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我国短期气候预测技术进展
引用本文:贾小龙,陈丽娟,高辉,王永光,柯宗建,刘长征,宋文玲,吴统文,封国林,赵振国,李维京.我国短期气候预测技术进展[J].应用气象学报,2013,24(6):641-655.
作者姓名:贾小龙  陈丽娟  高辉  王永光  柯宗建  刘长征  宋文玲  吴统文  封国林  赵振国  李维京
作者单位:国家气候中心,北京 100081
基金项目:资助项目:公益性行业(气象)科研专项(GYHY201306033),国家自然科学基金项目(41275073),973项目(2010CB428606),科技部科技支撑项目(2009BAC51B05)
摘    要:经过近60年的发展,我国短期气候预测技术和方法也有了长足进步。近年来,一些新的预报技术和机理认识不断应用于短期气候预测业务。ARGO海洋观测资料的使用大大提高了业务模式的预测技巧,新一代气候预测模式系统已经投入准业务化运行,研发了多种模式降尺度释用技术,多模式气候预测产品解释应用集成系统(MODES)和动力-统计结合的季节预测系统(FODAS)逐渐应用于业务中,大气季节内振荡(MJO)逐步在延伸期预报中得到应用。近年来,对全球海洋、北极海冰、欧亚积雪、南半球环流系统对东亚季风影响的新认识也不断引入到短期气候预测业务中。这些新技术和新认识的应用极大提高了我国短期气候预测的业务能力。

关 键 词:气候预测    气候模式    解释应用    东亚季风
收稿时间:4/8/2013 12:00:00 AM

Advances of the Short range Climate Prediction in China
Jia Xiaolong,Chen Liju,Gao Hui,Wang Yongguang,Ke Zongjian,Liu Changzheng,Song Wenling,Wu Tongwen,Feng Guolin,Zhao Zhenguo and Li Weijing.Advances of the Short range Climate Prediction in China[J].Quarterly Journal of Applied Meteorology,2013,24(6):641-655.
Authors:Jia Xiaolong  Chen Liju  Gao Hui  Wang Yongguang  Ke Zongjian  Liu Changzheng  Song Wenling  Wu Tongwen  Feng Guolin  Zhao Zhenguo and Li Weijing
Institution:National Climate Center, Beijing 100081
Abstract:Through the past 60-year development, the short-range climate prediction operation has made great progress in China in terms of the technology and methodology, undergoing the stages from the simple experiential statistic methods to numerical model. Especially in recent years, many objective prediction techniques and methods are well developed and applied in real-time operation. Meanwhile, many improved understanding and new knowledge of the climate system are also gradually used by climate forecasters.The ARGO (Array for Real-time Geostrophic Oceanography) global ocean data are applied in the global ocean data assimilation systems in NCC (NCC_GODAS), which enhances the monitoring and analyzing capability for the global ocean. The NCC_GODAS is integrated with coupled atmosphere-ocean models of NCC_CGCM, which increases the forecast skills for the short-term climate prediction. ARGO data are also applied for improving physical parameterization schemes in oceanic models, and the model capability of describing the real oceans and forecasting El Nio/Southern Oscillation is improved. The second-generation short-range climate forecast model, which upgrades many aspects of the resolution and physical process, exhibits a higher prediction skill comparing to the first-generation system. A preliminary evaluation indicates that the second-generation system shows a certain capability in predicting the pentad, ten-day, monthly, seasonal and inter-annual climate variability. The downscaling methods based on dynamical climate model are extensively used in operation including monthly prediction, seasonal prediction and extreme climate event prediction, improving the prediction skill of model production. Due to the limited predictability of a single model, multi-model ensemble (MME) is efficiently employed. Based on four operational dynamical models from NCC, NCEP, ECMWF and TCC, a multi-model ensemble system (MODES) is developed in NCC in 2011, in which downscaling technique is introduced and added to the ensemble prediction system. At present, this forecast system can issue monthly and seasonal ensemble prediction products and is applied by regional climate center. Based on the dynamical-statistical integration forecasting method, a forecasting system for seasonal precipitation (FODAS1.0) is developed, which has already been in quasi-operational use, showing stable prediction skill. The application of the intra-seasonal oscillation in the operational extended range forecast has made a great progress including that a MJO monitoring, prediction and application operational system is built up, and several forecast methods based on the intra-seasonal oscillation are applied. New knowledge and research achievements are gradually introduced into operation by forecaster, for example, in addition to the sea surface temperature (SST) in the equatorial mid-east Pacific, the SST in the Indian Ocean and the Atlantic Ocean are also seriously considered. In addition, the sea ice, snow cover over the Eurasia and the climate system in the Southern Hemisphere are also considered as the important impact factors in seasonal prediction.
Keywords:climate prediction  climate model  interpretation  East Asia Monsoon
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