基于Local-BGM法的冷渦暴雨集合預報試驗及評估檢驗

doi:10.12306/2021jms.0030

首頁 > 過刊瀏覽>2023年第43卷第1期 >36-45. DOI:10.12306/2021jms.0030

基于Local-BGM法的冷渦暴雨集合預報試驗及評估檢驗
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                        10.12306/2021jms.0030
                    
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中圖分類號:P457.6
基金項目:國家自然科學基金面上資助項目 (41575104);南方電網科學研究院有限責任公司基礎性前瞻性項目(SEPRI-K213004)

The ensemble forecasting experiment and assessment of a cold vortex rainstorm based on Local-BGM

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基于傳統(tǒng)增長模繁殖法(Breeding Growing Mode,BGM)和局地增長模繁殖法(Local Breeding Growing Mode,Local-BGM)生成初始擾動成員,對一次冷渦暴雨過程進行集合預報試驗,從多方面比較兩種方案的預報效果,并且在鄰域概率法(Neighborhood Probability,NP)中引入時間鄰域,評估概率預報結果。結果表明,引入局地化思想的Local-BGM方案能夠生成比傳統(tǒng)BGM方案更合理的初始擾動,具有很明顯的局地特征。對于擾動變量的預報,Local-BGM方案在均方根誤差和離散度等方面均表現更好,同時能夠提高各量級降水的預報技巧。鄰域集合概率法能夠綜合各個集合成員預報的降水信息得到優(yōu)于集合平均的概率預報,分數技巧評分更高。并且在考慮時間不確定性后,無論是控制預報、集合平均還是鄰域集合概率法,分數技巧評分均有很大改善,并且降水閾值越大改善效果越明顯,能夠為極端強降水天氣提供較為客觀的概率預報信息。

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Based on traditional Breeding Growing Mode (BGM) and Local Breeding Growing Mode (Local-BGM), the initial perturbation members are generated respectively. The ensemble forecasting experiments for the cold vortex rainstorm process were conducted and the forecasting effects of the two methods were compared in various aspects. A time factor is introduced into the Neighborhood Probability (NP) method to evaluate the probabilistic forecasting results. It is detected that the Local-BGM can generate a more reasonable initial perturbation field than traditional BGM and has strong local characteristics. For the forecast of perturbation variables, the Local-BGM performs better in the aspects of root mean square error, spread, etc. Meanwhile the forecasting effect of each precipitation magnitude is also improved. The NP method can consider precipitation information of each ensemble member to obtain a better probabilistic forecast with higher Fractional Skill Score (FSS) than the ensemble mean forecasting result. After considering the time uncertainty, whether it is control forecasting, ensemble mean forecasting or neighborhood probability method, the FSS is greatly improved and the improvement is more obvious as the precipitation threshold increases. The spatiotemporal NP method can provide more objective probabilistic forecasting results for extreme precipitation weather.

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張海鵬,智協(xié)飛,李昊,黎振宇,張志強,黃晶.基于Local-BGM法的冷渦暴雨集合預報試驗及評估檢驗.氣象科學,2023,43(1):36-45 ZHANG Haipeng, ZHI Xiefei, LI Hao, LI Zhenyu, ZHANG Zhiqiang, HUANG Jing. The ensemble forecasting experiment and assessment of a cold vortex rainstorm based on Local-BGM. Journal of the Meteorological Sciences,2023,43(1):36-45

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收稿日期:2020-07-01
最后修改日期:2021-03-02
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在線發(fā)布日期: 2023-05-15
出版日期: 2023-02-15

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