中國(guó)地面氣溫自適應(yīng)遞減平均降尺度方法的改進(jìn)研究

doi:10.3969/2015jms.0045

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中國(guó)地面氣溫自適應(yīng)遞減平均降尺度方法的改進(jìn)研究
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                        10.3969/2015jms.0045
                    
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基金項(xiàng)目:公益性行業(yè)（氣象）科研專項(xiàng)（GYHY201006017）

Improvement research of decaying average statistical downscaling technique on surface temperature in China

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針對(duì)基于卡爾曼濾波類型的自適應(yīng)遞減平均降尺度方案對(duì)中國(guó)地面氣溫精細(xì)化預(yù)報(bào)中，原方案在強(qiáng)降溫天氣預(yù)報(bào)結(jié)果不理想的問(wèn)題，將其中只隨空間變化的遞減平均權(quán)重系數(shù)w（i）改進(jìn)為含有空間、天氣過(guò)程信息的自適應(yīng)函數(shù)w（i，p）（i為站點(diǎn)信息，p為天氣過(guò)程信息）；在此基礎(chǔ)上將上一次的強(qiáng)降溫日信息當(dāng)做預(yù)報(bào)前一天信息，應(yīng)用改進(jìn)w（i，p）遞減平均降尺度方案稱為w（i，p）相似法；而直接從強(qiáng)降溫歷史信息中統(tǒng)計(jì)插值預(yù)報(bào)與觀測(cè)值的系統(tǒng)性偏差均值，并用以修正預(yù)報(bào)結(jié)果的方法稱為w（i，p）統(tǒng)計(jì)法。結(jié)果表明：改進(jìn)為自適應(yīng)函數(shù)w（i，p）后的降尺度方案對(duì)中國(guó)地面氣溫的預(yù)報(bào)效果有不同程度的改善，對(duì)于24 h強(qiáng)降溫預(yù)報(bào)，采用w（i，p）降尺度方案的預(yù)報(bào)誤差均方差較原方案減小了0.19℃；而進(jìn)一步改進(jìn)的w（i，p）相似法與w（i，p）統(tǒng)計(jì)法的預(yù)報(bào)誤差均方差分別減小了1.12℃、1.45℃，改進(jìn)效果顯著。

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In order to improve forecasting accuracy in cooling day, a fine forecast test is designed by using self-adapting Kalman Filter-typed decaying average statistical downscaling technique on surface temperature in China. Decaying weight w, defined as an only spatially variant function w(i) in decaying average statistical downscaling technique, was redefined as spatially and synoptic process variant function w(i,p) in this research where i represents station information and p represents synoptic process information. Selecting the similar weather information from history to find the law of cooling day is defined as the similarity decaying average statistical downscaling technique, while collecting systematic bias from interpolation method to modify forecasting result is defined as statistics decaying average statistical downscaling technique. Results show that the improved w(i,p) decaying average statistical downscaling technique performs better than the original method. The averaging Root Mean Square Error(RMSE) of 24 h intense cooling process day forecast decreases by 0.19℃ by using w(i,p) decaying average statistical downscaling technique, while the averaging RMSE decreases by 1.45℃ by using w(i,p) statistics decaying average statistical downscaling technique, respectively, which means significant improvement effect.

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肖瑤,郭品文.中國(guó)地面氣溫自適應(yīng)遞減平均降尺度方法的改進(jìn)研究.氣象科學(xué),2016,36(5):606-613 XIAO Yao, GUO Pinwen. Improvement research of decaying average statistical downscaling technique on surface temperature in China. Journal of the Meteorological Sciences,2016,36(5):606-613

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收稿日期:2015-01-12
最后修改日期:2015-04-22
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在線發(fā)布日期: 2016-11-01
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抽查舔水白紧大视频,冲喜娘子超甜哒激情五月,亚洲黄色图片偷拍网站,亚洲三级黄片免费播放,91在线观看喷潮红桃,日韩精品在线观看一区二区,久久久久久久久久久久黄色片子,日产精品99久久久久久久久,欧洲亚洲另类图片小说