应用EOS/MODIS卫星资料反演与估算西北雨养农业区地表能量和蒸散量

应用定西地区的陆面过程野外观测资料和四次EOS_MODIS卫星资料,对典型的西北半干旱雨养农业区的基本地表特征参数进行反演,在此基础上对各能量通量和蒸散量进行估算,进而分别分析其季节和空间变化.结果表明：应用卫星数据估算的各参量的相对误差基本都在20%以内,其空间和时间变化基本反映了当地的实际情况;区域各通量和日蒸散量分布极不均匀,表现为四季相差比较大的单峰型变化特征,冬季最小、其次是秋季、夏春两季最大;与面积较大的中、低植被覆盖度区域相比,小范围的高植被覆盖度区域的地表净辐射、潜热和日蒸散量相对较高,土壤热通量和显热通量相对较低,并且都在春、夏季节表现得更加显著.低、中植被覆盖度区的各能量通量的季节变化不显著的特征反映了半干旱西北雨养农业区土壤的干土层相对比较厚的特征.     

中国区域陆表热力作用时空分布及异常变化区域的成因

基于互补相关理论,通过20cm蒸发皿气象观测数据分析了中国区域1980～2000年地表热力时空变化和分布．结果显示：四川盆地为中心的长江中上游流域和黑龙江北部地区热力作用显著异常增强;新疆和云南部分区域热力作用显著减少．上述区域内低云覆盖率也同步发生显著的异常变化．通过西太平洋副热带高压波动数据和热带风暴频率资料证实,天气系统是造成地表热力异常分布的主要原因,并合理地解释了中国大部分区域年降水周期性和准周期性波动的成因．同时利用NOAA—AVHRR卫星遥感数据,分析了下垫面性质变化对地表热力异常分布的影响．在地表植被增加区域,地表热力作用下降;在地表植被减少强度最大的城市化周边地区,热力作用显著增强,而更大范围的热力增强却与天气系统引发的低云异常减少有关．     

基于卫星遥感资料的中国区域土壤湿度EnKF数据同化

土壤湿度在陆气相互作用过程中扮演着重要的角色,是气候、水文、农业、林业等研究中重要的地球物理参数之一.土壤湿度影响地面蒸散,径流、地表反射率、地表发射率以及地表感热和潜热通量,从而对气候有重要影响,它对大气的影响在全球尺度上仅次于海面温度,在陆地尺度其影响甚至超过海面温度.本文介绍了基于EnKF及陆面过程模型的中国区域陆面土壤湿度同化系统（CLSMDAS,China Land Soil Moisture Data Assimilation System）,以及该系统应用于中国区域陆面土壤湿度同化试验的结果.CLSMDAS包括以下几个部分：1）陆面模式采用美国国家大气研究中心NCAR的陆面过程模型Community Land Model Version3.0（简写为CLM3.0）;2）大气驱动场数据中的降水和地面入射太阳辐射数据来自FY2静止气象卫星每小时产品;3）陆面数据同化方法采用EnKF（Ensemble Kalman Filter）同化方法;4）观测数据包括AMSR-E卫星反演土壤湿度产品以及地面土壤湿度观测资料.利用CLSMDAS对2006年6~9月的土壤湿度同化试验结果的分析表明：陆面模式模拟和同化结果都能比较合理地反映出土壤湿度时空分布,同化的土壤湿度分布与2006年8月重庆、四川发生建国以来最严重的夏伏旱有非常好的对应关系,与发生在9月的湖北东部、广西南部等地的干旱区也有非常好的对应关系.     

西北地区戈壁局地陆面物理参数的研究

采用2000年8月～2001年9月在敦煌戈壁上观测的陆面过程资料，分析了敦煌地区荒漠戈壁地表反照率与太阳高度角和土壤湿度的关系以及土壤热传导率与土壤湿度的关系，初步给出了具有试验基础的戈壁局地反照率和土壤热传导率的多因子参数化公式. 并通过与观测值的比较发现试验资料拟合的参数化公式能够比较好地反映降水等气候因子引起的动态变化.     

