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Simulation of Spaceborne Microwave Radiometer Measurements of Snow Cover Using In Situ Data and Brightness Temperature Modeling

机译:利用原位数据和亮度温度模拟对星载微波辐射计测量积雪的模拟

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摘要

The Helsinki University of Technology (HUT) snow emission model is used to calculate the time series of brightness temperature of snow-covered sparsely forested area for the winter 2006–2007. Brightness temperature simulations that apply in situ observed physical parameters as input are compared with the Advanced Microwave Scanning Radiometer for Earth Observing System (AMSR-E) observations. Three models for the extinction coefficient of snow and the statistical and physical atmospheric models are compared. Simulation results are presented with full in situ data set and only air temperature and snow depth (SD) as input data. The obtained results indicate that the extinction coefficient model of Hallikainen originally used with the HUT snow emission model is the best suited for the Finnish snow data set used in this paper and also on frequencies which are outside the original range of the extinction coefficient model. The simulation results obtained using only air temperature and SD input data show that the HUT snow model is quite reliable even with a minimal in situ data set. A time series of optimized grain sizes was calculated by minimizing the simulation error. The optimized grain size tended to saturate with large values, and therefore, a new model to calculate an effective grain size was developed. The simulation with the effective grain size as input has lower rms error and higher correlation with AMSR-E data than the simulation with the measured grain size.
机译:赫尔辛基工业大学(HUT)的积雪排放模型用于计算2006-2007年冬季积雪稀疏林区的亮度温度时间序列。将就地观测的物理参数作为输入的亮度温度模拟与先进的地球观测系统微波扫描辐射计(AMSR-E)观测进行了比较。比较了三种雪的消光系数模型以及统计和物理大气模型。仿真结果以完整的原位数据集表示,只有气温和雪深(SD)作为输入数据。获得的结果表明,最初与HUT雪排放模型一起使用的Hallikainen的消光系数模型最适合本文中使用的芬兰雪数据集,并且最适用于超出消光系数模型原始范围的频率。仅使用空气温度和SD输入数据获得的仿真结果表明,即使使用最少的现场数据集,HUT雪模型也非常可靠。通过最小化模拟误差来计算最佳晶粒尺寸的时间序列。优化的晶粒尺寸趋于饱和,具有较大的值,因此,开发了一种用于计算有效晶粒尺寸的新模型。以有效晶粒尺寸作为输入的模拟比使用实测晶粒尺寸的模拟具有更低的均方根误差和与AMSR-E数据的相关性更高。

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