起伏地形下我国太阳散射辐射分布式模拟

基于1km×1km分辨率的数字高程模型(DEM)数据,考虑了地形因子对太阳散射辐射的影响,改进了开阔度的计算模型,确定了我国气候平均情况下月散射系数的空间分布,实现了实际起伏地形下我国太阳散射辐射的分布式模拟,计算了我国范围内1km×1km分辨率1-12月气候平均太阳散射辐射的空间分布.结果表明:局地地形对太阳散射辐射空间分布的影响比较明显;模拟结果可靠,可进行大数据量处理,适用于遥感图像处理、地理信息系统等数据处理平台.     

起伏地形下四川省太阳直接辐射时空分布特征

利用四川省159个地面常规气象观测站及周边9个太阳辐射站观测资料,基于数字高程模型(DEM)数据,考虑坡度、坡向和地形遮蔽作用的影响,研制起伏地形下太阳直接辐射分布式模型。结合四川省90 m×90 m分辨率的DEM数据,分析起伏地形下四川省太阳直接辐射空间分布特征和时间变化趋势。结果表明:(1)四川省太阳直接辐射纬向分布不明显,受海拔高度、日照百分率、局地地形影响较大;(2)四川省太阳直接辐射年总量东部盆地较低,1 300.0 MJ·m-2,川西高原及攀西地区较大,在1 900.0~3 486.9 MJ·m-2之间;(3)四川省太阳直接辐射时间变化明显,川东盆地太阳直接辐射1 000.0 MJ·m-2的地区有增加趋势,川西地区2 800.0 MJ·m-2的区域在减小,四川省宜宾、都江堰、南充、马尔康太阳直接辐射年总量、1月、7月气候倾向率均0。     

基于DEM的复杂地形下太阳散射辐射分布式模拟——以贵州高原为例

由于坡度、坡向和地形之间相互遮蔽等局地地形因子的影响,确定实际复杂地形下太阳散射辐射是比较困难的.本文在前人研究的基础上,对以前的模型进行了一些改进,考虑了坡度、坡向和地形相互遮蔽作用对复杂地形下天文辐射的影响,基于数字高程模型(DEM)数据,研制了以复杂地形下天文辐射为起始数据的复杂地形下太阳散射辐射的分布式模型,在模型中还考虑了散射辐射的各向异性.以地形复杂的贵州高原为例,应用100 m×100 m分辨率的DEM数据及气象站常规观测气象资料,计算了贵州高原复杂地形下各月及年的太阳散射辐射精细空间分布.结果表明:(1)局地地形因子(如坡度、坡向和地形遮蔽)对贵州高原复杂地形下太阳散射辐射的空间分布影响较大,随着地形的起伏变化,太阳散射辐射的空间分布明显不同,纬向分布特征不明显.(2)对于太阳散射辐射而言,地形对其的影响仍然很大,在太阳散射辐射计算时也是不容忽视的.     

起伏地形下深圳市天文辐射的空间分布

以起伏地形下天文辐射的分布模型为基础,借助地理信息系统（GhS）处理数据,将深圳市1：250,000DEM数据作为地形的综合反映,模拟计算了起伏地形下（坡度、坡向和地形遮蔽）深圳市天文辐射,分析了起伏地形下深圳市天文辐射的分布规律,完成了深圳市100m×100m分辨率的各月及全年的天文辐射的空间制图。结果表明：对于局部地形起伏引起的天文辐射的变化。秋、冬季最为显著,向阳坡和背阴坡的极值差异较大,这和太阳高度角随着季节变化而冬半年相对较低、夏半年相对较高有关。坡度对天文辐射的影响在冬半年较大,随着坡度的增大,辐射差值增大的幅度呈递减趋势。     

