中国三种太阳辐射起始数据分布式模拟

天文辐射、干洁大气总辐射和湿洁大气总辐射是太阳辐射模拟的3种重要起始数据。依托Iqbal Model C和起伏地形下干/湿洁大气总辐射模型,实现了水平面和起伏地形下干/湿洁大气总辐射分布式模拟。以DEM数据作为地形的综合反映,结合常规气象资料,计算了水平面和起伏地形下中国1 km×1 km分辨率日天文辐射量、干洁大气总辐射量、湿洁大气总辐射量的空间分布,并对3种太阳辐射起始数据的时空分布特征做了对比分析。结果表明:3种辐射量均遵循随纬向变化的宏观分布规律;水平面干/湿洁大气总辐射量的分布体现了海拔的影响,水平面湿洁大气总辐射量的分布还体现了水汽分布的影响;起伏地形下的3种辐射量能很好的体现坡度、坡向和地形之间相互遮蔽等局部地形特征对辐射量的影响;以干/湿洁大气总辐射作为起始数据,将有助于提高太阳总辐射的模拟精度。     

基于GIS的起伏地形下天文辐射分布式模型——以贵州高原为例

天文辐射是辐射计算、太阳能资源评估及其他相关研究领域重要的起始参量,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,使实际起伏地形下获得的天文辐射与水平面上获得的天文辐射有一定差异。确定实际起伏地形下天文辐射是比较困难的。应用数字高程模型(DEM)数据和地理信息系统(G IS),建立起伏地形下天文辐射分布式计算模型,计算了起伏地形下贵州高原100 m×100 m分辨率天文辐射精细空间分布,分析了局地地形因子对起伏地形下天文辐射的影响。结果表明:(1)贵州高原起伏地形下天文辐射的空间分布具有明显的地域分布特征。(2)贵州高原起伏地形下天文辐射年总量平均为481.7~13 041.8 M J/m2,1月、7月天文辐射分别为0.0~1 244.7 M J/m2、0.0~1 264.8 M J/m2。(3)局地地形因子对起伏地形下天文辐射空间分布的影响随季节和纬度变化,虽然坡度、坡向和地形遮蔽对天文辐射的影响,在太阳高度角较低的1月比太阳高度角较高的7月相对较大,但因为7月水平面获得的天文辐射的强度相对较大,7月局地地形对天文辐射的影响依然显著。因此,贵州高原起伏地形对天文辐射的影响是不容忽视的。     

贵州高原复杂地形下太阳总辐射精细空间分布

海拔、坡度、坡向以及周围地形遮蔽作用,造成山区各部位接受到的太阳辐射能有很大差异. 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总辐射的分布式模型,在模型中还考虑了散射辐射的各向异性及坡地反射辐射对复杂地形下太阳总辐射的影响.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100 m×100 m分辨率的复杂地形下太阳总辐射.结果表明:(1) 局地地形因子如坡度、坡向、地形遮蔽等对太阳总辐射影响显著,地形对复杂地形下太阳总辐射的影响是不容忽视的.(2)在缺乏复杂地形下坡面考察资料的情况下,建立以常规气象站观测资料为主的物理经验统计模型是实现细网格辐射资源计算的可行途径.     

起伏地形下黄河流域太阳直接辐射分布式模拟

基于数字高程模型(DEM)数据和气象站观测资料建立了起伏地形下太阳直接辐射分布式计算模型,模型充分考虑了地形因子(坡向、坡度、地形相互遮蔽)对起伏地形下太阳直接辐射空间分布的影响;以1km×1km分辨率的DEM数据作为地形的综合反映,计算了起伏地形下黄河流域1km×1km分辨率太阳直接辐射的空间分布;深入分析了起伏地形下太阳直接辐射受地理、地形因子影响的变化规律。结果表明:受地形起伏和坡向、坡度等局地地形因子的影响,山区年太阳直接辐射量的空间差异比较明显,向阳山坡(偏南坡)的年直接辐射量明显高于背阴山坡(偏北坡)     

起伏地形下黄河流域太阳直接辐射分布式模式

基于数字高程模型(DEM)数据和气象站观测资料建立了起伏地形下太阳直接辐射分布式计算模型,模型充分考虑了地形因子(坡向、坡度、地形相互遮蔽)对起伏地形下太阳直接辐射空间分布的影响;以1km×1km分辨率的DEM数据作为地形的综合反映,计算了起伏地形下黄河流域1km×1km分辨率太阳直接辐射的空间分布;深入分析了起伏地形下太阳直接辐射受地理、地形因子影响的变化规律.结果表明受地形起伏和坡向、坡度等局地地形因子的影响,山区年太阳直接辐射量的空间差异比较明显,向阳山坡(偏南坡)的年直接辐射量明显高于背阴山坡(偏北坡).     