我国黄土高原地区陆面能量的空间分布规律及其与气候环境的关系

我国黄土高原地区地处夏季风边缘,分布在气候和生态过渡带,气候环境的空间差异很大,对陆面能量的空间分布格局影响非常显著.然而,由于受该地区陆面过程观测站点较少的局限,对整个黄土高原区域陆面能量的空间分布规律及其影响机制的认识十分有限.在对CLM模式模拟的陆面能量平衡分量资料进行试验验证的基础上,利用CLM模式模拟的近30年黄土高原地区陆面能量平衡分量资料,分析了该地区近30年平均陆面能量平衡分量的空间变化特征以及与最干燥年和最湿润年的差异,研究了陆面能量平衡分量空间分布与经、纬度和海拔高度等地理因素及降水和气温等气候因子之间的关系.发现,黄土高原地区陆面能量平衡分量空间差异非常显著,地表净辐射和感热通量由南至北增加,潜热通量和土壤热通量从东南向西北减少;空间最干格点和最湿格点之间的地表感热、潜热和土壤热通量几乎相差1倍左右,地表能量分配由最干格点的感热通量主导转变为最湿格点的感热和潜热平分秋色;年际干湿波动对地表能量平衡分量的影响也相当显著,对感热和潜热通量的改变幅度最大接近30%.而且,经纬度和海拔高度等地理因素及温度和降水等气候要素均与陆面能量平衡分量空间分布有一定的相关性,但地表净辐射与海拔高度和纬度的关系更密切,感热通量与降水和纬度的关系更密切,而潜热和土壤热通量只与降水的关系比较密切.     

沙漠陆面过程参数化与模拟

沙漠地区植被稀疏、干旱少雨,其陆面物理过程具有与全球其它地区显著不同的特点.本文利用巴丹吉林沙漠观测资料,分析和计算了地表反照率、比辐射率、粗糙度和土壤热容量、热传导系数等关键陆面过程参数,建立了适合于沙漠地区的陆面过程模式DLSM (Desert Land Surface Model),并与NOAH陆面过程模式的模拟结果和观测资料进行了比较.结果表明:巴丹吉林沙漠地表反照率为0.273,比辐射率为0.950,地表粗糙度为1.55×10^-3 m,土壤热容量和热扩散系数分别为1.08×10⁶ J·m^-3·K^-1和3.34×10^-7 m²·s.辐射传输、感热输送和土壤热传导过程是影响沙漠地区地表能量平衡的主要物理过程.通过对这三种过程的准确模拟检验,DLSM能够较准确地模拟巴丹吉林沙漠地气能量交换特征;短波辐射、长波辐射和感热通量的模拟结果与观测值间的标准差分别为7.98,6.14,33.9 W·m^-2,与NOAH陆面过程模式的7.98,7.72,46.6 W·m^-2的结果接近.地表反照率是沙漠地区最重要的陆面过程参数,地表反照率增大5%,向上短波辐射通量随之增加5%,感热通量则减小2.8%.本文研究结果对丰富陆面过程参数化方案,改进全球陆面过程模式、气候模式具有参考意义.     

以微分热惯量为基础的地表蒸发全遥感信息模型及在甘肃沙坡头地区的验证

首先综合回顾了目前采用的地表通量遥感方法和途径.分析了现有遥感思路中不能摆脱非遥感参数的现实和困扰. 在实践的基础上, 建立了以微分热惯量为基础的地表蒸发全遥感信息模型. 其思路的关键是以微分热惯量提取土壤水分可供率而独立于土壤质地、类型等局地参数; 以土壤水分可供率推算波文比而摆脱气温、风速等非遥感参数. 并以净辐射通量和表观热惯量对土壤热通量进行参数化. 实现了以全遥感信息反演裸地蒸发(潜热通量)的目标. 应用接近最高和最低地表温度出现时刻的两幅NOAA- AVHRR 5个波段的影像图和地面同步观测数据, 作出了我国西北沙坡头地区的土壤蒸发的区域分布影像图. 同时以同步观测的地表蒸发值对影像图对应点的输出值进行了对比, 验证了本思路和模型的可行性, 并且讨论了本模型扩展到浓密植被区所能造成的误差和进一步改进途径.     