基于DEM的广东山地高分辨率太阳辐射模拟研究

对已有太阳总辐射模型进行改进,并利用MODIS产品取代地表反照率经验公式,在更小积分步长内进行计算,开发了复杂地形下太阳总辐射高分辨率模拟模型。应用1 km分辨率的数字高程模型(DEM)数据以及常规气象资料,对广东2个辐射站的太阳总辐射进行验证。结果表明:(1) 所建立的分布式太阳辐射模拟模型能准确模拟广东省太阳总辐射分布状况,模拟值与实测值吻合较好;(2) 研究区域四季辐射中的夏季辐射最高,秋季次之,冬季最低,年均太阳总辐射为2 893～4 655 J/(m2?s),平均值为4 167 J/(m2?s);(3) 大范围区域而言,广东夏、秋、冬季太阳总辐射的纬向分布十分显著,但从局地区域看,地形是影响太阳总辐射的主导因子。太阳总辐射是各种作物最基本也是最重要的能量来源,在小网格尺度上进行的精细化太阳总辐射计算可为多种作物的布局和种植规划提供重要的基础数据。      

起伏地形下河南省太阳散射辐射的分布式模拟

利用河南省及周边145个气象站1961－2000年常规气象观测资料和河南省1:25万DEM数据,充分考虑起伏地形下太阳散射辐射的天空因素与地面因素后,基于分布式开阔度模型和天文辐射模型,实现了起伏地形下河南省太阳散射辐射的分布式模拟.计算了100m×100 m分辨率下河南省1－12月气候平均太阳散射辐射及多年平均年散射辐射总量的空间分布.结果表明:在充分考虑经验系数的时空分布特征后,模拟精度有了进一步提高.与郑州站的观测资料对比验证表明,模拟精度较高,年平均绝对误差为3.06 MJ·m-2,年平均相对误差为1.67％;局地地形对太阳散射辐射的影响比较明显;通过个例年验证对模型性能和模拟结果进行考察,年平均相对误差不足11％.综上表明模型的时空模拟性能良好.     

山地天文辐射的地形影响与空间尺度效应研究

基于1∶25×104数字高程模型数据,依据起伏地形下天文辐射分布式模型算法,研究了陕西山地天文辐射空间分布规律,详细分析了地形因子对天文辐射的影响规律;同时,从不同的DEM分辨率和不同地貌类型两个方面探讨了天文辐射的空间尺度效应。结果表明:陕西天文辐射总量随着纬度的升高呈由南向北降低的趋势;局地地形因子对天文辐射的影响随季节、纬度、坡度及坡向等因素而变;同时山地天文辐射的空间尺度效应在地势起伏较大的山区和高原地区表现尤为明显。     

模式不同分辨率对新疆达坂城—小草湖风区地面风场模拟结果的分析

使用非静力平衡中尺度MM5V3模式及NCEP/GFS 1°×1°再分析资料,对新疆达坂城-小草湖风区2006年4～9月10m高度的风况进行了3km×3km与1km×1km的模拟试验。结果表明:(1)3km与1km分辨率模拟的平均风速的大小分布特征整体一致,仅在复杂地形处以及风速大小值中心区域的强弱上存在细微差别,1km高分辨率对风速大小区域分布的模拟比3km分辨率更细致,且风速大、小值之间的变化梯度更明显。(2)3km与1km分辨率的模拟试验均较真实地反映了地形比较平坦、地貌比较单一区域的日平均风速与逐时平均风速的变化特征,但分辨率的提高并不能完全减小模拟误差。对于地形、地貌特征相对复杂区域而言,水平分辨率的提高,反而会加大模拟偏差。(3)两种分辨率的模拟误差在7、8月最大,4、9月份最小;对逐时平均风速的模拟误差均与距初始场时刻的长短无关。(4)两种分辨率对柴窝堡站点的模拟偏差过大,这很可能与模式中定义的水体、植被等参数与实际相距过大,以及该处地形陡峭,恰好位于绿洲与水体之间的荒漠过渡带有关。     

