺失时均得到较好结果(均方差小于8 W/m2);MDV和NLR方法更适合于短时间数据缺失的插补:DLR和FAO-PM方法在观测数据出现连续波动时插补结果较差.由LUT、DLR、NLR、HANTS、FAO-PM方法得到的年蒸散量分别为395.8 mm、409.9 mm、393.5 mm、390.7 mm、399.4 mm,差异在2.3～19.2 mm之间变化.对比分析了LUT方法得到的年蒸散量(潜热通量)与净辐射、降水量以及LAS观测潜热通量间的变化规律,表明插补结果合理.