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Physical Basis of Short-term Climate Prediction in China and Short-term Climate Objective Prediction Methods
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摘要: 短期气候预测依据大气科学原理，运用气候动力学、统计学等手段，在研究气候异常成因的基础上对未来气候趋势进行预测。虽然目前我国短期气候预测的水平还不高，但短期气候预测是国家经济发展和防灾减灾的迫切需求，提高预测准确率是气象科研和业务人员的重要任务。该文从海洋、积雪等外强迫信号及大气环流大尺度变动等大气内部特性等角度概述了短期气候预测的物理基础，简要回顾了近60年来我国短期气候预测的发展历程，并介绍了作者近十几年来研制短期气候预测客观统计学及统计与动力学相结合预测模型的主要思路。Abstract: Short-term climate prediction means forecasting monthly, seasonal, and inter-annual climate trends in the future based on the principles of atmospheric science by using climate dynamics, statistics and other means. Although many researches on the short-term climate prediction have been implemented, the prediction capability is far from meeting the demands of the national economy development. A brief review of the progress in China has been made on the short-term climate prediction in recent 60 years. The physical basis of short-term climate prediction, including the external forcing and internal characteristics of the atmosphere is described. Several new short-term climate objective prediction methods are proposed and their applications to operational prediction are introduced.The ElñNio/La Niña phenomenon and snow cover over the Tibetan Plateau in winter are two important external forcing factors for short-term prediction in China. The large-scale atmospheric circulation patterns, for example, North Atlantic Oscillation (NAO), North Pacific Oscillation (NPO), Southern Oscillation (SO) and Arctic Oscillation (AO), are also important physical foundation for short-term climate prediction. Since the 1990s, numerical climate models have made rapid progress, and statistical downscaling method is also an important way to improve the accuracy of short-term climate prediction. In recent years, role of inter-decadal variability in short-term climate prediction are also attracting great attentions.
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Key words:
- short-term climate prediction;
- physical basis;
- prediction method
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图 1 淮河流域不同气候时段海表温度年代际分量平均值的差值分布
(阴影部分表示差值超过0.05显著性水平) (a) 1943—1964年与1922—1942年，(b) 1965—1997年与1943—1964年
Fig. 1 Difference of SST interdecadal sector between different climate periods of summer precipitation over Huaihe River Valley
(shaded area denotes passing the test of 0.05 level) (a) 1943—1964 and 1922—1942, (b) 1965—1997 and 1943—1964
图 2 青藏高原冬季积雪偏多年份 (a) 和偏少年份 (b) 我国夏季降水距平百分率合成分布
Fig. 2 Percentage anomalies of summer precipitation in China during rich snow years (a) and deficient snow years (b) in Tibetan Plateau
图 3 我国东部夏季降水年代际变化的时间-纬度剖面图
Fig. 3 The time-latitude cross section of interdecadal oscillation of summer precipitation in the east of China
图 4 长江中下游夏季降水与AO的30年滑动相关系数
Fig. 4 The 30-year running correlation coefficients between summer precipitation over the mid-lower reaches of the Yangtze and AO
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