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Predicting Lightning Activities by a Meso-scale Electrification and Discharge Model
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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。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.
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Key words:
- electrical model;
- lightning prediction;
- verification
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图 2 两层模拟区域及观测点(黑点)分布
(填色为地形)
Fig. 2 Locations of two domains and observation stations(black dot)
(the shaded denotes terrain)
图 3 3个个例观测和不同预报时间闪电密度对比
Fig. 3 Comparison of observed and simulated flash density with different forecast time of 3 cases
图 4 业务和不同时间预报检验
Fig. 4 Verification for the operational and numerical prediction with different forecast time
图 5 不同活动范围雷暴的预报检验
Fig. 5 Verification for the operational and numerical prediction with different forecast time
图 6 观测、业务及模式预报的雷暴发生站点数、命中站点数、空报站点数和漏报站点数
Fig. 6 Observed, operational and numerical prediction total thunderstorm station numbers in all verification cases along with the hit station number, false alarm station number and missing alarm station number
表 1 模式的基本设置
Table 1 Model design
参数 d01 d02 格点数 124×124 160×160 格距/km 12 4 时间步长/s 45 15 积分时间/h 24 24 边界层方案 YSU YSU 微物理方案 Milbrandt双参 Milbrandt双参 非感应起电方案 TGZ TGZ 积云方案 Kain-Fritsch 侧边界条件 嵌套 长波辐射方案 RRTM RRTM 短波辐射方案 Dudhia Dudhia 
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