复杂地形下黑河流域的太阳辐射计算

基于数字高程模型(DEM)数据,在充分考虑了地形因子对太阳直接辐射和散射辐射的影响后,实际计算了起伏地形下黑河流域的太阳辐射。在忽略地表和大气之间的多次反射后,地表太阳总辐射计为三项:按起伏坡面上实际入射角考虑的太阳直接辐射、经过下垫面天空视角因子订正的坡面天空散射辐射和考虑周围地形反射效应的附加辐射。计算结果表明:局地地形起伏对太阳直接辐射、总辐射空间分布的影响非常强烈,使得复杂地形下不同坡向间总辐射和直接辐射平均计算差额十分显著,且太阳天顶角从较小增大至中等大小时,这两种平均计算差额均加大一倍多;在较小和中等大小太阳天顶角下,不同坡向间总辐射平均计算差额,均较相同条件下直接辐射平均计算差额为小,这是因为总辐射还包括了天空漫射和邻近地形反射辐射因子,这两个因子和坡面上太阳入射方位的变化共同影响地表入射太阳辐射;起伏地形主要使得太阳辐射在局地区域内背阴、向阳坡向间发生显著的重新分配。因此,在复杂地形地区进行太阳辐射计算时必须考虑地形的影响。     

不同分辨率地形数据对黑河流域模拟结果的对比分析

陆面模式和分布式水文模式都要求细致的地面要素场描述,其中地形数据是一个重要的因子。目前,美国地质调查局(USGS)制作的全球30″地形数据已广泛应用于陆面模式和分布式水文/生态模式中,这套全球地形数据可以比较准确地描述地形的大尺度分布,然而若描写复杂地形的小尺度分布细节则略显不足。在黑河流域,我们有高分辨率的30 m地形数据,这里首先对黑河流域范围的该两套数据进行了比较;为评估黑河流域超高分辨率地形数据在大气模式中对气象要素的模拟能力,在中尺度大气模式(MM5)中分别使用黑河流域超高分辨率地形数据和全球30″地形数据,对黑河流域2003年6月大气要素场进行模拟。模拟结果显示,无论从要素场本身与地形空间分布的相关性还是要素变化的空间分布与地形变化的相关性看,地形对气压场、土壤和大气温度场以及大气可降水量场都有着重要影响,地形分布对月总降水量的空间分布也有一定影响。黑河数据对气温以及风向的模拟能力好于USGS数据,对降水过程模拟的改善程度不是很明显。     

起伏地形下浙江省散射辐射时空分异规律模拟

结合影响起伏地形下太阳散射辐射的天空因素与地面因素,通过基于数字高程模型（DEM）数据的起伏地形下天文辐射模型和地形开阔度模型,综合考虑地面因素对散射辐射的影响;基于常规地面气象站观测资料建立的水平面散射辐射模型,考虑天空因素对散射辐射的影响;建立了起伏地形下浙江省散射辐射分布式估算模型;逐月计算了浙江省散射辐射（100m×100m）的空间分布。结果表明：散射分量分布与地理地形因子、季风影响、大气透明程度有关,由高纬向低纬逐渐增加;季节分布特点为,夏季〉春季〉秋季〉冬季;坡度、坡向对散射辐射的分布影响小,但辐射值与开阔度呈正相关,各季辐射最大值分布在开阔度大处,最小值在开阔度最小处,不同季节有所伸缩。计算结果可以为气候变化和环境资源研究提供基础数据。     

Resolution effects on regional climate model simulations of seasonal precipitation over Europe

We analyze a set of nine regional climate model simulations for the period 1961–2000 performed at 25 and 50 km horizontal grid spacing over a European domain in order to determine the effects of horizontal resolution on the simulation of precipitation. All of the models represent the seasonal mean spatial patterns and amount of precipitation fairly well. Most models exhibit a tendency to over-predict precipitation, resulting in a domain-average total bias for the ensemble mean of about 20% in winter (DJF) and less than 10% in summer (JJA) at both resolutions, although this bias could be artificially enhanced by the lack of a gauge correction in the observations. A majority of the models show increased precipitation at 25 km relative to 50 km over the oceans and inland seas in DJF, JJA, and ANN (annual average), although the response is strongest during JJA. The ratio of convective precipitation to total precipitation decreases over land for most models at 25 km. In addition, there is an increase in interannual variability in many of the models at 25 km grid spacing. Comparison with gridded observations indicates that a majority of models show improved skill in simulating both the spatial pattern and temporal evolution of precipitation at 25 km compared to 50 km during the summer months, but not in winter or on an annual mean basis. Model skill at higher resolution in simulating the spatial and temporal character of seasonal precipitation is found especially for Great Britain. This geographic dependence of the increased skill suggests that observed data of sufficient density are necessary to capture fine-scale climate signals. As climate models increase their horizontal resolution, it is thus a key priority to produce high quality fine scale observations for model evaluation.     

