doi:  10.3878/j.issn.1006-9895.1803.17252
青藏高原积雪深度对延伸期预报技巧的影响

Influence of the Tibetan Plateau Snow Depth on the Extended-Range Prediction Skill
摘要点击 265  全文点击 249  投稿时间:2017-10-12  
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基金:  国家重点研发计划项目2017YFC1502303,国家自然科学基金项目41875101,41475096,国家科技支撑计划项目2015BAC03B04,气象预报业务关键技术发展专项YBGJXM(2017)04、YBGJXM(2018)04,科技部公益性行业(气象)科研专项项目GYHY201506014,河北省气象局科研开发项目17ky03
中文关键词:  青藏高原  积雪深度  延伸期预报  模式评估
英文关键词:  The Tibetan Plateau  Snow depth  Extended-range prediction  Model evaluation
                    
作者中文名作者英文名单位
韩世茹HAN Shiru河北省气候中心, 石家庄 050021
郑志海ZHENG Zhihai国家气候中心中国气象局气候研究开放实验室, 北京 100081;珠海区域气候-环境-生态预测预警协同创新中心, 广东珠海 519087
周须文ZHOU Xuwen河北省气候中心, 石家庄 050021
于长文YU Changwen河北省气候中心, 石家庄 050021
车少静CHE Shaojing河北省气候中心, 石家庄 050021
顾光芹GU Guangqin河北省气候中心, 石家庄 050021
卓嘎ZHUO Ga西藏自治区气候中心, 拉萨 850000
引用:韩世茹,郑志海,周须文,于长文,车少静,顾光芹,卓嘎.2019.青藏高原积雪深度对延伸期预报技巧的影响[J].大气科学,43(1):142-154,doi:10.3878/j.issn.1006-9895.1803.17252.
Citation:HAN Shiru,ZHENG Zhihai,ZHOU Xuwen,YU Changwen,CHE Shaojing,GU Guangqin,ZHUO Ga.2019.Influence of the Tibetan Plateau Snow Depth on the Extended-Range Prediction Skill[J].Chinese Journal of Atmospheric Sciences (in Chinese),43(1):142-154,doi:10.3878/j.issn.1006-9895.1803.17252.
中文摘要:
      高原积雪是重要的陆面因子,其变化的时间尺度长于大气而短于海洋。本文利用国家气候中心第二代月动力延伸期预测模式(DERF2.0)历史回报资料与被动微波资料(SMMR)、被动微波成像专用传感器(SSM/I)数据反演的逐日雪深资料,分析了1983~2014年冬季和春季转换季节高原积雪对热带外地区延伸期尺度预测技巧的影响。结果表明,高原积雪异常年动力模式在高原积雪显著影响的青藏高原地区、贝加尔湖地区和北太平洋地区预报技巧明显高于正常年份。随着预报时效的延长,高原积雪偏多年的技巧衰减最慢、其次为积雪偏少年,积雪正常年最快,表明高原积雪异常年可预报时效更长,且高原积雪异常对预报技巧的改善在第1候的预报中就显现出来,尤其是积雪偏多年,其影响时段明显要早于海洋。结果显示高原积雪对延伸期预报技巧有重要贡献,暗示高原积雪异常为东亚延伸期预报的潜在可预报源。
Abstract:
      The Tibetan Plateau snow cover is an important land surface factor, whose time scale of change is longer than that of the atmosphere and shorter than that of the ocean. This study analyzes the influence of the Tibetan Plateau snow depth anomaly onextended-range prediction technique over extratropical regions. The reforecast data from DERF2.0 (Dynamic Extended Range Forecast 2.0) model provided by the National Climate Center of China and the daily snow depth data inversion calculated by scanning multichannel microwave radiometer (SMMR) and special sensor microwave imager (SSM/I) from 1983 to 2014 are used. The results show that the skill in extended prediction of DERF2.0 is much higher in abnormal years than in normal years, especially over regions significantly affected by snow cover in the Tibetan Plateau like the Tibetan Plateau region, Lake Baikal region and the North Pacific region. With the extension of the forecast lead time, the skill in extended prediction at tenuates the slowest in more-snow years and attenuates the fastest in normal snow years. The above result shows that the predictable time is longer in abnormal years of the Tibetan Plateau snow. The skill in extended prediction is improved, which can be seen from the first pentad in the Tibetan Plateau snow abnormal years, especially in more-snow years. The influence of the snow cover is obviously earlier than that of the ocean. The Tibetan Plateau snow cover has an important contribution to the skill in extended prediction, suggesting that the Tibetan Plateau snow anomaly is a potential source of prediction for extended-range prediction in East Asian.
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