青藏高原地表特征时空分布

通过利用地理信息数据库、卫星反演参数、气象观测数据,分析了我国青藏高原地区地表植被覆盖、地表反照率分布、地表蒸发分布、地表积雪分布.结果显示,随着青藏高原地表年平均气温的显著升高,青藏高原部分区域地表覆盖特征也发生了改变.在青藏高原南缘湿润大区降水充分地区,地表反照率相对较低,潜热蒸发量最大,1982～2000年期间地表植被覆盖呈明显增加趋势.青藏高原地区积雪覆盖在各个气候区域也呈现同步变化特征,自1970～1989期间,降雪量呈持续增加趋势,但之后至2000年期间,全区降雪量呈下降趋势,其中积雪覆盖变化最强烈的时段发生在10月～4月之间,变化幅度最大的区域位于青藏高原的东南部区域.     

青藏高原MODIS地表反照率和GLASS地表反照率的对比分析

对比分析了青藏高原MODIS地表反照率产品和GLASS地表反照率产品的空间分布连续性、高质量反演结果的比例,应用青藏高原CAMP/Tibet试验期间的高精度观测数据评估了两种产品的精度,通过人工目视解译MODIS地表反射率图像并结合MODIS积雪产品分析了影响两种产品精度的原因,结果表明：1）GLASS地表反照率产品具有比MODIS地表反照率产品更好的空间分布连续性和更高的反演质量;2）绝大多数时段内两种产品都能与地面观测结果保持较好的一致性,能准确地反映地表反照率的异常变化过程;3）局地积雪是影响两种产品精度的重要因素之一;4）积雪条件下,GLASS地表反照率反演算法比MODIS地表反照率反演算法更具优势。研究结果有助于促进人们对地表反照率卫星遥感反演产品的认识,改进青藏高原地表反照率卫星遥感反演算法,提高青藏高原地表反照率卫星遥感反演结果的精度、反演质量和空间分布连续性。     

青藏高原地表反照率时空分布与统计回归计算

本文在利用NOAA/AVHRR数据反演得到1982～2000年青藏高原地区地表反照率时空分布的基础上,分析了地表反照率的时空变化及其与温度和降水之间的关系,得到地表反照率与温度和降水之间的统计方程,并用此方程计算了青藏高原地区地表反照率的时空分布。研究结果表明：青藏高原地区年均地表反照率的分布与高原自然地理带的分布特征大致吻合;地表反照率与温度和降水均有较好的相关性,相关性因下垫面植被类型的不同而有较大的差异,滞后1个月的温度和滞后2个月的降水的综合作用与地表反照率的相关性最好;月均地表反照率与温度和降水之间的二元曲线回归方程可以比较好的统计回归计算出青藏高原地区地表反照率的空间分布,该模型的系统偏差比较小,回归计算的效果比较好。     

青藏高原冬春积雪和地表热源影响亚洲夏季风的研究进展

青藏高原冬春积雪和地表热源的气候效应是青藏高原气候动力学的两个重要内容。大量资料分析和数值试验研究均表明这两个因子对亚洲季风有一定的预测意义,本文对此做了比较系统的回顾和总结,并进一步比较了青藏高原积雪和地表热源影响东亚和南亚夏季降水的异同。结果表明,东亚夏季降水在年际和年代际尺度上均存在"三极型"和"南北反相"型的空间分布特征,高原春季地表热源在年代际和年际尺度上主要影响东亚夏季降水"三极型"模态;在年代际尺度上它是中国东部出现"南涝北旱"格局的重要原因,而高原冬季积雪的作用相反。另一方面,高原冬季积雪在年际和年代际尺度上对印度夏季风降水的预测效果均要优于高原地表热源。无论是空间分布还是时间演变特征,高原冬季积雪与春季地表热源整体上均无统计意义上的显著联系。不断完善高原地面观测网和改进模式在高原地区的模拟性能,将是进一步深入理解高原积雪和地表热源影响亚洲季风物理过程和机制的关键所在。     

青藏高原GLASS地表反照率产品精度分析

应用2003年青藏高原3个站点的地表反照率观测结果,对比分析了GLASS(Global LAnd Surface Satellites)地表反照率1 km×1 km分辨率产品的精度,结果表明,GLASS黑空反照率、白空反照率与地表反照率地面观测结果的总体变化趋势基本一致,能够有效地反映实际地表状态的变化;局地积雪和云覆盖对GLASS地表反照率产品的精度影响较大,云覆盖导致GLASS地表反照率可能比实际地表反照率高;消除云覆盖和局地积雪的影响后,GLASS黑空反照率、白空反照率与地表反照率地面观测结果的均方根误差显著降低,分别为0.0155和0.0190。     