贵州高原起伏地形下日照时间的时空分布

由于坡度、坡向和地形之间相互遮蔽等局地地形因子的影响, 实际起伏地形下的日照时间与水平面上的日照时间有一定差异。该文建立了一种基于数字高程模型 (DEM) 的起伏地形下日照时间的模拟方法, 计算了起伏地形下贵州高原100 m×100 m分辨率日照时间的时空分布。结果表明:坡度、坡向、地形遮蔽对日照时间的影响较大, 实际起伏地形下日照时间的空间分布具有明显地域特征。1月太阳高度角较低, 坡度、坡向的作用非常明显, 地形遮蔽面积较大, 日照时间的空间差异较多, 日照时间为16~142 h, 最大值约为最小值9倍; 7月太阳高度角较高, 地形遮蔽面积相对较小, 日照时间的空间差异相对较少, 日照时间为133~210 h, 最大值为最小值1.6倍, 但由于7月日照时间相对较多, 局地地形对日照时间影响仍明显。4月、10月日照时间及其变化幅度介于1月和7月之间。     

Searching for Added Value in Simulating Climate Extremes with a High-Resolution Regional Climate Model over Western Canada. II: Basin-Scale Results

We evaluate the capacity of a regional climate model to simulate the statistics of extreme events, and also examine the effect of differing horizontal resolution, at the scale of individual hydrological basins in the topographically complex province of British Columbia, Canada. Two climate simulations of western Canada (WCan) were conducted with the Canadian Regional Climate Model (version 4) at 15 (CRCM15) and 45?km (CRCM45) horizontal resolution driven at the lateral boundaries by global reanalysis over the period 1973–1995. The simulations were evaluated with ANUSPLIN, a daily observational gridded surface temperature and precipitation product and with meteorological data recorded at 28 stations within the upper Peace, Nechako, and upper Columbia River basins. In this work, we focus largely on a comparison of the skill of each model configuration in simulating the 90th percentile of daily precipitation (PR90). The companion paper describes the results for a wider range of temperature and precipitation extremes over the entire WCan domain.

Over all three watersheds, both simulations exhibit cold biases compared with observations, with the bias exacerbated at higher resolution. Although both simulations generally display wet biases in median precipitation, CRCM15 features a reduced bias in PR90 in all three basins in summer and throughout the year in the upper Columbia River basin. However, the higher resolution model is inferior to CRCM45 with respect to rarer heavy precipitation events and also displays high spatial variability and lower spatial correlations with ANUSPLIN compared with the coarser resolution model. A reduction in the range of PR90 biases over the upper Columbia basin is noted when the 15?km results are averaged to the 45?km grid. This improvement is partly attributable to the averaging of errors between different elevation data used in the gridded observations and CRCM, but the sensitivity of CRCM15 to resolved topography is also clear from spatial maps of seasonal extremes. At the station scale, modest but systematic reductions in the bias of PR90 relative to ANUSPLIN are again found when the CRCM15 results are averaged to the 45?km grid. Furthermore, the annual cycle of inter-station spatial variance in the upper Columbia River basin is well reproduced by CRCM15 but not by ANUSPLIN or CRCM45. The former result highlights the beneficial effect of spatial averaging of small-scale climate variability, whereas the latter is evidently a demonstration of the added value at high resolution vis-à-vis the improved simulation of precipitation at the resolution limit of the model.     

