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Impact of a consistent height reassignment method for INSAT derived cloud motion vectors

机译:一致的高度重分配方法对INSAT导出的云运动矢量的影响

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摘要

¶Cloud Motion Vector wind (CMV) data is one of the major products derived from current day operational geostationary satellites and continues to be a useful source of information for global data assimilation systems. The CMV fields result basically from the apparent cloud motion estimated through a sequence of very high resolution radiometer (VHRR) images and the corresponding cloud level is inferred from observed brightness temperatures (BT) in the infrared window channel. The main problem in CMV production is associated with the assignment of correct height to the cloud tracked motions in view of the known limitations associated with the cloud emissivity characteristics and estimation of BTs. Despite these inherent uncertainties satellite derived CMVs are widely used to augment the conventional upper air wind data especially over the oceanic regions. In this study, an attempt is made to improve the quality of INSAT derived CMVs through an appropriate height re-assignment by employing first guess fields (short range forecasts) of a global forecast model.
机译:¶云运动矢量风(CMV)数据是从当今运行的对地静止卫星衍生而来的主要产品之一,并且仍然是全球数据同化系统的有用信息来源。 CMV场基本上是由通过一系列非常高分辨率的辐射计(VHRR)图像估算出的视云运动产生的,并且从红外窗口通道中观察到的亮度温度(BT)可以推断出相应的云水平。鉴于与云发射率特性和BT的估算有关的已知限制,CMV生产中的主要问题与为云跟踪的运动分配正确的高度有关。尽管存在这些固有的不确定性,但衍生自卫星的CMV被广泛用​​于增强常规的高空风数据,尤其是在大洋地区。在这项研究中,尝试通过采用全局预测模型的第一个猜测字段(短程预测),通过适当的高度重新分配来提高INSAT衍生的CMV的质量。

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  • 来源
    《Meteorology and Atmospheric Physics》 |2003年第4期|163-172|共10页
  • 作者单位

    National Centre for Medium Range Weather Forecasting [NCMRWF] Lodi Road New Delhi India;

    National Centre for Medium Range Weather Forecasting [NCMRWF] Lodi Road New Delhi India;

    National Centre for Medium Range Weather Forecasting [NCMRWF] Lodi Road New Delhi India;

    India Meteorological Department Lodi Road New Delhi India;

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