青藏高原4月陆面状况和地表加热异常与中国夏季降水的联系

利用1981—2002年GIMMS-NDVI资料、中国西部数据中心提供的雪深长时间序列数据集、中国753个测站降水资料及ECMWF再分析地表通量资料,通过相关和合成分析等统计方法,探讨了青藏高原(下称高原)4月植被覆盖、积雪异常与地表加热异常和与后期中国夏季降水之间的联系。结果表明,高原4月的陆面状况与同期的地表加热存在密切的联系,植被覆盖和积雪深度的变化具有较好的一致性;高原植被覆盖(积雪)主要影响地表感热(潜热)通量,从而改变高原地区的地表加热;高原地表加热和中国夏季降水存在较为密切的关系。就年际异常而言,前期高原地表加热异常与长江以南地区6月降水存在明显的负相关,与7月降水的显著负相关区域主要位于华北、东北地区,与8月降水的显著负相关区主要位于长江中上游及淮河一带。相比之下,前期高原地表加热与夏季降水的年际增幅异常之间存在更为密切的联系,即前期高原地表加热年际增幅异常与长江以南及西南部分地区6月降水年际增幅异常为负相关,而与7、8月降水年际增幅异常主要呈南正北负的分布特征。     

青藏高原积雪时空变化特征及年际异常成因

利用国家气象信息中心提供的日积雪深度的台站观测资料以及JRA55提供的大气环流再分析资料,分析了1961 2013年前冬(11月至次年1月)和后冬(2 4月)青藏高原中东部地区积雪深度(以下简称积雪)的时空变化特征,探究了影响高原中东部整体积雪异常和年际变化的环流形态及水汽条件。结果表明,高原积雪以显著的年际变化和年代际变化为主,在空间分布上具有明显的不均匀性,海拔越高,积雪的年际变率越大。不论前冬还是后冬,高原中东部积雪最主要的变化形势均为全区一致型。1961 2013年前冬和后冬积雪无明显的长期变化趋势,前冬的积雪在1996年以前显著增加,1996年以后转为减少趋势。从高原积雪年际变化的成因来看,前冬积雪很可能同时受北极涛动和高原附近位势高度年际变化的主导,后冬积雪受高原附近位势高度变化的主导,并受北极涛动年际变化的调节。当高原积雪偏多时,阿拉伯海到青藏高原以东地区的位势高度偏低,导致南支槽活跃,高原南侧西风急流加强,槽前携带的水汽增加,副热带高压偏北偏强同时其外围携带的水汽增加;贝加尔湖脊加强有利于引导冷空气南下,冷空气和暖湿空气在高原东部交汇使得高原中东部降雪和积雪增加。     

1982—2000年中国区域地表反照率时空分布特征

利用1982—2000年NOAA-AVHRR数据资料,研究了中国区域地表反照率的空间分布及其随时间的变化规律。结果表明,中国区域年均地表反照率在空间分布上有很大的差异,胡焕庸线以西地区地表反照率明显大于以东地区;年平均地表反照率呈现缓慢下降趋势,但是不同地区的变化趋势有所不同,年均地表反照率显著降低的区域主要集中在华北平原,显著增加的区域主要集中在长白山和大兴安岭北部;不同季节地表反照率存在很大的差异,冬季最大,春、夏季次之,秋季最小,且冬季平均地表反照率波动幅度比较大;不同地表覆盖的地表反照率的年际变化也存在比较显著的差异。     

青藏高原不同地区辐射特征对比分析

利用"全球协调加强观测计划(CEOP)之亚澳季风青藏高原试验"(CAMP/Tibet)在藏北高原的BJ站、NPAM站及中国科学院珠穆朗玛峰大气与环境综合观测研究站、纳木错多圈层相互作用综合观测研究站和藏东南高山环境综合观测研究站2007年的辐射观测资料,分析了这些地区不同下垫面地表辐射各分量及地表反照率的日变化和月际变化特征。结果表明,向下短波辐射受太阳高度角的影响存在明显的日变化和月际变化;向上短波辐射的月际变化基本与总辐射一致,在个别月份由于高原积雪造成地表反照率较高,从而使晴天向上短波辐射全年较高;向下长波辐射存在基本的季节变化,最大值出现在天空总云量较多的夏季(6～8月),最小值出现在冬季(12月和1月);向上长波辐射基本上都是夏季为全年最大,冬季为全年最小。这与地表温度的年变化情况相一致。高原不同地区各季节晴天地表净辐射存在差异,NPAM站和藏东南站由于下垫面植被覆盖较好,净辐射值各季节均高于其它各站;NPAM站、纳木错站和珠峰站地表反照率日变化曲线呈"U"型,BJ站和藏东南站日变化相对复杂,藏东南站全年月平均地表反照率较小且变化不大,其他各站存在基本的年变化趋势。     

