首页> 外文期刊>Journal of Applied Meteorology and Climatology >Evaluation of Cloud-Phase Retrieval Methods for SEVIRI on Meteosat-8 Using Ground-Based Lidar and Cloud Radar Data
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Evaluation of Cloud-Phase Retrieval Methods for SEVIRI on Meteosat-8 Using Ground-Based Lidar and Cloud Radar Data

机译:使用地面激光雷达和云雷达数据评估Meteosat-8上SEVIRI的云相检索方法

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Three cloud-phase determination algorithms from passive satellite imagers are explored to assess their suitability for climate monitoring purposes in midlatitude coastal climate zones. The algorithms are the Moderate Resolution Imaging Spectroradiometer (MODIS)-like thermal infrared cloud-phase method, the Satellite Application Facility on Climate Monitoring (CM-SAF) method, and an International Satellite Cloud Climatology Project (ISCCP)-like method. Using one year (May 2004–April 2005) of data from the Spinning Enhanced Visible and Infrared Imager (SEVIRI) on the first Meteosat Second Generation satellite (Meteosat-8), retrievals of the methods are compared with collocated and synchronized ground-based cloud-phase retrievals obtained from cloud radar and lidar observations at Cabauw, Netherlands. Three aspects of the satellite retrievals are evaluated: 1) instantaneous cloud-phase retrievals, 2) monthly-averaged water and ice cloud occurrence frequency, and 3) diurnal cycle of cloud phase for May–August 2004. For the instantaneous cases, all methods have a very small bias for thick water and ice cloud retrievals (5%). The ISCCP-like method has a larger bias for pure water clouds (10%), which is likely due to the 260-K threshold leading to misdetection of water clouds existing at lower temperatures. For the monthly-averaged water and ice cloud occurrence, the CM-SAF method is best capable of reproducing the annual cycle, mainly for the water cloud occurrence frequency, for which an almost constant positive bias of 8% was found. The ISCCP- and MODIS-like methods have more problems in detecting the annual cycle, especially during the winter months. The difference in annual cycle detection among the three methods is most probably related to theuse of visibleear-infrared reflectances that enable a more direct observation of cloud phase. The diurnal cycle in cloud phase is reproduced well by all methods. The MODIS-like method reproduces the diurnal cycle best, with correlations of 0.89 and 0.86 for water and ice cloud occurrence frequency, respectively.
机译:探索了来自被动卫星成像仪的三种云相确定算法,以评估其在中纬度沿海气候区中进行气候监测的适用性。这些算法是类似中分辨率成像光谱仪(MODIS)的热红外云相方法,气候监测卫星应用设施(CM-SAF)方法和国际卫星云气候计划(ISCCP)类方法。使用第一颗Meteosat第二代卫星(Meteosat-8)上的旋转增强型可见光和红外成像仪(SEVIRI)的一年(2004年5月)数据,将该方法的检索结果与同位同步的地面云进行比较从荷兰Cabauw的云雷达和激光雷达观测中获得的两阶段检索。评估了卫星检索的三个方面:1)瞬时云相检索,2)月平均水和冰云出现频率,以及3)2004年5月至8月的云相昼夜周期。对于瞬时情况,所有方法对于浓水和冰云的取回,偏差很小(5%)。类似于ISCCP的方法对纯水云有较大偏差(10%),这很可能是由于260-K阈值导致在较低温度下对水云的误检测。对于月平均水和冰云的出现,CM-SAF方法最能重现年周期,主要是针对水云的出现频率,发现其几乎恒定的8%的正偏差。类似于ISCCP和MODIS的方法在检测年度周期方面存在更多问题,尤其是在冬季。三种方法之间年度周期检测的差异很可能与可见/近红外反射率的使用有关,从而可以更直接地观察云相。所有方法都能很好地再现云期的昼夜周期。类似于MODIS的方法可以最好地再现昼夜周期,水和冰云的出现频率分别为0.89和0.86。

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