GPS/PWV資料在梅雨鋒暴雨個(gè)例中的同化試驗(yàn)

doi:10.3969/2015jms.0017

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GPS/PWV資料在梅雨鋒暴雨個(gè)例中的同化試驗(yàn)
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                        10.3969/2015jms.0017
                    
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基金項(xiàng)目:國家重點(diǎn)基礎(chǔ)研究發(fā)展計(jì)劃(973計(jì)劃)項(xiàng)目(2015CB452801);國家重點(diǎn)基礎(chǔ)研究發(fā)展計(jì)劃(973計(jì)劃)項(xiàng)目(2013CB430100)

Assimilation Experiment of GPS/PWV Data in The Rainstrom Case of Meiyu Front

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基于WRF(Weather Research and Forecasting Model,天氣預(yù)報(bào)模式)及其三維變分同化系統(tǒng)3DVAR,利用江蘇省GPS/PWV(PWV:Precipitable Water Vapor,GPS反演得到可降水量)資料,并將其與探空資料比對(duì)訂正,針對(duì)2011年6月18日梅雨鋒暴雨進(jìn)行3h循環(huán)同化模擬。在降水參數(shù)化方案敏感性試驗(yàn)與單點(diǎn)同化試驗(yàn)基礎(chǔ)上,設(shè)計(jì)多組試驗(yàn)對(duì)6h降水量進(jìn)行TS(Threat Score)評(píng)估。結(jié)果表明:(1)同化訂正GPS/PWV資料對(duì)降水預(yù)報(bào)能力顯著提高,特別是大雨、暴雨量級(jí)以上的預(yù)報(bào)能力;(2)降水量的RMSE(Root Mean Squared Error,均方根誤差)相比控制試驗(yàn)均減小,CC(Correlation Coefficient,相關(guān)系數(shù))均增大,最顯著試驗(yàn)RMSE從19.1mm下降到12.6mm,CC從0.45上升到0.74;(3)NMC方法統(tǒng)計(jì)的背景誤差協(xié)方差條件下中雨至暴雨量級(jí)TS評(píng)分均有一定程度提高,默認(rèn)的背景誤差協(xié)方差在大雨以上量級(jí)TS評(píng)分大幅提高。

Abstract:

Based on WRF(Weather Research and Forecasting Model) and its three-demensional variational data assimilation system 3DVAR, three hours cycling assimilation experiments of Meiyu front rainstorm occured on June 18, 2011 are carried out with GPS/PWV(PWV:Precipitable Water Vapor) data which are corrected by comparing with sounding data. Based on the sensitivity researches of parameterization schemes for precipitation forecast and single point assimilation tests, several experiments are designed to assess 6 hour accumulated rainfall by TS scores(Threat Score). The results show that: (1) the capacity of precipitation forecast is significantly increased with the assimilation of the corrected GPS/PWV data, especially in heavy rain and torrential rain. (2) RMSE(Root Mean Squared Error) are reduced and CC(correlation coefficient) are increased by comparing with control tests. The RMSE drops from 19.1 mm to 12.6 mm and the CC increases from 0.45 to 0.74 in the most significant tests. (3) The TS scores are improved in the magnitudes from middle rain to torrential rain under the background error covariance derived from NMC method, while TS scores are improved significantly in the magnitudes beyond heavy rain under the default background error covariance.

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貝純純,李昕,王元,曹建奎,曾明劍. GPS/PWV資料在梅雨鋒暴雨個(gè)例中的同化試驗(yàn).氣象科學(xué),2016,36(2):149-157 BEI Chunchun, LI Xin, WANG Yuan, CAO Jiankui, ZENG Mingjian. Assimilation Experiment of GPS/PWV Data in The Rainstrom Case of Meiyu Front. Journal of the Meteorological Sciences,2016,36(2):149-157

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收稿日期:2014-12-17
最后修改日期:2015-03-10
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在線發(fā)布日期: 2016-06-13
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