春季青藏高原积雪年际变率的年代际转型对东亚夏季风影响的研究进展

冬春青藏高原积雪异常是东亚夏季风的重要预测因子之一。本文系统回顾了近20年关于青藏高原积雪年际变率的年代际转型影响东亚夏季风的相关研究,主要结论如下：（1）20世纪90年代初春季青藏高原积雪的年际变率从东西偶极型转变为全区一致型,这主要受北太平洋、热带大西洋海温异常变化的影响,也与南极涛动、北极涛动的变化密切相关;（2）春季青藏高原积雪年际变率的年代际转型可通过影响东亚高层的副热带西风急流和低层的水汽输送,进而影响东亚夏季风降水格局变化;（3）青藏高原积雪异常可通过“高原大气河”的机制影响梅雨雨带;（4）大西洋年代际振荡可调节春季青藏高原积雪与梅雨降水关系的年代际变化,当大西洋年代际振荡为正（负）位相时,春季青藏高原积雪与梅雨的关系加强（减弱）。最后,本文对青藏高原积雪异常影响东亚季风变化的关键科学问题进行了讨论与展望。     

CHARACTERISTICS OF VEGETATION COVER, ROUGHNESS AND ALBEDO DISTRIBUTION OVER CHINA*

To build land surface dataset for climate model,with application of remote sensing technique as well as the Geographic Information System(GIS),the data of surface type,roughness and albedo over China in 1997 were retrieved,resolutions being 10 km×10 km.Based on these data,an analysis is conducted on the geographic distributions and seasonal variations of surface vegetation cover and roughness as well as albedo over China.Results show that surface vegetation cover is mainly located to the south of Yangtze River,in Southwest and Northeast China andsparse vegetation cover is in the Northwest.The variation of land surface cover affects the variations of land surface roughness and albedo.High albedo occurred in the north of Xinjiang Autonomous Region,the north of Northeast China and the Qinghai-Xizang Plateau in winter,in correspondence with the location of snow cover.For most part of China,surface roughness decreases and albedo increases in winter,while the roughness increases and the albedo decreases in summer,which could mainly result from land surface cover(snow cover and vegetation cover)and soil moisture changes.This shows that the geographic distribution and seasonal variation of the albedo are almost opposite to those of the roughness,in agreement with theoretical results.Temporally,the amplitude of surface roughness change is quite small in comparison with the roughness itself.     

利用MODIS卫星资料反演中国地区晴空地表短波反照率及其特征分析

利用MODIS地表双向反照率产品(MOD43B1),结合地表海拔高度和地表覆盖类型资料,计算并分析了中国地区晴空反照率的时空分布,以及地表反照率与地形和地表覆盖的关系.首先,利用改则自动气象站的地基观测对MODIS地表反照率进行了对比验证.验证结果表明卫星观测可以较好地反映反照率随时间的变化,MODIS地表反照率与地表实测反照率符合较好.年平均地表反照率与海拔高度有很好的相关,反照率的高值出现在高海拔山区.冬春季节,我国高海拔山区因积雪覆盖成为反照率的高值区;夏秋季节,地表反照率主要受地表土壤湿度和植被盖度的影响,沙地和沙漠地带反照率最高.最后,计算了中国典型地表类型的反照率随时间的变化,结果表明大部分地表类型的反照率具有较大的时间变化,地表反照率在春秋季节较大,夏季反照率较小.     

