General Atmospheric Circulation Studies

这一研究项目旨在改进对时间尺度超过一周的大气变异性的理解和预测。这种“低频变化”是由外部强迫(如在年度周期中)、大气内部的动力过程(如阻塞)以及大气与底层介质(主要是海洋混合层和陆地-地表水文)之间的相互作用产生的。该研究涉及使用合成、数字滤波、主成分分析、奇异值分解和聚类分析等统计技术对观测数据集进行诊断。根据目前对天气和气候系统的理论理解来解释结果。这项研究将涉及(1)探测和解释北半球温度和压力场的年际和年代际气候变率，(2)低频变率的非线性方面，包括北半球冬季环流是否表现出真正的双峰频率分布所表现出的独特的‘环流体制’的问题，(3)不同季节和世界海洋不同部分观测到的海面温度异常类型之间的关系；(4)气候学平均年循环的一些鲜为人知的方面；(5)扩展范围数值天气预报中的系统误差。这项研究很重要，因为它寻求提高我们对天气和气候过程的理解，因此有可能提高我们预测天气和气候的能力。

This research project is directed at improved understanding and prediction of atmospheric variability with time scales longer than a week. This 'low-frequency variability' is generated by external forcing (as in the annual cycle), dynamical processes internal to the atmosphere such as blocking, and by interactions between the atmosphere and the underlying media (primarily the oceanic mixed layer and the land-surface hydrology). The research involves the diagnosis of observational data sets using statistical techniques such as compositing, digital filtering, principal component analysis, singular value decomposition, and cluster analysis. Results are interpreted in light of the current theoretical understanding of weather and climate systems. The research will address (1) detection and interpretation of interannual and interdecadal climate variability in Northern Hemisphere temperature and pressure fields, (2) nonlinear aspects of low-frequency variability including the question of whether the Northern Hemisphere winter circulation exhibits distinct 'circulation regimes' manifested in truly bimodal frequency distributions, (3) relationships between patterns of sea-surface temperature anomalies observed in different seasons and in different parts of the world ocean, (4) some poorly understood aspects of the climatological mean annual cycle and (5) systematic errors in extended-range numerical weather prediction. This research is important because it seeks to improve our understanding of weather and climate processes and hence has the potential for improving our ability to predict weather and climate.