基于OMOS方法的地面氣溫短時(shí)預(yù)報(bào)——以重慶市為例

doi:10.12306/2021jms.0104

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基于OMOS方法的地面氣溫短時(shí)預(yù)報(bào)——以重慶市為例
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                        10.12306/2021jms.0104
                    
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中圖分類號(hào):P456.7
基金項(xiàng)目:重慶市氣象局業(yè)務(wù)技術(shù)攻關(guān)重點(diǎn)（團(tuán)隊(duì)）項(xiàng)目（ywgg-201412）；中國氣象局河南省農(nóng)業(yè)氣象保障與應(yīng)用技術(shù)重點(diǎn)實(shí)驗(yàn)室開放研究基金（AMF202111）

Application of OMOS in short-term forecast of surface air temperature in Chongqing

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基于重慶市氣象局業(yè)務(wù)運(yùn)行的風(fēng)暴尺度快速同化和預(yù)報(bào)系統(tǒng)（Storm-Scale Rapid Assimilation and Forecast System，SSRAFS）、氣象信息綜合分析處理系統(tǒng)（Meteorological Information Comprehensive Analysis And Process System，MICAPS）地面觀測和高空觀測資料，進(jìn)行模式輸出統(tǒng)計(jì)（Model Output Statistics，MOS）方法和納入超前實(shí)況因子的MOS （MOS with Prior Observation Predictors，OMOS）方法對重慶地區(qū)地面氣溫96 h內(nèi)逐小時(shí)預(yù)報(bào)試驗(yàn)，并以SSRAFS地面氣溫預(yù)報(bào)結(jié)果作為參考進(jìn)行對比分析。結(jié)果表明：MOS方法在1~96 h預(yù)報(bào)時(shí)效內(nèi)的預(yù)報(bào)技巧高于SSRAFS，氣溫預(yù)報(bào)均方根誤差（Root Mean Square Error，RMSE）平均減小1.22℃，CC和HR2分別平均增大0.006和20.4%；在1~7 h預(yù)報(bào)時(shí)效，RMSE平均減小1.70℃，CC和HR2分別平均增大0.07和34.5%；且MOS方法在重慶東北部及中南部地區(qū)改進(jìn)效果較為明顯。OMOS方法在氣溫短期預(yù)報(bào)中表現(xiàn)優(yōu)于MOS方法，尤其在1~7 h預(yù)報(bào)時(shí)效，比MOS方法RMSE平均減小0.43℃，CC和HR2分別平均增大0.008和8.3%；其在1~4 h預(yù)報(bào)時(shí)效時(shí)表現(xiàn)更加優(yōu)異，與MOS方法相比，RMSE平均減小0.66℃，CC和HR2分別平均增大0.13和12.3%。因此，在MOS的基礎(chǔ)上，OMOS能夠進(jìn)一步提升地面氣溫的預(yù)報(bào)技巧，且在重慶東北部及中南部地區(qū)的預(yù)報(bào)效果有明顯改進(jìn)。

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Based on the Storm-Scale Rapid Assimilation and Forecast System (SSRAFS) operated by the Chongqing Meteorological Administration, along with MICAPS ground observation and upper-air observation data, this study conducted experiments on hourly surface air temperature forecasts within 96 hours for the Chongqing region. Model Output Statistics (MOS) and MOS with Prior Observation Predictors (OMOS) methods were utilized, and a comparative analysis was performed by using the SSRAFS surface air temperature forecasts as a reference. Results indicate that MOS outperforms SSRAFS in terms of forecasting skill for lead times ranging from 1 to 96 hours. On average, MOS reduces the RMSE of surface air temperature forecasts by 1.22℃, while increasing CC and HR2 by 0.006 and 20.4% respectively. For 1-7 h forecasts, MOS achieves an average decrease in RMSE of 1.70℃, and average increases in CC and HR2 of 0.07 and 34.5%, respectively. MOS exhibits a more noticeable improvement in the northeastern and south-central regions of Chongqing. Comparatively, OMOS performs better than MOS for short-term temperature forecasts, particularly within 1-7 h lead times, with an average decrease in RMSE of 0.43℃, and average increases in CC and HR2 of 0.008 and 8.3%, respectively. OMOS demonstrates even better performance during 1-4 h lead times, with an average decrease in RMSE of 0.66℃, and average increases in CC and HR2 of 0.13 and 12.3%, respectively, compared to MOS. Therefore, OMOS further enhances the forecasting skill of surface air temperature based on MOS, with significant improvements observed in the northeastern and south-central regions of Chongqing.

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王田,季焱,杜欽,朱壽鵬,智協(xié)飛.基于OMOS方法的地面氣溫短時(shí)預(yù)報(bào)——以重慶市為例.氣象科學(xué),2023,43(5):652-661 WANG Tian, JI Yan, DU Qin, ZHU Shoupeng, ZHI Xiefei. Application of OMOS in short-term forecast of surface air temperature in Chongqing. Journal of the Meteorological Sciences,2023,43(5):652-661

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收稿日期:2021-07-20
最后修改日期:2021-12-29
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在線發(fā)布日期: 2024-01-23
出版日期: 2023-10-15

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