陆面蒸散对气候变化的影响

利用含有较真实的陆面过程的GOALS/LASG陆气耦合模式, 分别进行亚洲/北美洲陆面蒸散的敏感性试验来研究陆地与大气环流的相互作用. 模拟结果表明：模式气候对地表蒸散的变化是极其敏感的. 尤其是亚洲地表蒸散的变化将引起极为显著的气候效应, 若地表无蒸散将使气候在一定程度上变暖变干; 此外, 陆面蒸散的异常还通过季风降水的变化和 β 效应进一步影响副热带高压的形成和变异; 进而造成北半球甚至全球大气环流发生显著变化. 因此, 除了传统观点使人们很重视副热带高压活动对我国东部大陆夏季降水的影响以外, 陆面蒸散的异常通过季风降水的变化也会对副热带高压的活动产生明显影响. 由此, 夏季陆面蒸散及其水汽相变所致的大气内热源的变化是影响天气和气候的一个重要外强迫.     

北京城市热岛的时空变化分析

利用1987、1999、2000、2001、2002和2005年六幅陆地卫星影像研究北京市规划区地表城市热岛（SUHI）．首先用决策树分类法进行分类，得到六幅不同时相的土地利用／覆盖分类图像．根据Artis＆Carnahan算法利用热红外通道的灰度值计算地表辐射亮温，基于分类结果进行比辐射率纠正，计算地表温度．通过分析北京市规划区1987～2005年间地表城市热岛的特征，发现不同土地利用／土地覆盖类型与地表城市热岛有密切关系；2001年、2002年和2005年影像中市区的热岛分布的破碎度增加，由原来的集中分布慢慢向周围扩散，并在市区中心植被覆盖高的区域出现蓝色“凉爽”区；地表城市热岛增加的区域与城市扩展区域一致，城市化过程是城市热岛面积不断增加的主要的原因．     

GMS 5资料反演地表温度的一个修正算法

本文研究发展利用GMS 5/VISSR每小时卫星观测资料反演地表温度的方法,首先利用时空判断法进行云检测寻找晴空像元,然后从辐射传输方程出发,由实时探空资料求取大气上行、下行辐射率及大气透过率,根据由AVHRR NDVI导出的地表比辐射率,用单时相双光谱分裂窗法反演得到地表温度.比较反演结果与54511站及其他中国基准站2000年地面0cm地表温度实测值,相对于国际上其他经验公式而言,本文算法在精度上有所提高.敏感性分析试验着重于大气衰减的影响.基于本文算法,给出了内蒙中东部地区地表温度连续4天的变化实例以及东亚部分陆地“纯晴天”地表温度图.     

Modeling Water and Heat Balance Components for Large Agricultural Region Utilizing Information from Meteorological Satellites

The method has been developed to evaluate water and heat balance components for vegetation covered area of regional scale based on the refined physical-mathematical model of vertical water and heat exchange between land surface and atmosphere (Land Surface Model, LSM) for vegetation season adapted to satellite information on land surface and meteorological conditions. The LSM is accommodated for utilizing satellite-derived estimates of vegetation and meteorological characteristics as model parameters and input variables. Estimates of these characteristics presented as distributions of their values over the study area have been obtained from AVHRR/NOAA, MODIS/EOS Terra and Aqua, SEVIRI/Meteosat-9, -10 data. To build such estimates methods and technologies have been developed and refined using results of thematic processing measurement data from these sensors. Among them the original Multi Threshold Method (MTM) has been developed and tested to calculate daily precipitation sums using rainfall intensity estimates retrieved from AVHRR and SEVIRI data with subsequent replacement of ground-measured rainfall amounts by these daily rainfalls. All technologies have been adapted to the study area with square of 227300 km² being the part of the Central Black Earth Region of European Russia. Developed earlier procedures of utilizing satellitederived estimates of vegetation and meteorological characteristics (including precipitation) in the model have been refined and verified. Final result of modeling is the fields of soil water content, evapotranspiration and other water and heat balance components of the region under study for years 2012–2014 vegetation seasons.     

