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首页> 外文期刊>Remote Sensing >Estimating High Resolution Daily Air Temperature Based on Remote Sensing Products and Climate Reanalysis Datasets over Glacierized Basins: A Case Study in the Langtang Valley, Nepal
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Estimating High Resolution Daily Air Temperature Based on Remote Sensing Products and Climate Reanalysis Datasets over Glacierized Basins: A Case Study in the Langtang Valley, Nepal

机译：基于遥感产品和气候再分析数据集的冰川化盆地的高分辨率日气温估算：以尼泊尔郎塘谷为例

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摘要

Near surface air temperature (Ta) is one of the key input parameters in land surface models and hydrological models as it affects most biogeophysical and biogeochemical processes of the earth surface system. For distributed hydrological modeling over glacierized basins, obtaining high resolution Ta forcing is one of the major challenges. In this study, we proposed a new high resolution daily Ta estimation scheme under both clear and cloudy sky conditions through integrating the moderate-resolution imaging spectroradiometer (MODIS) land surface temperature (LST) and China Meteorological Administration (CMA) land data assimilation system (CLDAS) reanalyzed daily Ta. Spatio-temporal continuous MODIS LST was reconstructed through the data interpolating empirical orthogonal functions (DINEOF) method. Multi-variable regression models were developed at CLDAS scale and then used to estimate Ta at MODIS scale. The new Ta estimation scheme was tested over the Langtang Valley, Nepal as a demonstrating case study. Observations from two automatic weather stations at Kyanging and Yala located in the Langtang Valley from 2012 to 2014 were used to validate the accuracy of Ta estimation. The RMSEs are 2.05, 1.88, and 3.63 K, and the biases are 0.42, ?0.68 and ?2.86 K for daily maximum, mean and minimum Ta, respectively, at the Kyanging station. At the Yala station, the RMSE values are 4.53, 2.68 and 2.36 K, and biases are 4.03, 1.96 and ?0.35 K for the estimated daily maximum, mean and minimum Ta, respectively. Moreover, the proposed scheme can produce reasonable spatial distribution pattern of Ta at the Langtang Valley. Our results show the proposed Ta estimation scheme is promising for integration with distributed hydrological model for glacier melting simulation over glacierized basins.
机译：近地表空气温度（Ta）是陆地表面模型和水文模型的关键输入参数之一，因为它会影响地球表面系统的大多数生物地球物理和生物地球化学过程。对于冰川盆地上的分布式水文模拟，获得高分辨率的Ta强迫是主要挑战之一。在这项研究中，我们通过结合中分辨率成像光谱仪（MODIS）地表温度（LST）和中国气象局（CMA）土地数据同化系统（ CLDAS）重新分析了每日Ta。通过数据插值经验正交函数（DINEOF）方法重建时空连续MODIS LST。在CLDAS规模上开发了多变量回归模型，然后将其用于在MODIS规模上估计Ta。作为示范案例研究，新的Ta估算方案在尼泊尔Langtang谷地进行了测试。利用2012年至2014年在郎塘谷的Kyanging和Yala的两个自动气象站进行的观测来验证Ta估计的准确性。在Kyanging站，每日最大，平均和最小Ta的RMSE为2.05、1.88和3.63 K，偏差分别为0.42，？0.68和？2.86K。在Yala站，估计的每日最大，平均和最小Ta的RMSE值分别为4.53、2.68和2.36 K，偏差分别为4.03、1.96和0.35K。此外，所提出的方案可以在郎塘谷产生合理的Ta空间分布格局。我们的结果表明，提出的Ta估算方案有望与分布式水文模型集成，用于冰川盆地的冰川融化模拟。

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