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1.
James L. Foster Gail Skofronick‐Jackson Huan Meng James R. Wang George Riggs Paul J. Kocin Benjamin T. Johnson Judah Cohen Dorothy K. Hall Son V. Nghiem 《水文研究》2012,26(22):3459-3471
The snowfall in the Baltimore/Washington metropolitan area during the winter of 2009/2010 was unprecedented and caused serious snow‐related disruptions. In February 2010, snowfall totals approached 2 m, and because maximum temperatures were consistently below normal, snow remained on the ground the entire month. One of the biggest contributing factors to the unusually severe winter weather in 2009/2010, throughout much of the middle latitudes, was the Arctic Oscillation. Unusually high pressure at high latitudes and low pressure at middle latitudes forced a persistent exchange of mass from north to south. In this investigation, a concerted effort was made to link remotely sensed falling snow observations to remotely sensed snow cover and snowpack observations in the Baltimore/Washington area. Specifically, the Advanced Microwave Scanning Radiometer onboard the Aqua satellite was used to assess snow water equivalent, and the Advanced Microwave Sounding Unit‐B and Microwave Humidity Sounder were employed to detect falling snow. Advanced Microwave Scanning Radiometer passive microwave signatures in this study are related to both snow on the ground and surface ice layers. In regard to falling snow, signatures indicative of snowfall can be observed in high frequency brightness temperatures of Advanced Microwave Sounding Unit‐B and Microwave Humidity Sounder. Indeed, retrievals show an increase in snow water equivalent after the detection of falling snow. Yet, this work also shows that falling snow intensity and/or the presence of liquid water clouds impacts the ability to reliably detect snow water equivalent. Moreover, changes in the condition of the snowpack, especially in the surface features, negatively affect retrieval performance. Copyright © 2011. This article is a U.S. Government work and is in the public domain in the USA. 相似文献
2.
The soil freeze–thaw controls the hydrological and carbon cycling and thus affects water and energy exchanges at land surface. This article reported a newly developed algorithm for distinguishing the freeze/thaw status of surface soil. The algorithm was based on information from Advanced Microwave Scanning Radiometer Enhanced (AMSR‐E) which records brightness temperature (Tb) in the afternoon and after midnight. The criteria and discriminant functions were obtained from both radiometer observations and model simulations. First of all, the microwave radiation from freeze–thaw soil was examined by carrying out experimental measurements at 18·7 and 36·5 GHz using a Truck‐mounted Multi‐frequency Microwave Radiometer (TMMR) in the Heihe River of China. The experimental results showed that the soil moisture is a key component that differentiates the microwave radiation behaviours during the freeze–thaw process, and the differences in soil temperature and emissivity between frozen and thawed soils were found to be the most important criteria. Secondly, a combined model was developed to consider the impacts of complex ground surface conditions on the discrimination. The model simulations quite followed the trend of in situ observations with an overall relation coefficient (R) of approximately 0·88. Finally, the ratio of Tb18·7H (horizontally polarized Tb at 18·7 GHz) to Tb36·5V was considered primarily as the quasi‐emissivity, which is more reasonable and explicit in measuring the microwave radiation changes in soil freezing and thawing than the spectral gradient. By combining Tb36·5V to indicate the soil temperature variety, a Fisher linear discrimination analysis was used to establish the discriminant functions. After being corrected by TMMR measurements, the new discriminant algorithm had an overall accuracy of 86% when validated by 4‐cm soil temperature. The multi‐year discriminant results also provided a good agreement with the classification map of frozen ground in China. Copyright © 2011 John Wiley & Sons, Ltd. 相似文献
3.
