以西藏地区38个国家基准站和基本站的实测降水资料，利用双线性插值、相关系数、散点斜率和相对误差等指标，对热带降水测量卫星（TRMM）的3B43降水产品的精度进行检验和分析。结果表明：月尺度上，整体而言TRMM3B43降水产品与实测降水量具有较好的一致性，其中西藏西部和东部喜马拉雅山脉东段北麓地区相关性相对较差，平均相对误差较大。年尺度上TRMM3B43降水产品的相关性不如月尺度好，平均相对误差随统计数值的增大而减小。在应用TRMM3B43降水产品进行流域面雨量估算时，采用气象站点实测降水资料校准TRMM3B43降水产品的T-G联合法，对TRMM3B43降水产品进行订正。

<p>统计降尺度是解决由气象模式输出的低分辨率资料到流域尺度资料转换的手段之一，已成为一个重要的研究领域。统计降尺度方法十分丰富，分为传递函数法、天气形势法和天气发生器3类，3类之间并无严格的界限。统计降尺度涉及到时间与空间降尺度、随机型与确定型降尺度、时间自相关与空间相关性以及面向格点与面向站点的降尺度这4个方面的属性与分类问题，各种具体方法在这些方面的表现有所不同。近年来，相似法、隐马尓可夫模型、广义线性模型、Poisson点过程以及乘性瀑布过程获得了较大的发展和应用，并诞生了各种非线性模型以及物理&mdash;统计模型等新方法，已有一些影响较大的统计降尺度模型软件。新的方法在不断涌现，其中非线性模型、气候情境随机模拟技术、短期预报资料降尺度技术以及结合物理机理的统计降尺度方法是未来的主要发展趋势。</p>

A stochastic model that relates synoptic atmospheric data to daily precipitation at a network of gages is presented. The model extends the nonhomogeneous hidden Markov model (NHMM) of Hughes et al. by incorporating precipitation amounts. The NHMM assumes that multisite, daily precipitation occurrence patterns are driven by a finite number of unobserved weather states that evolve temporally according to a first-order Markov chain. The state transition probabilities are a function of observed or modeled synoptic scale atmospheric variables such as mean sea level pressure. For each weather state we evaluate the joint distribution of daily precipitation amounts at n sites through the specification of n conditional distributions. The conditional distributions consist of regressions of transformed amounts at a given site on precipitation occurrence at neighboring sites within a set radius. Results for a network of 30 daily precipitation gages and historical atmospheric circulation data in southwestern Australia indicate that the extended NHMM accurately simulates the wet-day probabilities, survival curves for dry- and wet-spell lengths, daily precipitation amount distributions at each site, and intersite correlations for daily precipitation amounts over the 15 year period from 1978 to 1992.

Precipitation data with accurate, high spatial resolution are crucial for improving our understanding of basin scale hydrology. We explore the relation between precipitation estimates derived from the Tropical Rainfall Monitoring Mission (TRMM) and the normalized difference vegetation index (NDVI) for different spatial scales on the Iberian Peninsula in southern Europe, using time series from 2001 to 2007. Analysis shows that NDVI is a good proxy for precipitation. On an annual basis an exponential function best describes the relation between NDVI and precipitation. The optimum relation between NDVI and precipitation is found at an approximate scale of 75 100 km. This is an intermediate scale and it is likely that at smaller scales NDVI is determined primarily by anthropogenic land use and at larger scales factors such as geology, soils, and temperature play an increasingly important role. The fact that both TRMM and NDVI are subject to bias due to orbital deviations, atmospheric conditions and imperfect retrieval algorithms could also influence the scale dependency. The derived relation between NDVI and precipitation is used to develop a new downscaling methodology that uses coarse scale TRMM precipitation estimates and fine scale NDVI patterns. The downscaled precipitation estimates are subsequently validated using an independent precipitation dataset. The downscaling procedure resulted in significant improvements in correlation, bias, and root mean square error for average annual precipitation over the whole period, for a dry year (2005), and a wet year (2003).

Abstract This article presents the results of an experiment to estimate rainfall from the normalized difference vegetation index (NDVI). The study was carried out in the semi-arid region of south and southern Botswana, principally the Kalahari desert, where few rainfall-reporting stations exist. A statistical regression between NDVI and rainfall is developed for four areas with diverse soil conditions. These are used to estimate rainfall at an independent station or group of stations. The estimates reliably capture both the seasonal cycle and inter-annual variability. These regressions are used to produce a map of mean annual rainfall for the period 1982 to 1993, based on NDVI data, for the region 22 to 27 S and 20 to 26 E. The estimates are verified using all data available in the Meteorological Services' archive for these years.

