双站摄像资料重建闪电三维通道的方法

为了满足准确分析闪电通道三维发展特征和闪电先导相互作用的需求,建立了一种利用双站摄像资料重建闪电三维通道的方法,从两幅在不同位置拍摄到的闪电二维图像上分别获取通道的坐标序列,利用空间立体几何原理,寻找两组序列中互相匹配的坐标,再由匹配的坐标序列重建出最终的闪电三维通道。通过对一次实际观测个例的重建与分析,验证了重建算法在实际观测中的可靠性,并对闪电通道的三维长度和二维长度进行了对比,发现两者差异可达2倍以上,充分说明了闪电三维特征分析的重要性。     

改进的互功率谱相位法在雷声声源定位中的应用

互相关函数法是一种常用的时延估计方法,但在低信噪比和闪电存在多分叉的情况下,该方法的效果不理想。针对这一问题,该文选取广州地区2009年8月24日19:08:04和2012年5月5日08:01:00的两次闪电过程的雷声记录,结合高速摄像资料,比较了互相关函数法和改进的互功率谱相位法在雷声声源定位中的应用效果。首先,利用互相关函数法和改进的互功率谱相位法计算声源点的方向信息,定位结果与高速摄像照片对比具有较好的一致性,证明了定位方法的可靠性,对比结果表明:在低信噪比环境和多分叉闪电情况下,改进的互功率谱相位法能够获得比互相关函数法更好的定位效果。最后给出了综合利用改进的互功率谱相位法计算得到的方向信息和声源点与观测点的距离信息得到的雷声声源三维定位结果。     

Impacts of a Large-scale Adaptive Blending Scheme for CMA-MESO on Regional Forecasts-A Case Study of Typhoon Haima

Large-scale atmospheric information plays an important role in the regional model for the forecasts of weather such as tropical cyclone (TC). However, it is difficult to be fully represented in regional models due to domain size and a lack of observation data, particularly at sea used in regional data assimilation. Blending analysis has been developed and implemented in regional models to reintroduce large-scale information from global model to regional analysis. Research of the impact of this large-scale blending scheme for the Global / Regional Assimilation and PrEdiction System (CMA-MESO) regional model on TC forecasting is limited and this study attempts to further progress by examining the adaptivity of the blending scheme using the two-dimensional Discrete Cosine Transform (2D-DCT) filter on the model forecast of Typhoon Haima over Shenzhen, China in 2016 and considering various cut-off wavelengths. Results showed that the error of the 24-hour typhoon track forecast can be reduced to less than 25 km by applying the scale-dependent blending scheme, indicating that the blending analysis is effectively able to minimise the large-scale bias for the initial fields. The improvement of the wind forecast is more evident for u-wind component according to the reduced root mean square errors (RMSEs) by comparing the experiments with and without blending analysis. Furthermore, the higher equitable threat score (ETS) provided implications that the precipitation prediction skills were increased in the 24h forecast by improving the representation of the large-scale feature in the CMA-MESO analysis. Furthermore, significant differences of the track error forecast were found by applying the blending analysis with different cut-off wavelengths from 400 km to 1200 km and the track error can be reduced less than by 10 km with 400 km cut-off wavelength in the first 6h forecast. It highlighted that the blending scheme with dynamic cut-off wavelengths adapted to the development of different TC systems is necessary in order to optimally introduce and ingest the large-scale information from global model to the regional model for improving the TC forecast. In this paper, the methods and data applied in this study will be firstly introduced, before discussion of the results regarding the performance of the blending analysis and its impacts on the wind and precipitation forecast correspondingly, followed by the discussion of the effects of different blending scheme on TC forecasts and the conclusion section.