GRAPES-TYM模式對(duì)我國(guó)東部近海海霧預(yù)報(bào)性能評(píng)估
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國(guó)家重點(diǎn)研發(fā)計(jì)劃(2019YFC1510102)、青島市氣象局海霧預(yù)報(bào)預(yù)警技術(shù)團(tuán)隊(duì)、山東省氣象局臺(tái)風(fēng)與海洋氣象創(chuàng)新團(tuán)隊(duì)資助


Assessment of Global/Regional Assimilation and Prediction System-Typhoon Model (GRAPES-TYM) for Sea Fog Prediction over Eastern China Seas
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    摘要:

    基于2020年上半年我國(guó)東部近海站點(diǎn)觀測(cè)資料和葵花8衛(wèi)星反演海霧產(chǎn)品對(duì)我國(guó)自主研發(fā)的GRAPES-TYM模式進(jìn)行了海霧預(yù)報(bào)性能評(píng)估。點(diǎn)、面檢驗(yàn)結(jié)果表明:模式48 h和72 h TS分別為0.40和0.36,黃海海霧預(yù)報(bào)性能最優(yōu),34°~37°N海域內(nèi)大部分站點(diǎn)TS高于0.50。黃海海霧落區(qū)預(yù)報(bào)檢驗(yàn)顯示均壓場(chǎng)形勢(shì)下預(yù)報(bào)最準(zhǔn)確,平均臨界成功指數(shù)為0.35;氣旋后部海霧多空?qǐng)?bào)。2 m相對(duì)濕度預(yù)報(bào)偏差具有局地性特征,相對(duì)濕度低估的站海霧預(yù)報(bào)擊中率、TS相對(duì)低,反之亦然。另外,模式對(duì)成霧相關(guān)氣象要素預(yù)報(bào)誤差相對(duì)小且對(duì)成霧有利時(shí)海霧預(yù)報(bào)基本正確;模式預(yù)報(bào)風(fēng)向較實(shí)際風(fēng)向偏東南,易出現(xiàn)冷偏差和濕偏差,虛假的有利溫濕條件導(dǎo)致海霧空?qǐng)?bào)。

    Abstract:

    Based on stational observations and retrieved sea fog products by the Kuihua-8 satellite from January to June 2020, this paper have evaluated the performance of the independent researched and developed GRAPES-TYM model to forecast sea fogs over the Eastern China Seas. Results indicate that sea fog forecasting for the Eastern China Seas by GRAPES-TYM is relatively promising, for TS of 48 h and 72 h is 0.40 and 0.36, respectively. Especially the model shows the best ability to predict the Yellow Sea sea fogs with TS of most stations in the sea area between 34°N and 37°N higher than 0.50. The further assessment indicates that the fog area forecast under the uniformed pressure field is more accurate, with an average CSI of 0.35. The model often gives false alarms when under the back of the cyclone. It appears that deviations between observed and forecasted surface air temperature and relative humidity are relative to locality. The hit rate and TS are lower with underestimating relative humidity, and vice versa. Our results also suggest that for successful cases, the model accurately captures the near-surface meteorological conditions, which are favourable for fog formation. In contrast, the model shows a large error in near-surface relative humidity and temperature for false alarm cases compared to successful cases. The predicted near-surface wind direction is often in the southeast of the actual wind direction, which is prone to introduce cold bias and overprediction of relative humidity. False favourable temperature and humidity conditions lead to false sea fog alarms.

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黃彬,高榮珍,時(shí)曉曚. GRAPES-TYM模式對(duì)我國(guó)東部近海海霧預(yù)報(bào)性能評(píng)估[J].氣象科技,2022,50(6):783~792

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  • 收稿日期:2021-12-01
  • 定稿日期:2022-08-22
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  • 在線發(fā)布日期: 2022-12-30
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