首页> 外文期刊>Tellus, Series A. Dynamic meteorology & oceanography >Impact of satellite-based lake surface observations on the initial state of HIRLAM. Part I: evaluation of remotely-sensed lake surface water temperature observations
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Impact of satellite-based lake surface observations on the initial state of HIRLAM. Part I: evaluation of remotely-sensed lake surface water temperature observations

机译:基于卫星的湖面观测对HIRLAM初始状态的影响。第一部分:遥感湖地表水温观测的评价

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Lake Surface Water Temperature (LSWT) observations are used to improve the lake surface state in the High Resolution Limited Area Model (HIRLAM), a three-dimensional numerical weather prediction (NWP) model. In this paper, satellite-derived LSWT observations from the Moderate Resolution Imaging Spectroradiometer (MODIS) and the Along-Track Scanning Radiometer (AATSR) are evaluated against in-situ measurements collected by the Finnish Environment Institute (SYKE) for a selection of large- to medium-size lakes during the open-water season. Data assimilation of these LSWT observations into the HIRLAM is in the paper Part II. Results show a good agreement between MODIS and in-situ measurements from 22 Finnish lakes, with a mean bias of ?1.13°C determined over five open-water seasons (2007–2011). Evaluation of MODIS during an overlapping period (2007–2009) with the AATSR-L2 product currently distributed by the European Space Agency (ESA) shows a mean (cold) bias error of ?0.93°C for MODIS and a warm mean bias of 1.08°C for AATSR-L2. Two additional LSWT retrieval algorithms were applied to produce more accurate AATSR products. The algorithms use ESA's AATSR-L1B brightness temperature product to generate new L2 products: one based on Key et al. (1997) and the other on Prata (2002) with a finer resolution water mask than used in the creation of the AATSR-L2 product distributed by ESA. The accuracies of LSWT retrievals are improved with the Key and Prata algorithms with biases of 0.78°C and ?0.11°C, respectively, compared to the original AATSR-L2 product (3.18°C).
机译:湖面水温(LSWT)观测用于改善高分辨率有限区域模型(HIRLAM)(一种三维数值天气预报(NWP)模型)中的湖面状态。在本文中,对中分辨率成像光谱仪(MODIS)和沿轨扫描辐射仪(AATSR)衍生的卫星LSWT观测值进行了评估,以对比芬兰环境研究所(SYKE)收集的现场测量结果,以选择大型的在开阔水域到中型湖泊。这些LSWT观测值与HIRLAM的数据同化在论文第二部分中。结果表明,MODIS与来自22个芬兰湖泊的实地测量结果吻合良好,在五个开放水域(2007-2011年)确定的平均偏差为1.13°C。使用欧洲航天局(ESA)当前分发的AATSR-L2产品对MODIS进行的重叠期(2007-2009)评估显示,MODIS的平均(冷)偏差为0.93°C,温暖的平均偏差为1.08 AATSR-L2为°C。应用了另外两种LSWT检索算法来生成更准确的AATSR产品。该算法使用ESA的AATSR-L1B亮度温度乘积生成新的L2乘积:一种基于Key等人的算法。 (1997)和Prata(2002)上的另一种产品,其分辨率比水面罩要好于ESA发行的AATSR-L2产品的制造。与原始AATSR-L2产品(3.18°C)相比,Key和Prata算法的偏差分别为0.78°C和±0.11°C,从而提高了LSWT检索的准确性。

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