Spring snow melt run‐off in high latitude and snow‐dominated drainage basins is generally the most significant annual hydrological event. Melt timing, duration, and flow magnitude are highly variable and influence regional climate, geomorphology, and hydrology. Arctic and sub‐arctic regions have sparse long‐term ground observations and these snow‐dominated hydrologic regimes are sensitive to the rapidly warming climate trends that characterize much of the northern latitudes. Passive microwave brightness temperatures are sensitive to changes in the liquid water content of the snow pack and make it possible to detect incipient melt, diurnal melt‐refreeze cycles, and the approximate end of snow cover on the ground over large regions. Special Sensor Microwave Imager (SSM/I) and Advanced Microwave Scanning Radiometer for EOS (AMSR‐E) passive microwave brightness temperatures (Tb) and diurnal amplitude variations (DAV) are used to investigate the spatial variability of snowmelt onset timing (in two stages, ‘DAV onset’ and ‘melt onset’) and duration for a complex sub‐arctic landscape during 2005. The satellites are sensitive to small percentages of liquid water, and therefore represent ‘incipient melt’, a condition somewhat earlier than a traditional definition of a melting snowpack. Incipient melt dates and duration are compared to topography, land cover, and hydrology to investigate the strength and significance of melt timing in heterogeneous landscapes in the Pelly River, a major tributary to the Yukon River. Microwave‐derived melt onset in this region in 2005 occurred from late February to late April. Upland areas melt 1–2 weeks later than lowland areas and have shorter transition periods. Melt timing and duration appear to be influenced by pixel elevation, aspect, and uniformity as well as other factors such as weather and snow mass distribution. The end of the transition season is uniform across sensors and across the basin in spite of a wide variety of pixel characteristics. Copyright © 2007 John Wiley & Sons, Ltd. 相似文献
4.
由陆面信息系统 (Land Information System, 简称LIS) 通过NOAH陆面过程模型使用集合卡尔曼滤波开展AMSR-E (Advanced Microwave Scanning Radiometer-Earth Observing System) 土壤湿度同化试验,得到2003年中国区域垂直深度为4层、水平空间分辨率为0.25°×0.25°的土壤湿度试验数据。使用农业气象观测站土壤相对湿度和国家生态系统野外科学观测研究站土壤体积含水量对试验结果进行检验,结果表明:同化过程整体上提高了陆面模型的模拟精度,草地生态系统模拟精度高于作物和森林生态系统;有效的同化过程依赖于AMSR-E土壤湿度的准确性;模拟出的土壤湿度空间分布特征与实际相符。同化试验得到的时空相对连续且精度相对准确的土壤湿度数据是气候变化和干旱监测的重要数据基础。 相似文献
5.
被动微波土壤水分反演模型研究 总被引：3，自引：0，他引：3
在分析现有地表辐射模型的基础上,分析了被动微波遥感的辐射传输方程,并且对辐射传输过程的主要因素进行了分析.最后对地面辐射进行了介绍,并针对被动微波AMSR数据提出了地表土壤水分反演的模型. 相似文献
6.
用被动微波AMSR数据反演地表温度及发射率的方法研究 总被引：8，自引：1，他引：8
针对对地观测卫星多传感器的特点，提出了借助MODIS地表温度产品从被动微波数据中反演地表温度的方法。即利用MODIS地表温度产品和AMSR不同通道之间的亮度温度，建立地表温度的反演方程。该方法克服了以往需要测量同步数据的困难，为不同传感器之间的参数反演相互校正和综合利用多传感器的数据提供实际应用和理论依据。文中以MODIS地表温度产品作为评价标准，对方法进行检验，其平均误差为2~3℃。另外，微波的发射率是土壤水分反演的关键参数，在对微波地表温度反演的基础上，进一步对发射率进行了研究。 相似文献
7.
AMSR2辐射率资料同化对台风“山神”分析和预报的影响研究 总被引：3，自引：2，他引：1
在WRFDA-3DVar（Weather Research and Forecasting model's 3-dimensional variational data assimilation）的框架下,添加了新的探测器AMSR2（Advanced Microwave Scanning Radiometer 2）微波辐射率资料的同化模块,实现了AMSR2辐射率资料在中小尺度同化系统中的有效使用。台风"山神"（Son-Tinh）直接同化AMSR2资料的个例试验结果表明,AMSR2资料可以很好的探测出台风的形态,并且与没有同化该资料的控制试验相比,同化AMSR2辐射率资料可以有效提高模式分析场的质量,进一步提高了台风中心气压,最大风速和台风路径的预报。 相似文献
8.