复杂地形下长江流域太阳总辐射的分布式模拟

利用长江流域气象站1960-2005年的观测资料(包括常规气象站点资料和辐射站点资料)、NOAA-AVHRR遥感数据(反演地表反照率),以1km×1km的数字高程模型(DEM)反映地形状况的主要数据,通过基于DEM数据的起伏地形下天文辐射模型和地形开阔度模型,分别建立了长江流域太阳直接辐射、散射辐射和地形反射辐射分布式模型,实现了长江流域太阳总辐射模拟,并对总辐射模拟结果进行了时空分布规律分析和对其受季节、纬度、地形因子(高度、坡度和坡向等)影响的局部规律分析,以及模拟结果的误差分析和站点验证分析。结果显示:太阳总辐射在季节上受影响的程度依次是春季>冬季>夏季>秋季;随着高度、坡度、纬度的增加,太阳总辐射受坡向影响的程度呈增强趋势,从坡向上看,向阳山坡(偏南坡)对太阳总辐射量明显高于背阴坡(偏北坡)。模拟的平均绝对误差为13.04177MJm^-2,相对误差平均值3.655%,用站点验证方法显示:模拟绝对误差为22.667MJm^-2,相对误差为4.867%。     

基于地形的福建省太阳辐射模拟计算及评估

取分布式模拟方法,利用福建省69个气象站1971—2007年日照资料及100 m×100 m分辨率的高程数据,计算了福建省范围内历年1—12月的太阳辐射量.结果表明,福建省年太阳总辐射主要在3 800~5 300 MJ/m2之间,年太阳直接辐射在1 800~2 800 MJ/m2之间;月太阳辐射介于230~590 MJ/m2之间,其中6—9月为一年中辐射较高的4个月份.太阳辐射的高值区主要位于福建东南部的莆田、泉州、厦门、漳州4市的沿海一带,年太阳总辐射超过4 500 MJ/m2,年太阳直接辐射超过2 100 MJ/m2.此外,受地形及地表特征的影响,位于福建北部的南平市的部分地区太阳辐射也相对较高.     

基于DEM的黄河流域天文辐射空间分布

基于1 km×1 km分辨率的数字高程模型(DEM) 数据,利用建立的起伏地形下天文辐射分布式计算模型,计算了黄河流域1 km×1 km分辨率各月天文辐射的空间分布。结果表明:局部地形对黄河流域年和四季天文辐射的空间分布影响明显;在太阳高度角较低的冬季,地理和地形因子对天文辐射的影响相当强烈,山区天文辐射的空间差异大,1月份向阳山坡(偏南坡) 天文辐射可为背阴山坡(偏北坡) 的2~3倍,极端天文辐射的差异可达10倍以上;而在太阳高度角较高的夏季,天文辐射空间差异较小,7月份不同地形极端天文辐射的差异仅在16%左右;四季中,地形对天文辐射影响的程度为冬季>秋季>春季>夏季。     

复杂地形任意天气情形下太阳直接辐射量模拟

以太阳辐射传输参数化模型为基础,结合MODIS影像两次白天的云产品和水汽产品及DEM,构建了复杂地形任意天气情形下每日太阳直接辐射量模型。选取代表不同气候类型与地形起伏状况的3个典型站点（拉萨、北京、额济纳旗）,以2007年每日实测值对模拟结果进行了验证,其相关系数分别为0.77、0.77和0.85。研究表明:有云天气下,云是影响地表太阳直接辐射数量和空间分布的主要因子;模型对时间步长不敏感。引起误差的原因主要是MODIS云产品的时空分辨率较低以及云的3D效应导致模拟的困难,对地形起伏较大地区,小比例尺的DEM也会导致较大的误差,同时实测值与模拟值的空间尺度不匹配也引起了一定误差。     

西藏高原暖季(5-10月)大气浑浊度及消光特性的初探

青藏高原以其平均海拔高度(约4000米)最高闻名于世。由于海拔高度的影响,空气稀薄,大气干洁,太阳辐射透过大气损失和被吸收的也少,因此,这里的太阳年总辐射量高居全国之冠,年总辐射量多在140—190千卡/厘米~2,比起我国东部平原地区多60—80     

复杂地形对长江流域太阳总辐射的影响(英文)

Global solar radiation(GSR) is the most direct source and form of global energy, and calculation of its quantity is highly complex due to influences of local topography and terrain inter-shielding. Digital elevation model(DEM) data as a representation of the complex terrain and multiplicity condition produces a series of topographic factors(e.g. slope, aspect, etc.). Based on 1 km resolution DEM data, meteorological observations and NOAA-AVHRR remote sensing data, a distributed model for the calculation of GSR over rugged terrain within the Yangtze River Basin has been developed. The overarching model permits calculation of astronomical solar radiation for rugged topography and comprises a distributed direct solar radiation model, a distributed diffuse radiation model and a distributed terrain reflectance radiation model. Using the developed model, a quantitative simulation of the GSR space distribution and visualization has been undertaken, with results subsequently analyzed with respect to locality and terrain. Analyses suggest that GSR magnitude is seasonally affected, while the degree of influence was found to increase in concurrence with increasing altitude. Moreover, GSR magnitude exhibited clear spatial variation with respect to the dominant local aspect; GSR values associated with the sunny southern slopes were significantly greater than those associated with shaded slopes. Error analysis indicates a mean absolute error of 12.983 MJm-2 and a mean relative error of 3.608%, while the results based on a site authentication procedure display an absolute error of 22.621 MJm-2 and a relative error of 4.626%.     

