Global solar radiation (GSR) is an essential physical quantity for agricultural management and designing infrastructures. Because GSR has often been modeled as a function of sunshine duration (SD) and day length for a...Global solar radiation (GSR) is an essential physical quantity for agricultural management and designing infrastructures. Because GSR has often been modeled as a function of sunshine duration (SD) and day length for a given set of locations and calendar days, analyzing interannual trends in GSR and SD is important to evaluate, predict or regulate the cycles of energy and water between geosphere and atmosphere. This study aimed to exemplify interannual trends in GSR and SD, which had been recorded from 2001 to 2022 in 40 meteorological stations in Japan, and validate the applicability of an SD-based model to the evaluation of GSR. Both the measured GSR and SD had increased in many of the stations in the study period with averaged rates of 0.252 [W·m−2·y−1] and 0.015 [h·d−1·y−1], respectively. The offset and the slope of the SD-based model were estimated by fitting the model to the measured data sets and were found to have been almost constant with the averages of 0.201[-] and 0.566[-], respectively, indicating that characteristics of the SD-GSR relation had not varied for the 22-year period and that the model and its parameter set can be stationarily applicable to the analyses and predictions of GSR in recent years. The stable trends in both parameters also implied that the upward trend in SD can be a main explanatory factor for that in the measured GSR. The upward trend in SD had coincided with the increase in the frequency of heavy-shortened rains, suggesting that the time period of each rainfall event had gradually decreased, which may be attributable to the obtained upward trend in SD. Further studies are required to clarify if there is some cause-effect relation between the changes in rainfall patterns and the standard level of solar radiation reaching the land surface.展开更多
以北京市为研究区域,联合使用光学遥感数据和雷达数据,对植被覆盖区地表土壤水分进行反演研究。在利用同期光学数据提取出归一化水分指数(normalized differential water index,NDWI)之后,利用water-cloud模型去除植被层在土壤水分后向...以北京市为研究区域,联合使用光学遥感数据和雷达数据,对植被覆盖区地表土壤水分进行反演研究。在利用同期光学数据提取出归一化水分指数(normalized differential water index,NDWI)之后,利用water-cloud模型去除植被层在土壤水分后向散射中的贡献,然后考虑到地表粗糙度,在构建后向散射数据库的基础上分别利用HH和HV极化方式的后向散射系数构建土壤水分反演模型,并对反演结果进行对比研究。结果表明,采用HH极化方式反演土壤水分的均方根误差为0.044,相对误差为15.5%;采用HV极化方式反演土壤水分的均方根误差为0.057,相对误差为20.3%;相比而言,HH极化的反演效果更好。展开更多
利用毕节2010-2019年观测资料,分析不同天气现象下日最高气温特征,建立高温模型,并对近5 a 24 h高温进行检验,得出如下结论:(1)毕节高温日变化在夏季最稳定,春季波动最大。气温日较差晴天最大,阴天最小,多云时略大于阴间多云。(2)毕节8...利用毕节2010-2019年观测资料,分析不同天气现象下日最高气温特征,建立高温模型,并对近5 a 24 h高温进行检验,得出如下结论:(1)毕节高温日变化在夏季最稳定,春季波动最大。气温日较差晴天最大,阴天最小,多云时略大于阴间多云。(2)毕节8~10成云出现频率高达65.7%,夏季晴天频率波动大,春、夏季多云频率较高,且按天气现象分类统计月平均高温时,其峰值均出现在7月。(3) 24 h高温预报准确率月、季变化特征明显,夏季准确率最高,较最低的冬季高出21.4%,在区别天气现象的情况下,阴雨天时预报准确率最高,多云时最低,其中12月多云时最低为25%。(4)回归模型分析发现不同季节同种天气现象24 h高温预报影响因子权重差异明显,日照时数和平均本站气压对模型影响程度较高。不同季节晴天影响因子差异最大,拟合效果最好时段在夏季,平均估计误差为1.2℃,估计误差最大在冬季,平均估计误差为1.7℃。展开更多
Sunshine duration（SD） is strongly correlated with solar radiation, and is most widely used to estimate the latter. This study builds a remote sensing model on a 100 m × 100 m spatial resolution to estimate SD f...Sunshine duration（SD） is strongly correlated with solar radiation, and is most widely used to estimate the latter. This study builds a remote sensing model on a 100 m × 100 m spatial resolution to estimate SD for the Ningxia Hui Autonomous Region, China. Digital elevation model（DEM） data are employed to reflect topography, and moderate-resolution imaging spectroradiometer（MODIS） cloud products（Aqua MYD06-L2 and Terra MOD06-L2） are used to estimate sunshine percentage. Based on the terrain（e.g.,slope, aspect, and terrain shadowing degree） and the atmospheric conditions（e.g., air molecules, aerosols,moisture, cloud cover, and cloud types）, observation data from weather stations are also incorporated into the model. Verification results indicate that the model simulations match reasonably with the observations,with the average relative error of the total daily SD being 2.21%. Further data analysis reveals that the variation of the estimated SD is consistent with that of the maximum possible SD; its spatial variation is so substantial that the estimated SD differs significantly between the south-facing and north-facing slopes,and its seasonal variation is also large throughout the year.展开更多
