非降水回波同化在臺風(fēng)"山竹"數(shù)值預(yù)報中的應(yīng)用

doi:10.12306/2024jms.0036

首頁 > 過刊瀏覽>2024年第44卷第6期 >1003-1015. DOI:10.12306/2024jms.0036

非降水回波同化在臺風(fēng)"山竹"數(shù)值預(yù)報中的應(yīng)用
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                        10.12306/2024jms.0036
                    
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中圖分類號:P412.25;P456.7
基金項目:國家自然科學(xué)基金資助項目(42192553)

Application of no-rain echo data assimilation in the forecast of Typhoon "Mangkhut"

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我國是世界上受臺風(fēng)影響最多的國家之一,臺風(fēng)強度和登陸前后精細(xì)降水預(yù)報一直是業(yè)務(wù)難題,因此數(shù)值模式就成為重要的預(yù)報工具,但由于多種因素的影響,高分辨率模式容易出現(xiàn)虛假對流,從而引起降水的空報情況。本文針對臺風(fēng)雷達資料同化中未充分同化大范圍低反射率區(qū)域非降水回波問題,利用多普勒岸基天氣雷達對精細(xì)風(fēng)場和水凝物分布有高時空觀測的特點,基于廣州和陽江兩部S波段多普勒雷達的徑向風(fēng)速和反射率因子資料,通過WRF及其3DVAR系統(tǒng),進行非降水回波同化試驗,研究該同化方法在臺風(fēng)天氣過程中的預(yù)報效果。對2018年強臺風(fēng)"山竹"進行資料同化和數(shù)值模式模擬,結(jié)果表明,非降水回波同化降低了氣旋性風(fēng)場增量和水汽增量,減小了臺風(fēng)北部螺旋雨帶和海南地區(qū)的組合反射率,抑制了模式的虛假對流,使臺風(fēng)的強度、結(jié)構(gòu)與雷達觀測更接近。同時非降水回波同化還增大了臺風(fēng)中心的最小海平面氣壓,顯著改進了臺風(fēng)最小海平面氣壓12 h的模擬效果,降低了廣東北部和海南島北部的過量降水模擬,改進了6 h降水模擬的TS評分和FAR評分,有效減少了常規(guī)反射率同化試驗的降水空報情況。

Abstract:

China is one of the countries most affected by typhoons in the world. The intensity of typhoons and the detailed precipitation forecast before and after landing have always been challenging issues in operational forecasting. Therefore, numerical models have become important forecasting tools. However, high-resolution models are prone to false convection due to various factors, leading to false reports of precipitation. This paper addressed the issue of insufficient assimilation of no-rain echoes in large areas of low reflectivity in typhoon radar data assimilation. Utilizing the high temporal and spatial observation characteristics of Doppler shore-based weather radar for detailed wind fields and hydrometeor distribution, based on the radial wind speed and reflectivity factor data of two S-band Doppler radars in Guangzhou and Yangjiang, through the WRF and its 3DVAR system, no-rain echo assimilation experiments were conducted to research whether this assimilation method can effectively suppress false precipitation in the model during typhoon weather processes. For the strong Typhoon "Mangkhut" in 2018, data assimilation and numerical model forecasting were carried out. Results show that the assimilation of no-rain echoes reduces the cyclonic wind field increment and water vapor increment, reduces the combined reflectivity of the typhoon's no-rthern spiral rain belt and Hainan area, suppresses the model's false convection, and makes the typhoon's intensity and structure closer to radar observations. At the same time, the assimilation of no rain echoes also increases the minimum sea level pressure of the typhoon center, significantly improves the 12 h forecast of the typhoon's minimum sea level pressure, reduces the excessive precipitation forecast in the northern part of Guangdong and the northern part of Hainan Island, improves the TS score and FAR score of the 6 h precipitation forecast, and effectively reduces the false precipitation report situation of the conventional reflectivity assimilation experiment.

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周凡皓,閔錦忠.非降水回波同化在臺風(fēng)"山竹"數(shù)值預(yù)報中的應(yīng)用.氣象科學(xué),2024,44(6):1003-1015 ZHOU Fanhao, MIN Jinzhong. Application of no-rain echo data assimilation in the forecast of Typhoon "Mangkhut". Journal of the Meteorological Sciences,2024,44(6):1003-1015

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收稿日期:2024-03-25
最后修改日期:2024-05-15
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在線發(fā)布日期: 2025-01-08
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