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Development of multimodel ensemble based district level medium range rainfall forecast system for Indian region

机译:基于多模型合奏的印度地区区域中等降水量预报系统的开发

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India Meteorological Department has implemented district level medium range rainfall forecast system applying multimodel ensemble technique, making use of model outputs of state-of-the-art global models from the five leading global NWP centres. The pre-assigned grid point weights on the basis of anomaly correlation coefficients (CC) between the observed values and forecast values are determined for each constituent model at the resolution of 0.25° ×0.25° utilizing two season datasets (1 June–30 September, 2007 and 2008) and the multimodel ensemble forecasts (day-1 to day-5 forecasts) are generated at the same resolution on a real-time basis. The ensemble forecast fields are then used to prepare forecasts for each district, taking the average value of all grid points falling in a particular district. In this paper, we describe the development strategy of the technique and performance skill of the system during summer monsoon 2009. The study demonstrates the potential of the system for improving rainfall forecasts at five days time scale over Indian region. Districtwise performance of the ensemble rainfall forecast reveals that the technique, in general, is capable of providing reasonably good forecast skill over most states of the country, particularly over the states where the monsoon systems are more dominant.
机译:印度气象部门已经利用多模式集成技术,利用了来自五个主要的全球NWP中心的最新全球模型的模型输出,实施了区域级中程降雨预报系统。利用两个季节数据集(6月1日至9月30日,在0.25°×0.25°的分辨率下,为每个组成模型确定基于观测值和预测值之间的异常相关系数(CC)的预先分配的网格点权重。 2007年和2008年)和多模型集合预测(第1天到第5天的预测)是在相同的分辨率下实时生成的。然后,使用集合预报字段为每个地区准备预报,并获取落入特定地区的所有网格点的平均值。在本文中,我们描述了该系统在2009年夏季季风期间的技术和性能技能的发展策略。研究证明了该系统在改善印度地区五天时间尺度降雨预报方面的潜力。总体降雨预报的区域分布情况表明,该技术通常能够在该国大多数州(尤其是在季风系统占主导地位的州)提供合理的良好预报技能。

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