Influence of land evapotranspiration on climate variations

A coupled numerical model of the global atmosphere with a qualified biosphere (GOALS/LASG) has been used to assess the nature of the physical mechanisms for land-atmosphere interactions, and the impacts of the Asian/North American land-surface evapotranspiration on the regional and global climate. This sensitivity study suggests that the simulated climate would be relatively sensitive to land surface evapotranspiration, especially over the Asian regions. The removal of evapotranspiration in Asia would create a warmer and drier climate to a certain degree. Furthermore, the surface evapotranspiration anomalies would make a substantial contribution to the formation and variation of subtropical anticyclones through the changes in monsoon precipitation and the β -effect, but also make a large contribution to the variations of the atmospheric circulation in the Northern Hemisphere and even the globe. Therefore, besides the traditional perception that we have generally emphasized on the influence of subtropical anticyclones activities on the boreal summer precipitation over the regions of eastern China, the surface evapotranspiration anomalies, however, also have substantial impacts on the subtropical anticyclones through the changes in monsoon precipitation. For this reason, the variation in the internal heating sources of the atmosphere caused by the land surface evapotranspiration and the vapor phase change during the boreal summer is an important external factor forcing the weather and climate.     

Determination of regional net radiation and soil heat flux over a heterogeneous landscape of the Tibetan Plateau

This paper explores the potential for documenting regional fields of surface energy fluxes over the Tibetan plateau using published algorithms and previously calibrated empirical formulae with data from NOAA‐14 AVHRR and atmospheric data collected during the GAME‐Tibet field experiment. Comparison with observations at three field sites suggests errors in the resulting estimates are less than 10% in the clear sky conditions necessary for application of this approach. Because of the need for clear skies, it was only possible to calculate the desired regional fields for one satellite scene during the 5 month study period. Maps of surface energy fluxes, and frequency analyses of these maps, are presented for this scene. The need for an alternative, more consistently applicable, satellite‐based method to map surface energy fields is highlighted. Copyright © 2002 John Wiley & Sons, Ltd.     

昆仑山地震前长波辐射异常特征分析

应用NOAA、AVHRR资料反演的地气长波辐射值OLR对2001年11月14日昆仑山口西8.1级地震进行了追踪研究。结果表明：2001年10月起OLR出现明显的异常带，随时间的变化，异常区域不断向未来的震源聚拢，并且在未来地震震中区持续存在小的OLR高值闭合区，10月开始OLR出现突出的反常升势。     

Measurement of ecological capital of Chinese terrestrial ecosystem based on remote sensing

The biosphere of the Earth is the material founda-tion of human survival and development.With the increasing problems of the resources,the environment and population,most countries in the world have paid special attention to the measurement and evaluation of ecological capital,which refers to the sum of the direct natural resources value and the indirect ecosystem services value.Ecological capital depends on not only the quality of the national ecological environment,butalso the social recogni…     

Relations indices de Végétation–Pluie au Burkina Faso: Cas du Bassin Versant du Nakambé/Relationship between Rainfall and Vegetation Indexes in Burkina Faso: A Case Study of the Nakambé Basin

Abstract

This work deals with the problem of the use of remote sensing data derived from NOAA/AVHRR observations for monitoring the West African Sahel climatic variability. NDVI is widely used in hydrological and climatological research, and in the study of global climatic changes. The relationships between NDVI and climatic parameters are not well established yet and are the focus of many studies. The relationships between NDVI and rainfall were studied at a 10-day time step in the Nakambe River basin in Burkina Faso in the Sahelo-Sudanian area over the years 1982–1999. Good correlations were found in the annual evolution of these two variables. The statistical analysis shows a significant relationship between NDVI and the sum of the annual rainfall with determination coefficients greater than 0.80. At the spatial scale of 0.5° × 0.5°, the determination coefficient ranges from 0.91 to 0.96. It was also found that the NDVI is a good indicator of the determination of the beginning and the end of the rainy season. It gives reasonably good results in comparison with the other methods commonly used in the study region.     

近20年青海湖湖水面积变化遥感

采用NOAA/AVHRR资料,对青海湖湖面进行水体判识,并利用线性混合模式对混合象元进行处理,定量估算了近20年青海湖湖水面积并分析了变化趋势,表明近20年青海湖湖水面积在不断减小,每年减少约4km2,并且青海湖干涸部分主要在其北部.进一步采用主成分分析和回归分析方法对青海湖地区降水、气温和蒸发量做了初步气候分析,表明青海湖地区降水减少、气温升高、蒸发量增加是青海湖湖水面积逐年减少的主要原因.     

