| GRAPES_SDM沙尘模式在新疆的客观检验 |
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| 引用本文： | 段海霞,李耀辉,霍文,秦贺,马玉芬.GRAPES_SDM沙尘模式在新疆的客观检验[J].中国沙漠,2016,36(2):441-448. |
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| 作者姓名： | 段海霞 李耀辉 霍文 秦贺 马玉芬 |
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| 作者单位： | 1. 中国气象局兰州干旱气象研究所, 甘肃省(中国气象局)干旱气候变化与减灾重点(开放)实验室, 甘肃 兰州 730020;<2r>2. 中国气象局乌鲁木齐沙漠气象研究所, 新疆 乌鲁木齐 830002;<2r>3. 新疆维吾尔自治区气象台, 新疆 乌鲁木齐 830002 |
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| 基金项目： | 中国沙漠气象科学研究基金项目(Sqj2012003) |
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| 摘 要： | 使用天气学检验方法,对新疆2008-2013年春季沙尘天气GRAPES_SDM沙尘模式预报情况进行检验评估,通过TS、预报效率等检验统计量分析了在新疆的预报效果,通过平均误差、均方根误差、误差标准差等格点误差和站点误差量的分析,分析了主要预报要素的客观检验结果,指出近地面气温和风速的误差为初始条件的不确定以及观测和预报分辨率尺度不一致造成的随机性误差。在此基础上给出了新疆南疆盆地和新疆东部地区数值预报业务的误差特征,并根据检验结果定性地分析了模式预报系统性和非系统性误差的可能来源。
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| 关 键 词： | GRAPES_SDM TS评分 平均误差 均方根误差 |
| 收稿时间： | 2014-11-02 |
| 修稿时间： | 2015-01-12 |
Objective Verification of GRAPES_SDM Model in Xinjiang,China |
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| Duan Haixia,Li Yaohui,Huo Wen,Qin He,Ma Yufen.Objective Verification of GRAPES_SDM Model in Xinjiang,China[J].Journal of Desert Research,2016,36(2):441-448. |
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| Authors: | Duan Haixia Li Yaohui Huo Wen Qin He Ma Yufen |
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| Institution: | 1. Key Laboratory of Arid Climatic Change and Reducing Disaster of Gansu Province/Key Open Laboratory of Climatic Change and Disaster Reduction of CMA, Institute of Arid Meteorology, China Meteorological Administration, Lanzhou 730020, China;2. Institute of Desert Meteorology, China Meteorological Administration, Urumqi 830002, China;3. Xinjiang Meteorological Observatory, Urumqi 830002, China |
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| Abstract: | By comparing the forecast product by the GRAPES_SDM model and the observed data of dust-storm weather in Xinjiang in the springs of 2008-2013, we tested the forecast product with synoptic verification method. By analyzing mean error, error standard deviation and root-mean-square error, the characteristics of error distribution of numerical forecast in Xinjiang are shown, and the possible sources of the systematic and non-systematic error are analyzed. The results showed that the 2-m height air temperature and 10-m height wind speed error mainly came from the uncertainty of the initial conditions and the inconsistencies of the resolution of observation and prediction. We also proposed some suggestions on improving the GRAPES_SDM model forecast accuracy. |
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| Keywords: | GRAPES_SDM Model TS score mean error root-mean-square error |
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