Influence of complex topography on global solar radiation in the Yangtze River Basin

Global solar radiation（GSR） is the most direct source and form of global energy, and calculation of its quantity is highly complex due to influences of local topography and terrain inter-shielding. Digital elevation model（DEM） data as a representation of the complex terrain and multiplicity condition produces a series of topographic factors（e.g. slope, aspect, etc.）. Based on 1 km resolution DEM data, meteorological observations and NOAA-AVHRR remote sensing data, a distributed model for the calculation of GSR over rugged terrain within the Yangtze River Basin has been developed. The overarching model permits calculation of astronomical solar radiation for rugged topography and comprises a distributed direct solar radiation model, a distributed diffuse radiation model and a distributed terrain reflectance radiation model. Using the developed model, a quantitative simulation of the GSR space distribution and visualization has been undertaken, with results subsequently analyzed with respect to locality and terrain. Analyses suggest that GSR magnitude is seasonally affected, while the degree of influence was found to increase in concurrence with increasing altitude. Moreover, GSR magnitude exhibited clear spatial variation with respect to the dominant local aspect; GSR values associated with the sunny southern slopes were significantly greater than those associated with shaded slopes. Error analysis indicates a mean absolute error of 12.983 MJm-2 and a mean relative error of 3.608%, while the results based on a site authentication procedure display an absolute error of 22.621 MJm-2 and a relative error of 4.626%.     

起伏地形下黄河流域太阳直接辐射分布式模拟

1 Introduction Directsolarradiation (DSR)isthe key com ponentofthe globalradiation reaching the Earth.For the influence of terrain factors,calculation of DSR quantity of rugged terrain is considerably com plex (Oliphantetal.,2003). The solarradiation quan…     

晴空下山区太阳辐射模拟

由于太阳辐射在山区的空间分布情况较为复杂,在Arcgis,Envi和C++基础上,提出了一个晴空条件下估算山区太阳辐射分布的模型。在借鉴国内外太阳辐射研究成果基础上充分考虑了地形因素和大气状况,利用Modtran大气辐射传输模型、DEM和Modis反照率数据建立了山区太阳辐射计算模型。以黑河上游山区为试验区,利用该模型模拟得到了黑河上游山区的太阳辐射,分析了坡度、坡向、海拔对太阳辐射空间分布的影响,并利用实测值对模型进行了验证,结果表明：该模型可较好地反映研究区内山区太阳总辐射的分布,可用于山区太阳辐射的估算。     

基于DEM的黄河流域天文辐射空间分布

Based on the developed distributed model for calculating astronomical solar radiation (ASR), monthly ASR with a resolution of 1 km× 1 km for the rugged terrains of Yellow River Basin was calculated, with DEM data as the general characterization of terrain. This model gives an all-sided consideration on factors that influence the ASR. Results suggest that (1) Annual ASR has a progressive decrease trend from south to north; (2) the magnitude order of seasonal ASR is: summer＞spring＞autumn＞winter; (3) topographical factors have robust effect on the spatial distribution of ASR, particularly in winter when a lower sun elevation angle exists; (4) the ASR of slopes with a sunny exposure is generally 2 or 3 times that of slopes with a shading exposure and the extreme difference of ASR for different terrains is over 10 times in January; (5) the spatial differences of ASR are relatively small in summer when a higher sun elevation angle exists and the extremedifference of ASR for different terrains is only 16% in July; and (6) the sequence of topographical influence strength is: winter＞autumn＞spring＞summer.     

Simulation of astronomical solar radiation over Yellow River Basin based on DEM

1IntroductionDistributed watershed hydrological model has become one of the hot topics in hydrology for its predominance in reflecting the influence of the spatial distributed features of terrains on hydrological processes (Wan etal., 2001; Abbott etal., 1986; Beven etal., 1992). However its demands on the spatio-temporal changeful surface elements such as solar radiation, precipitation, temperature etc. are strict. Being the limitations of observation techniques, data availability and study …     

Simulation of astronomical solar radiation over Yellow River Basin based on DEM

Based on the developed distributed model for calculating astronomical solar radiation (ASR), monthly ASR with a resolution of 1 km×1 km for the rugged terrains of Yellow River Basin was calculated, with DEM data as the general characterization of terrain. This model gives an all-sided consideration on factors that influence the ASR. Results suggest that (1) Annual ASR has a progressive decrease trend from south to north; (2) the magnitude order of seasonal ASR is: summer>spring>autumn>winter; (3) topographical factors have robust effect on the spatial distribution of ASR, particularly in winter when a lower sun elevation angle exists; (4) the ASR of slopes with a sunny exposure is generally 2 or 3 times that of slopes with a shading exposure and the extreme difference of ASR for different terrains is over 10 times in January; (5) the spatial differences of ASR are relatively small in summer when a higher sun elevation angle exists and the extreme difference of ASR for different terrains is only 16% in July; and (6) the sequence of topographical influence strength is: winter>autumn>spring>summer.