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首页> 外文期刊>Remote Sensing of Environment: An Interdisciplinary Journal >Evaluation of the HUT modified snow emission model over lake ice using airborne passive microwave measurements
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Evaluation of the HUT modified snow emission model over lake ice using airborne passive microwave measurements

机译:使用机载无源微波测量评估HUT修正的湖冰上雪排放模型

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The algorithms designed to estimate snow water equivalent (SWE) using passive microwave measurements falter in lake-rich high-latitude environments due to the emission properties of ice covered lakes on low frequency measurements. Microwave emission models have been used to simulate brightness temperatures (Tbs) for snowpack characteristics in terrestrial environments but cannot be applied to snow on lakes because of the differing subsurface emissivities and scattering matrices present in ice. This paper examines the performance of a modified version of the Helsinki University of Technology (HUT) snow emission model that incorporates microwave emission from lake ice and sub-ice water. Inputs to the HUT model include measurements collected over brackish and freshwater lakes north of Inuvik, Northwest Territories, Canada in April 2008, consisting of snowpack (depth, density, and snow water equivalent) and lake ice (thickness and ice type). Coincident airborne radiometer measurements at a resolution of 80 × 100 m were used as ground-truth to evaluate the simulations.The results indicate that subsurface media are simulated best when utilizing a modeled effective grain size and a 1. mm RMS surface roughness at the ice/water interface compared to using measured grain size and a flat Fresnel reflective surface as input. Simulations at 37. GHz (vertical polarization) produce the best results compared to airborne Tbs, with a Root Mean Square Error (RMSE) of 6.2. K and 7.9. K, as well as Mean Bias Errors (MBEs) of -8.4. K and -8.8. K for brackish and freshwater sites respectively. Freshwater simulations at 6.9 and 19. GHz H exhibited low RMSE (10.53 and 6.15. K respectively) and MBE (-5.37 and 8.36. K respectively) but did not accurately simulate Tb variability (R=-0.15 and 0.01 respectively). Over brackish water, 6.9. GHz simulations had poor agreement with airborne Tbs, while 19. GHz V exhibited a low RMSE (6.15. K), MBE (-4.52. K) and improved relative agreement to airborne measurements (R = 0.47). Salinity considerations reduced 6.9. GHz errors substantially, with a drop in RMSE from 51.48. K and 57.18. K for H and V polarizations respectively, to 26.2. K and 31.6. K, although Tb variability was not well simulated. With best results at 37. GHz, HUT simulations exhibit the potential to track Tb evolution, and therefore SWE through the winter season.
机译:该算法旨在通过被动微波测量来估算雪水当量(SWE),这在湖水丰富的高纬度环境中会因抖动而降低,这是因为低频测量时冰覆盖的湖泊具有发射特性。微波发射模型已被用于模拟陆地环境中积雪特征的亮温(Tbs),但由于冰中存在的地下发射率和散射矩阵不同,因此无法应用于湖泊的积雪。本文研究了赫尔辛基工业大学(HUT)降雪模型的修改版本的性能,该模型结合了湖冰和冰水中的微波发射。 HUT模型的输入包括2008年4月在加拿大西北地区Inuvik以北的咸淡水湖和淡水湖上收集的测量值,包括积雪(深度,密度和雪水当量)和湖冰(厚度和冰类型)。机载辐射计的重合分辨率为80×100 m,被用作地面真相以评估模拟结果。结果表明,当使用模型化有效粒径和冰上1. mm RMS表面粗糙度时,地下介质的模拟效果最佳/水界面与使用测得的晶粒尺寸和平坦的菲涅尔反射面作为输入进行比较。与机载Tb相比,在37. GHz(垂直极化)下的模拟产生最佳结果,均方根误差(RMSE)为6.2。 K和7.9。 K,以及-8.4的平均偏差误差(MBE)。 K和-8.8。分别用于微咸水和淡水站点的K。在6.9和19. GHz H处进行的淡水模拟显示出较低的RMSE(分别为10.53和6.15。K)和MBE(分别为-5.37和8.36。K),但不能准确地模拟Tb的变化(分别为R = -0.15和0.01)。苦咸水6.9。 GHz模拟与机载Tb的一致性差,而19. GHz V的RMSE(6.15。K),MBE(-4.52。K)低,并且相对于机载测量的相对一致性更高(R = 0.47)。盐度的考虑因素降低了6.9。 GHz误差很大,RMSE从51.48下降。 K和57.18。对于H和V极化,K分别为26.2。 K和31.6。 K,尽管并未很好地模拟Tb的变异性。在37. GHz的最佳结果下,HUT仿真具有跟踪Tb演变以及跟踪整个冬季SWE的潜力。

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