CHARACTERISTICS OF VARIATION IN SURFACE ALBEDO AND SNOW FORCING OVER THE TIBETAN PLATEAU

The combination of field experiments and satellite observations is the fundamental way tounderstand the characteristics of spatial-temporal variation in surface albedo over the Tibetan(Qinghai-Xizang) Plateau. Under the condition without snow cover, the relatively regular annualvariation cycle of the surface albedo can be expressed by an empirical formula. The effect of snowcover on the surface albedo in winter can be expressed by introducing two variables of snow forcingand sensitivity parameter. The existing satellite retrieved results of surface albedo may provide thedigital grid data for describing the geographical distribution. However, some satellite retrievedsurface albedos available over the Tibetan Plateau are obviously too low in winter. Taking thesatellite derived results in summer as the background field representative of geographicaldistribution and combining the empirical formula of annual cycle based on the surface observations,a dynamic model of surface albedo is developed for the need of modeling the climatic influence ofthe underlying surface forcing of the Tibetan Plateau.     

CHARACTERISTICS OF VARIATION IN SURFACE ALBEDO AND SNOW FORCING OVER THE TIBETAN PLATEAU*

The combination of field experiments and satellite observations is the fundamental way to understand the characteristics of spatial-temporal variation in surface albedo over the Tibetan(Qinghai-Xizang) Plateau. Under the condition without snow cover, the relatively regular annual variation cycle of the surface albedo can be expressed by an empirical formula. The effect of snow cover on the surface albedo in winter can be expressed by introducing two variables of snow forcing and sensitivity parameter. The existing satellite retrieved results of surface albedo may provide the digital grid data for describing the geographical distribution. However, some satellite retrieved surface albedos available over the Tibetan Plateau are obviously too low in winter. Taking the satellite derived results in summer as the background field representative of geographical distribution and combining the empirical formula of annual cycle based on the surface observations,a dynamic model of surface albedo is developed for the need of modeling the climatic influence of the underlying surface forcing of the Tibetan Plateau.     

Land Cover, Rainfall and Land-Surface Albedo in West Africa

Land surface albedo is an important variable in General Circulation Models (GCMs). When land cover is modified through anthropogenic land use, changes in land-surface albedo may produce atmospheric subsidence and reduction of rainfall. In this study we examined albedo time series and their relationships with rainfall, land cover, and population in West Africa. This particular region was selected because it has become a focal point in debates over biophysical impacts of desertification and deforestation. Our analyses revealed that albedo and rainfall were related only modestly at short time scales (monthly and annual) and that mean annual albedo values remained relatively stable from 1982–1989 over a widerange of climatic and vegetation zones in West Africa. The relationship between long-term mean rainfall and mean albedo was strong and curvilinear(r² = 0.802). The same was true for the relationship betweenpercent tree cover and mean albedo (r² = 0.659). These results suggest that long-term climate patterns, which control vegetation type and canopy structure, have greater influence on albedo than short-term fluctuations in rainfall. Our results reinforce other recent studies based on satellite data that have questioned the extent and pervasiveness of desertification in West Africa.     

Quantifying uncertainties in projections of extremes��a perturbed land surface parameter experiment

Uncertainties in the climate response to a doubling of atmospheric CO₂ concentrations are quantified in a perturbed land surface parameter experiment. The ensemble of 108 members is constructed by systematically perturbing five poorly constrained land surface parameters of global climate model individually and in all possible combinations. The land surface parameters induce small uncertainties at global scale, substantial uncertainties at regional and seasonal scale and very large uncertainties in the tails of the distribution, the climate extremes. Climate sensitivity varies across the ensemble mainly due to the perturbation of the snow albedo parameterization, which controls the snow albedo feedback strength. The uncertainty range in the global response is small relative to perturbed physics experiments focusing on atmospheric parameters. However, land surface parameters are revealed to control the response not only of the mean but also of the variability of temperature. Major uncertainties are identified in the response of climate extremes to a doubling of CO₂. During winter the response both of temperature mean and daily variability relates to fractional snow cover. Cold extremes over high latitudes warm disproportionately in ensemble members with strong snow albedo feedback and large snow cover reduction. Reduced snow cover leads to more winter warming and stronger variability decrease. As a result uncertainties in mean and variability response line up, with some members showing weak and others very strong warming of the cold tail of the distribution, depending on the snow albedo parametrization. The uncertainty across the ensemble regionally exceeds the CMIP3 multi-model range. Regarding summer hot extremes, the uncertainties are larger than for mean summer warming but smaller than in multi-model experiments. The summer precipitation response to a doubling of CO₂ is not robust over many regions. Land surface parameter perturbations and natural variability alter the sign of the response even over subtropical regions.     