Perspectives in using a remotely sensed dryness index in distributed hydrological models at the river‐basin scale

In a previous study a spatially distributed hydrological model, based on the MIKE SHE code, was constructed and validated for the 375 000 km² Senegal River basin in West Africa. The model was constructed using spatial data on topography, soil types and vegetation characteristics together with time‐series of precipitation from 112 stations in the basin. The model was calibrated and validated based on river discharge data from nine stations in the basin for 11 years. Calibration and validation results suggested that the spatial resolution of the input data in parts of the area was not sufficient for a satisfactory evaluation of the modelling performance. The study further examined the spatial patterns in the model input and output, and it was found that particularly the spatial resolution of the precipitation input had a major impact on the model response. In an attempt to improve the model performance, this study examines a remotely sensed dryness index for its relationship to simulated soil moisture and evaporation for six days in the wet season 1990. The index is derived from observations of surface temperature and vegetation index as measured by the NOAA Advanced Very High Resolution Radiometer (AVHRR) sensor. The correlation results between the index and the simulation results are of mixed quality. A sensitivity analysis, conducted on both estimates, reveals significant uncertainties in both. The study suggests that the remotely sensed dryness index with its current use of NOAA AVHRR data does not offer information that leads to a better calibration or validation of the simulation model in a spatial sense. The method potentially may become more suitable with the use of the upcoming high‐resolution temporal Meteosat Second Generation data. Copyright © 2002 John Wiley & Sons, Ltd.     

Comparison of ensemble-based state and parameter estimation methods for soil moisture data assimilation

Model parameters are a source of uncertainty that can easily cause systematic deviation and significantly affect the accuracy of soil moisture generation in assimilation systems. This study addresses the issue of retrieving model parameters related to soil moisture via the simultaneous estimation of states and parameters based on the Common Land Model (CoLM). The state-parameter estimation algorithms AEnKF (Augmented Ensemble Kalman Filter), DEnKF (Dual Ensemble Kalman Filter) and SODA (Simultaneous optimization and data assimilation) are entirely implemented within an EnKF framework to investigate how the three algorithms can correct model parameters and improve the accuracy of soil moisture estimation. The analysis is illustrated by assimilating the surface soil moisture levels from varying observation intervals using data from Mongolian plateau sites. Furthermore, a radiation transfer model is introduced as an observation operator to analyze the influence of brightness temperature assimilation on states and parameters that are estimated at different microwave signal frequencies. Three cases were analyzed for both soil moisture and brightness temperature assimilation, focusing on the progressive incorporation of parameter uncertainty, forcing data uncertainty and model uncertainty. It has been demonstrated that EnKF is outperformed by all other methods, as it consistently maintains a bias. State-parameter estimation algorithms can provide a more accurate estimation of soil moisture than EnKF. AEnKF is the most robust method, with the lowest RMSE values for retrieving states and parameters dealing only with parameter uncertainty, but it possesses disadvantages related to increasing sources of uncertainty and decreasing numbers of observations. SODA performs well under the complex situations in which DEnKF shows slight disadvantages in terms of statistical indicators; however, the former consumes far more memory and time than the latter.     

植被覆盖状况影响中国地表气温变化的观测事实

利用NOAA/AVHRR归一化植被指数（NDVI）及观测气温与再分析地表气温的差值（Observation Minus Reanalysis, OMR）分析了植被覆盖状况对中国地表气温变化的影响.结果表明,地表气温OMR趋势值与NDVI在空间上呈现出显著的负相关关系,植被覆盖状况差（NDVI小于0.1）的区域地表升温较为显著,气温OMR趋势值超过0.2℃/10a,而植被覆盖度高（NDVI大于0.5）的区域气温OMR趋势值则变化不大,甚至出现降温.气温OMR趋势值对植被的季节变化还有着敏感的响应.不同区域植被覆盖状况的差异可能导致中国地表气温变化对全球变暖的响应不同,预测中国未来气候变化需要考虑植被覆盖状况及其动态变化的影响.