利用被动微波可穿透云层的优势,基于GCOM-W1/AMSR2（Global Change Observation Mission-Water/ Advanced Microwave Scanning Radiometer 2）星载被动微波传感器的多通道亮度温度数据,反演了2016年1月下旬“超级寒潮”过程的广东省每日地表温度,分析了寒潮过程中广东省地表温度的时空变化特征。结果表明：在寒潮前后,广东省地表温度呈现出明显的先下降而后上升的趋势,寒潮过程带来的地表最低温度在广东北部大部分地区达到了277 K（4℃）,西南大部分地区为280~282 K（7~9℃）,其余大部分地区278~279 K（5~6℃）;降温幅度在广东南部地区达到了8~12 K（8~12℃）,北部大部分地区为5~7 K（5~7℃）。此外,利用归一化植被指数（NDVI）对植被生长的指示作用,基于HJ-1 A/B卫星的CCD传感器的多通道反射率数据,计算了近3年冬季广东省典型马铃薯种植区域马铃薯叶片的NDVI值,结果表明：马铃薯叶片的NDVI值在此次寒潮过程后出现了明显的下降,大部分地区（55.4%）马铃薯NDVI降低了0.1~0.2,部分地区（17.2%）马铃薯NDVI下降了0.2~0.3;进一步对比此次“超级寒潮”后同时段的前2年数据,发现寒潮后马铃薯叶片NDVI相对于正常年份也低了0.2,表明马铃薯叶片NDVI下降的主要原因是寒潮带来的低温,而不只是马铃薯的正常老化现象。NDVI的降低表明大部分地区马铃薯生长受到了抑制,马铃薯生长状况的这一变化也通过现场调查得到了证实。 相似文献
9.
基于AMSR2被动微波积雪参量高精度反演方法研究 总被引：2，自引：2，他引：0
以新疆为研究区域建立了被动微波遥感积雪深度高精度反演模型,采用高空间和时间分辨率AM SR2被动微波遥感数据(2012年11月-2015年3月逐日数据),结合研究区域海拔高度、坡度、坡向、沙漠,荒漠和地表粗糙度等地形、地貌特征,考虑冰川、水体、林地等地表覆盖类型和不同季节的新雪、干雪和湿雪等积雪属性的微波辐射特征,以决策树阈值法为基础,通过采集样本分类建立起多种雪深判识阈值,在此基础上建立AMSR2高精度积雪深度反演综合模型,分类分析不稳定积雪和冰川信息,从而实现雪深在60 cm以内的积雪深度AMSR2反演的主要原理、思路及方法,并对模型的反演结果跟台站实测或者野外观测积雪值以时间和空间角度进行检验.结果表明:该综合模型能够定量判识研究区域复杂地形地貌条件下的1~60 cm积雪厚度,检验的复相关系数为0.74~0.88,均方根误差为2.92~6.14 cm,平均绝对偏差指数为3~4 cm,雪深误差5 cm的精度为91%~94%,雪深误差2.5cm的精度为81%~87%. 相似文献
10.
Information on regional snow water equivalent (SWE) is required for the management of water generated from snowmelt. Modeling of SWE in the mountainous regions of eastern Turkey, one of the major headwaters of Euphrates–Tigris basin, has significant importance in forecasting snowmelt discharge, especially for optimum water usage. An assimilation process to produce daily SWE maps is developed based on Helsinki University of Technology (HUT) model and AMSR‐E passive microwave data. The characteristics of the HUT emission model are analyzed in depth and discussed with respect to the extinction coefficient function. A new extinction coefficient function for the HUT model is proposed to suit models for snow over mountainous areas. Performance of the modified model is checked against the original, other modified cases and ground truth data covering the 2003–2007 winter periods. A new approach to calculate grain size and density is integrated inside the developed data assimilation process. An extensive validation was successfully performed by means of snow data measured at ground stations during the 2008–2010 winter periods. The root mean square error of the data set for snow depth and SWE between January and March of the 2008–2010 periods compared with the respective AMSR‐E footprints indicated that errors for estimated snow depth and predicted SWE values were 16.92 cm and 40.91 mm, respectively, for the 3‐year period. Validation results were less satisfactory for SWE less than 75.0 mm and greater than 150.0 mm. An underestimation for SWE greater than 150 mm could not be resolved owing to the microwave signal saturation that is observed for dense snowpack. Copyright © 2012 John Wiley & Sons, Ltd. 相似文献