The use of remotely sensed data to describe, study, monitor and provide greater understanding on watershed’s landscape dynamics have proven to be useful worldwide, especially where timely and reliable ground information are neither available nor accessible like in most of the developing world. This paper, thus presents the first documented relationship between NDVI and rainfall in humid central Africa, and serves as a precursor in the understanding of the interaction between catchment characteristics and water resources of the Semliki region. This study investigates spatial and temporal relationship between NDVI and satellite-derived rainfall. Normalized Difference Vegetation Index (NDVI) time series derived from the NOAA–AVHRR (National Oceanic and Atmospheric Administration–Advanced Very High Resolution Radiometer) satellite data and FEWS satellite-derived rainfall are analyzed. The Semliki watershed (23,621 km 2) of the equatorial Nile basin is the study area. Monthly NDVI time series of 21 Semliki’s subcatchments (S3–S23) over 7 years (2001–2007) were processed and extracted with Windisp 5.1 from 10-day NDVI maximum value composite images. At the monthly time step, only 12 subcatchments had weak positive correlation (0.23–0.42) at 5% significance level and the rest were not significantly correlated. Incorporating a 1-month lag effect increased the correlation coefficients between the two variables (0.28–0.68) with 17 subcatchments being significantly correlated at the designated level. The topography within the catchment was found to play a defining role for NDVI values. S15, S16, S18 and S20, the subcatchments covering the Mount Ruwenzori characterized by elevations up to 4862 m above sea level, consistently recorded the lowest values of NDVI over time and no significant correlation could be established between rainfall and NDVI.

<p>庞大的青藏高原不仅影响其周围的气候,也影响整个亚洲甚或全球的气候,而且本身还形成了独特的高原气候。但高原上气象观测站点极为稀少,降水资料奇缺,难以完整、深刻地认识高原降水的时空分布格局。选用热带降雨测量计划卫星(Tropical Rainfall Measuring Mission,TRMM)3B43 月尺度降水率数据,并根据114 个气象站点数据与TRMM数据的差额和克里格球形插值模型对原数据进行了修正,克服了原数据低值高估、高值低估的问题,并以此分析了青藏高原1998~2011 年的多年平均降水的空间格局与季节分布特征。研究结果证实了青藏高原降水的空间格局呈现自东南向西北递减、自南向北逐渐减少的基本分布规律,包括喜马拉雅山北坡雨影区、高原西北部&ldquo;寒旱核心&rdquo;的存在;还发现了一些新的规律,包括阿里喀喇昆仑山少雨区、高原腹地相对湿润区、横断山脉中心相对干旱区等。高原降水的季节分配不均匀,其中,西、北部春(3~5 月)、秋(9~11 月)和冬(12~2 月)的降水占全年降水比例均为20%~30%,夏季(6~8 月)降水稍多,比例为30%~40%;东南部降水主要集中在夏季,比例高达40%~60%,春、秋降水比例为20%~30%,冬季降水比例低于10%。</p>

Remotely sensed precipitation from METEOSAT data and leaf area index (LAI) from NOAA AVHRR data is used as input data to the distributed hydrological modelling of three subcatchments (82,000 km 2) in the Senegal River Basin. Further, root depths of annual vegetation are related to the temporal and spatial variation of LAI. The modelling results are compared with results based on conventional input of precipitation and vegetation characteristics. The introduction of remotely sensed LAI shows improvements in the simulated hydrographs, a marked change in the relative proportions of actual evapotranspiration comprising canopy evaporation, soil evaporation and transpiration, while no clear trend in the spatial pattern could be found. The remotely sensed precipitation resulted in similar model performances with respect to the simulated hydrographs as with the conventional raingauge input. A simple merging of the two inputs did not result in any improvement.

A remote sensing based method is presented for calculating evapotranspiration rates (位E) using standard meteorological field data and radiometric surface temperature recorded for bare soil, maize and wheat canopies in Denmark. The estimation of 位E is achieved using three equations to solve three unknowns; the atmospheric resistance (rae), the surface resistance (rs) and the vapour pressure at the surface (es) where the latter is assessed using an empirical expression. The method is applicable, without modification, to dense vegetation and moist soil, but for a dry bare soil, where the effective source of water vapour is below the surface, the temperature of the evaporating front (Ts*) can not be represented by the measured surface temperature (Ts). In this case (Ts-Ts*) is assessed as a linear function of the difference between surface temperature and air temperature. The calculated 位E is comparable to latent heat fluxes recorded by the eddy covariance technique.

The use of remotely sensed data to describe, study, monitor and provide greater understanding on watershed’s landscape dynamics have proven to be useful worldwide, especially where timely and reliable ground information are neither available nor accessible like in most of the developing world. This paper, thus presents the first documented relationship between NDVI and rainfall in humid central Africa, and serves as a precursor in the understanding of the interaction between catchment characteristics and water resources of the Semliki region. This study investigates spatial and temporal relationship between NDVI and satellite-derived rainfall. Normalized Difference Vegetation Index (NDVI) time series derived from the NOAA–AVHRR (National Oceanic and Atmospheric Administration–Advanced Very High Resolution Radiometer) satellite data and FEWS satellite-derived rainfall are analyzed. The Semliki watershed (23,621 km 2) of the equatorial Nile basin is the study area. Monthly NDVI time series of 21 Semliki’s subcatchments (S3–S23) over 7 years (2001–2007) were processed and extracted with Windisp 5.1 from 10-day NDVI maximum value composite images. At the monthly time step, only 12 subcatchments had weak positive correlation (0.23–0.42) at 5% significance level and the rest were not significantly correlated. Incorporating a 1-month lag effect increased the correlation coefficients between the two variables (0.28–0.68) with 17 subcatchments being significantly correlated at the designated level. The topography within the catchment was found to play a defining role for NDVI values. S15, S16, S18 and S20, the subcatchments covering the Mount Ruwenzori characterized by elevations up to 4862 m above sea level, consistently recorded the lowest values of NDVI over time and no significant correlation could be established between rainfall and NDVI.