基于TIGGE多模式降水量預(yù)報(bào)的統(tǒng)計(jì)降尺度研究

doi:10.3969/2014jms.0058

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基于TIGGE多模式降水量預(yù)報(bào)的統(tǒng)計(jì)降尺度研究
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                        10.3969/2014jms.0058
                    
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基金項(xiàng)目:公益性行業(yè)(氣象)科研專項(xiàng)(GYHY200906009);中國氣象局公共氣象服務(wù)中心委托項(xiàng)目(CMAGJ2013M23);江蘇省高校優(yōu)勢(shì)學(xué)科建設(shè)工程資助項(xiàng)目(PAPD)

Statistical downscaling research of precipitation forecast based on TIGGE multimodel ensemble

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利用TIGGE資料中歐洲中期天氣預(yù)報(bào)中心、美國國家環(huán)境預(yù)報(bào)中心、英國氣象局以及日本氣象廳4個(gè)中心,1~7 d預(yù)報(bào)時(shí)效的降水量預(yù)報(bào)資料,以TRMM/3B42RT降水量作為"觀測(cè)值",對(duì)東亞地區(qū)降水量進(jìn)行統(tǒng)計(jì)降尺度處理。首先利用邏輯回歸方法將天氣分為有雨和無雨,再對(duì)有雨的情況,利用線性回歸方法對(duì)插值后的預(yù)報(bào)結(jié)果進(jìn)行降尺度訂正,最后將4個(gè)中心的預(yù)報(bào)值進(jìn)行消除偏差集合平均,得到多模式集成的降水量預(yù)報(bào)場。結(jié)果表明:邏輯回歸能夠有效地改善預(yù)報(bào)中小雨的空?qǐng)?bào)情況,統(tǒng)計(jì)降尺度訂正后的預(yù)報(bào)結(jié)果比直接插值更加準(zhǔn)確,多模式集成的預(yù)報(bào)效果優(yōu)于單模式結(jié)果,其改進(jìn)效果隨預(yù)報(bào)時(shí)效的延長逐漸減小。

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By taking the TRMM/3B42RT rainfall amount as "observed value", the 1-7 day's precipitation forecasting data from the European Centre for Medium-Range Weather Forecasts, the Japan Meteorological Agency, the National Centers for Environmental Prediction and the UK Met Office in the TIGGE datasets were used to statistically downscale the precipitation over East Asia(90-140 °E,15-45 °N). Firstly, the weather phenomenon was divided into rain and no-rain by logistic regression. Then, the linear regression was subsequently used to statistically downscale the interpolated precipitation forecast for rainy weather. Finally, the bias-removed ensemble mean was applied to gain the multimodel ensemble precipitation forecast. Results show that the logistic regression can effectively eliminate the false alarms for light and moderate rain; the forecasts by statistical downscaling are more accurate than that by interpolating. The multimodel ensemble forecast is superior to that by individual model in terms of the root-mean-square errors and the anomaly correlation coefficients of the precipitation forecasts, whose improvement effects decrease as forecast leading time increases.

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王海霞,智協(xié)飛.基于TIGGE多模式降水量預(yù)報(bào)的統(tǒng)計(jì)降尺度研究.氣象科學(xué),2015,35(4):430-437 WANG Haixia, ZHI Xiefei. Statistical downscaling research of precipitation forecast based on TIGGE multimodel ensemble. Journal of the Meteorological Sciences,2015,35(4):430-437

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收稿日期:2013-12-04
最后修改日期:2014-03-25
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在線發(fā)布日期: 2015-09-11
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