Impact of absorbing aerosol deposition on snow albedo reduction over the southern Tibetan plateau based on satellite observations

We investigate the snow albedo variation in spring over the southern Tibetan Plateau induced by the deposition of light-absorbing aerosols using remote sensing data from moderate resolution imaging spectroradiometer (MODIS) aboard Terra satellite during 2001–2012. We have selected pixels with 100 % snow cover for the entire period in March and April to avoid albedo contamination by other types of land surfaces. A model simulation using GEOS-Chem shows that aerosol optical depth (AOD) is a good indicator for black carbon and dust deposition on snow over the southern Tibetan Plateau. The monthly means of satellite-retrieved land surface temperature (LST) and AOD over 100 % snow-covered pixels during the 12 years are used in multiple linear regression analysis to derive the empirical relationship between snow albedo and these variables. Along with the LST effect, AOD is shown to be an important factor contributing to snow albedo reduction. We illustrate through statistical analysis that a 1-K increase in LST and a 0.1 increase in AOD indicate decreases in snow albedo by 0.75 and 2.1 % in the southern Tibetan Plateau, corresponding to local shortwave radiative forcing of 1.5 and 4.2 W m⁻², respectively.

     

Numerical simulation of the impact of vegetation index on the interannual variation of summer precipitation in the Yellow River Basin

Two sets of numerical experiments using the coupled National Center for Environmental Prediction General Circulation Model （NCEP/GCM T42L18） and the Simplified Simple Biosphere land surface scheme （SSiB） were carried out to investigate the climate impacts of fractional vegetation cover （FVC） and leaf area index （LAI） on East Asia summer precipitation, especially in the Yellow River Basin （YRB）. One set employed prescribed FVC and LAI which have no interannual variations based on the climatology of vegetation distribution; the other with FVC and LAI derived from satellite observations of the International Satellite Land Surface Climate Project （ISLSCP） for 1987 and 1988. The simulations of the two experiments were compared to study the influence of FVC, LAI on summer precipitation interannual variation in the YRB. Compared with observations and the NCEP reanalysis data, the experiment that included both the effects of satellite-derived vegetation indexes and sea surface temperature （SST） produced better seasonal and interannual precipitation variations than the experiment with SST but no interannual variations in FVC and LAI, indicating that better representations of the vegetation index and its interannual variation may be important for climate prediction. The difference between 1987 and 1988 indicated that with the increase of FVC and LAI, especially around the YRB, surface albedo decreased, net surface radiation increased, and consequently local evaporation and precipitation intensified. Further more, surface sensible heat flux, surface temperature and its diurnal variation decreased around the YRB in response to more vegetation. The decrease of surface-emitting longwave radiation due to the cooler surface outweighed the decrease of surface solar radiation income with more cloud coverage, thus maintaining the positive anomaly of net surface radiation. Further study indicated that moisture flux variations associated with changes in the general circulation also contributed to the precipitation interannual variation.     

The Albedo of Vegetated Land Surfaces: Systems Analysisand Mathematical Modeling

Summary The albedo of vegetated land surfaces (surface albedo) is a key factor in climate modeling and in mechanistic accounting of many ecological processes. This paper proposes a testable numerical equation for the analysis and projection of surface albedo. Conceptualized as the manifestation of a canopy elements-determined basic property after modifications by temporal and spatial circumstances, surface albedo was depicted analytically in relation to 11 driving variables (leaf size, leaf life span, relative leaf age, canopy leaf cover, relative stem cover, vegetation height, stress-calendar day, drought indicator, optical air mass, station atmospheric pressure, snow cover). With peripheral algorithms developed to derive all but two of those variables, surface albedo was linked ultimately to eight rudimentary factors (calendar day, latitude, elevation, vegetation height, dominant plant species, monthly air temperature, monthly precipitation, snow cover). The analytical framework, and then its coefficient values, for surface albedo were generally supported by a series of statistical evaluations in terms of: (i) the equation’s ability to capture, by regression fitting, the variation in the surface albedo of 26 forests (135 data points) distributed around the world; (ii) the quantitative significance of individual driving variables; (iii) the randomness of residual or error distributions; (iv) the performance of the forests-fitted equation in extrapolative prediction of surface albedo against independent data for 8 deforested sites (93 data points) and for 3 types of vegetation (7 data points) at the Arctic treeline. Compared to the data, the fitted or projected albedo values had a margin of error generally within ±10%. The individual coefficient values and component functions of the final equation were consistent with their supposed mechanistic underpinnings, based on independent information from the literature. The equation shed new insight into the quantitative behavior of surface albedo, and upon further validation, should be useful for modeling surface albedo as a key land surface-atmosphere feedback link that varies and interacts with climate and vegetation. Received August 18, 1997