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利用起放电模式开展闪电活动的直接预报试验
引用本文:徐良韬,陈双,姚雯,谌芸,张荣.利用起放电模式开展闪电活动的直接预报试验[J].应用气象学报,2018,29(5):534-545.
作者姓名:徐良韬  陈双  姚雯  谌芸  张荣
作者单位:1.中国气象科学研究院灾害天气国家重点实验室/雷电物理和防护工程实验室, 北京 100081
基金项目:国家重点基础研究发展计划(2014CB441406),国家自然科学基金项目(41605003),中国气象科学研究院基本科研业务费专项资金(2016Y008,2017Z003)
摘    要:利用耦合有起电和放电物理过程的中尺度起电放电模式WRF-Electric,开展了华北地区连续3年(2015—2017年)的闪电活动预报试验。结合全国地闪定位观测资料,针对不同影响范围雷暴类型和预报时间,对数值预报结果开展点对点的定量检验,评估模式对闪电活动的预报能力及特点。结果表明:WRF-Electric中尺度模式具备一定的区域闪电活动预报能力,在起报后的6~12 h对闪电活动区域具有较好的预报效果。雷暴落区预报的点对点定量检验中,模式和业务预报在华北主汛期(6—8月)的预报临界成功指数(CSI)均为0.1,模式对于活动范围较小的局地性雷暴过程的预报更具参考价值。模式预报的闪电活动范围相对集中,闪电活动密度偏高,预报的主要问题存在于放电参数化方案的设计。应当考虑到模式空间分辨率对云内电场强度的影响,合理降低闪电参数化中的放电阈值以扩大预报的闪电活动范围。模式在闪电密度的定量预报上还有较大改进空间,单次放电中和电荷量应当更符合观测事实。

关 键 词:起放电模式    闪电预报    检验
收稿时间:2018/6/3 0:00:00
修稿时间:2018/8/2 0:00:00

Predicting Lightning Activities by a Meso-scale Electrification and Discharge Model
Xu Liangtao,Chen Shuang,Yao Wen,Chen Yun and Zhang Rong.Predicting Lightning Activities by a Meso-scale Electrification and Discharge Model[J].Quarterly Journal of Applied Meteorology,2018,29(5):534-545.
Authors:Xu Liangtao  Chen Shuang  Yao Wen  Chen Yun and Zhang Rong
Institution:1.Laboratory of Lightning Physics and Protection Engineering, State Key Laboratory of Severe Weather, Chinese Academy of Meteorological Sciences, Beijing 1000812.National Meteorological Center, Beijing 1000813.Weather Modification Center, China Meteorological Administration, Beijing 100081
Abstract:Using WRF-Electric model coupled with electrification and discharge schemes, experimental predictions are carried out on the regional lightning activity from 2015 to 2017. By establishing a lightning activity prediction verification method, experiment results are classified and evaluated. Taking operational prediction as a reference, the ability to predict regional lightning activity with the numerical model is evaluated objectively. Main problems of the model are identified through verification, which provides a basis for its further improvement.The major region of lightning activity could be predicted well by the meso-scale electrification and discharge model. In the strict point-to-point verification, the CSI of the model prediction almost reach the operational prediction level during the main flood season (June-August). Quantitative verification results over North China also show that the prediction performs best with the forecast time of 6-12 hours. For small-scale thunderstorms, CSI of the model prediction is higher than that of the operational prediction. With expansion of the thunderstorm scale, the model prediction gradually loses its advantage. Therefore, the model is more valuable for predicting localized and small-scale thunderstorms.The range of the lightning activity predicted by the model is small and relatively concentrated, and some scattered lightning activity is often missed. Thus, in the parameterization of discharge, the threshold should be decreased at the initial time of lightning to improve the performance in relatively weaker electrification region. The lightning flash density predicted by the model is obviously greater than observed. To reduce the predicted flash density in the strong electrification area, the amount of neutralization charge of a single lightning should be consistent with the observation in the discharge scheme.CSI is relatively low with both the operational and this model prediction. In some cases, the prediction can achieve a relatively high CSI, but in long-term prediction experiments it''s difficult to maintain high score using the strict point-to-point verification method. On the other hand, for weather phenomena with strong randomness in their occurrence position, the predictability is usually poor.Although the model can forecast the lightning activity area well, reaching the level of operational prediction, many problems remain in terms of the flash density forecast. How to parameterize lightning reasonably in a meso-scale model is still unresolved and extremely challenging. Currently, numerical models can predict precipitation successfully, while the ability to quantitatively predict the flash density is far behind. Improvement in lightning parameterization schemes and the selection of relevant thresholds in models relies on new methods and a large number of experiments being conducted.
Keywords:electrical model  lightning prediction  verification
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