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首页> 外文期刊>Journal of earth system science >Satellite-based technique for nowcasting of thunderstorms over Indian region
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Satellite-based technique for nowcasting of thunderstorms over Indian region

机译:基于卫星的印度地区雷暴临近预报技术

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India experiences severe thunderstorms during the months, Marcha€“June. But these systems are not predicted well, mainly due to the absence of mesoscale observational network over Indian region and the expert system. As these are short lived systems, the nowcast is attempted worldwide based on satellite and radar observations. Due to inadequate radar network, satellite plays the dominant role for nowcast of these thunderstorms. In this study, a nowcast based algorithm ForTracc developed by Vila et al. (Weather Forecast 23:233a€“245, 2008) has been examined over the Indian region using Infrared Channel (10.8 ??m) of INSAT-3D for prediction of Mesoscale Convective Systems (MCS). In this technique, the current location and intensity in terms of Cloud Top Brightness Temperature (CTBT) of the MCS are extrapolated. The purpose of this study is to validate this satellite-based nowcasting technique for Convective Cloud Clusters that helps in optimum utilization of satellite data and improve the nowcasting. The model could predict reasonably the minimum CTBT of the convective cell with average absolute error (AAE) of 7 K for different lead periods (30a€“180 min). However, it was underestimated for all the lead periods of forecasts. The AAE in the forecasts of size of the cluster varies from about 3?—104 km2 for 30-min forecast to 7?—104 km2 for 120-min forecast. The mean absolute error in prediction of size is above 31a€“38% of actual size for different lead periods of forecasts from 30 to 180 min. There is over estimation in prediction of size for 30 and 60 min forecasts (17% and 2.6% of actual size of the cluster, respectively) and underestimation in 90 to 180-min forecasts (a€“2.4% to a€“28%). The direct position error (DPE) based on the location of minimum CTBT ranges from 70 to 144 km for 30a€“180-min forecast respectively.
机译:在3月-6月的几个月中,印度经历了雷暴。但是这些系统的预测不是很好,主要是由于印度地区和专家系统缺乏中尺度的观测网络。由于这些系统寿命短,因此将在全球范围内根据卫星和雷达观测结果进行临近预报。由于雷达网络不足,卫星在这些雷暴的临近预报中起着主导作用。在这项研究中,由Vila等人开发的基于临近预报的算法ForTracc。 (天气预报23:233a€245,2008)已使用INSAT-3D的红外通道(10.8 m)对印度地区进行了研究,以用于预测中尺度对流系统(MCS)。在此技术中,根据MCS的云顶亮度温度(CTBT)推断当前位置和强度。这项研究的目的是验证对流云团的这种基于卫星的临近预报技术,该技术有助于最佳利用卫星数据并改善临近预报。该模型可以合理预测对流池的最小CTBT,在不同的提前期(30至180分钟)内,平均绝对误差(AAE)<7K。但是,对于所有预测的预测周期,它都被低估了。群集大小的预测中的AAE范围从30分钟预报的3?-104 km 2 到120分钟预报的7?-104 km 2 不等。在30到180分钟的不同预测周期内,尺寸预测的平均绝对误差大于实际尺寸的31%至38%。对于30分钟和60分钟的预测(分别占集群实际大小的17%和2.6%),对大小的预测有过高估计;而对于90分钟至180分钟的预测,则被低估了(2.4%至28%) )。基于最小CTBT位置的直接位置误差(DPE)分别为30至180分钟的预测范围从70到144 km。

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