Spatiotemporal modeling of monthly soil temperature using artificial neural networks

Soil temperature data are critical for understanding land–atmosphere interactions. However, in many cases, they are limited at both spatial and temporal scales. In the current study, an attempt was made to predict monthly mean soil temperature at a depth of 10 cm using artificial neural networks (ANNs) over a large region with complex terrain. Gridded independent variables, including latitude, longitude, elevation, topographic wetness index, and normalized difference vegetation index, were derived from a digital elevation model and remote sensing images with a resolution of 1 km. The good performance and robustness of the proposed ANNs were demonstrated by comparisons with multiple linear regressions. On average, the developed ANNs presented a relative improvement of about 44 % in root mean square error, 70 % in mean absolute percentage error, and 18 % in coefficient of determination over classical linear models. The proposed ANN models were then applied to predict soil temperatures at unsampled locations across the study area. Spatiotemporal variability of soil temperature was investigated based on the obtained database. Future work will be needed to test the applicability of ANNs for estimating soil temperature at finer scales.     

Effects of complex terrain on net surface longwave radiation in China

Net surface longwave radiation (NSLR) is one of key meteorological factors and is strongly influenced by cloud cover, surface temperature, humidity, and local micrometeorological conditions as well as terrain conditions. Realistically estimating NSLR is vitally important for understanding surface radiation balance and investigating micrometeorological factors of air pollution dispersion, especially in regions with complicated terrain. In this study, we proposed a distributed model for estimating NSLR by considering effects of complex local terrain conditions in China. Meteorological data (including mean temperature, relative humidity, and sunshine percentage) and observed NSLR data from 1993 to 2001 together with the digital elevation model data were used to parametrize the model and account for the effects of atmospheric factors and surface terrain factors according to the isotropic principle. The monthly NSLR during 1961–2000 was estimated at a spatial resolution of 1 km. Topographic analysis suggests that the distribution characteristics of NSLR with elevation or slope are consistent with those of field observations. In particular, the estimated NSLR is favorably comparable with site-level observations on the Tibetan Plateau (average relative error < 11%). Our results indicate that this model can describe microscale distribution features in mountainous areas in detail and that this improved approach can be used for NSLR spatial estimation in other regions with complicated terrain.     

基于TRMM卫星的近10a甘肃临夏降水变化特征

基于2001~2010年TRMM 3B43降水资料和数字高程模型（DEM）数据,采用回归模型＋残差的方法,对甘肃临夏回族自治州近10 a的TRMM 3B43降水数据进行降尺度运算,并结合研究区6个雨量站的观测值,对TRMM 3B43降尺度结果进行精度检验,在此基础上定量研究了临夏回族自治州近10 a的降水量时空变化特征。结果表明：TRMM 3B43降尺度降水量数据整体上具有一定的可信度,但比地面台站的观测值偏小;甘肃临夏州年降水量呈现出由西南向东北递减的趋势,且降水量随着海拔高度的升高而逐渐增加,两者相关系数为0.82;年内降水主要集中在5~9月,基本占全年降水量的70%以上,其中6月降水量最大,12月降水量最小。     

New Method for Estimating Daily Global Solar Radiation over Sloped Topography in China

A new scheme for the estimation of daily global solar radiation over sloped topography in China is developed based on the Iqbal model C and MODIS cloud fraction. The effects of topography are determined using a digital elevation model. The scheme is tested using observations of solar radiation at 98 stations in China, and the results show that the mean absolute bias error is 1.51 MJ m~(-2) d~(-1) and the mean relative absolute bias error is 10.57%. Based on calculations using this scheme,the distribution of daily global solar radiation over slopes in China on four days in the middle of each season(15 January,15 April, 15 July and 15 October 2003) at a spatial resolution of 1 km × 1 km are analyzed. To investigate the effects of topography on global solar radiation, the results determined in four mountains areas(Tianshan, Kunlun Mountains, Qinling,and Nanling) are discussed, and the typical characteristics of solar radiation over sloped surfaces revealed. In general, the new scheme can produce reasonable characteristics of solar radiation distribution at a high spatial resolution in mountain areas,which will be useful in analyses of mountain climate and planning for agricultural production.