文摘Global solar radiation (GSR) is an essential physical quantity for agricultural management and designing infrastructures. Because GSR has often been modeled as a function of sunshine duration (SD) and day length for a given set of locations and calendar days, analyzing interannual trends in GSR and SD is important to evaluate, predict or regulate the cycles of energy and water between geosphere and atmosphere. This study aimed to exemplify interannual trends in GSR and SD, which had been recorded from 2001 to 2022 in 40 meteorological stations in Japan, and validate the applicability of an SD-based model to the evaluation of GSR. Both the measured GSR and SD had increased in many of the stations in the study period with averaged rates of 0.252 [W·m−2·y−1] and 0.015 [h·d−1·y−1], respectively. The offset and the slope of the SD-based model were estimated by fitting the model to the measured data sets and were found to have been almost constant with the averages of 0.201[-] and 0.566[-], respectively, indicating that characteristics of the SD-GSR relation had not varied for the 22-year period and that the model and its parameter set can be stationarily applicable to the analyses and predictions of GSR in recent years. The stable trends in both parameters also implied that the upward trend in SD can be a main explanatory factor for that in the measured GSR. The upward trend in SD had coincided with the increase in the frequency of heavy-shortened rains, suggesting that the time period of each rainfall event had gradually decreased, which may be attributable to the obtained upward trend in SD. Further studies are required to clarify if there is some cause-effect relation between the changes in rainfall patterns and the standard level of solar radiation reaching the land surface.
文摘以北京市为研究区域,联合使用光学遥感数据和雷达数据,对植被覆盖区地表土壤水分进行反演研究。在利用同期光学数据提取出归一化水分指数(normalized differential water index,NDWI)之后,利用water-cloud模型去除植被层在土壤水分后向散射中的贡献,然后考虑到地表粗糙度,在构建后向散射数据库的基础上分别利用HH和HV极化方式的后向散射系数构建土壤水分反演模型,并对反演结果进行对比研究。结果表明,采用HH极化方式反演土壤水分的均方根误差为0.044,相对误差为15.5%;采用HV极化方式反演土壤水分的均方根误差为0.057,相对误差为20.3%;相比而言,HH极化的反演效果更好。
基金Supported by the National Natural Science Foundation of China(41175077)Jiangsu Innovation Program for Graduate Education(CXZZ12-0506)
文摘Sunshine duration（SD） is strongly correlated with solar radiation, and is most widely used to estimate the latter. This study builds a remote sensing model on a 100 m × 100 m spatial resolution to estimate SD for the Ningxia Hui Autonomous Region, China. Digital elevation model（DEM） data are employed to reflect topography, and moderate-resolution imaging spectroradiometer（MODIS） cloud products（Aqua MYD06-L2 and Terra MOD06-L2） are used to estimate sunshine percentage. Based on the terrain（e.g.,slope, aspect, and terrain shadowing degree） and the atmospheric conditions（e.g., air molecules, aerosols,moisture, cloud cover, and cloud types）, observation data from weather stations are also incorporated into the model. Verification results indicate that the model simulations match reasonably with the observations,with the average relative error of the total daily SD being 2.21%. Further data analysis reveals that the variation of the estimated SD is consistent with that of the maximum possible SD; its spatial variation is so substantial that the estimated SD differs significantly between the south-facing and north-facing slopes,and its seasonal variation is also large throughout the year.
