Climate System Dynamics on Long Time Scales

[摘要]加州大学洛杉矶分校michael gill研究气候变化的内因和外因问题。它强调了大气在数月至数年的气候变率中的作用，海洋在数年至数十年的变率中的作用，以及海洋-大气-冰盖耦合系统在数十年至数千年的气候变率中的作用。该方法使用了流体动力学、动力系统理论、科学计算和非参数统计等工具。动力学工具将应用于大气、海洋和耦合模式的层次。这些模式的范围从具有少量变量的最简单模式，例如海洋的箱形模式，到完全耦合的一般环流模式（GCMs）。pi将使用各种数学和统计技术研究气候子系统跨时间尺度的耦合。在10-100天的季内时间尺度上，指数将考虑对低频大气变率的两种互补描述，即偶发性和周期性，即多种天气状况和季内振荡。在100天到10年或更长时间的次年际尺度上，研究强调了中纬度海洋风力环流的内部变异性。这种环流研究了规定的时间常数和季节变化的风应力作用于海洋模式，以及完全耦合的海洋-大气模式。在几十年到几百年甚至更长的时间尺度上，pi将使用综合耦合模型，如CSM和IPSL。模拟结果将与仪器记录和古记录进行分析和比较，以确定和描述自然变率和人为气候变化在这些时间尺度上的相对重要性。这项工作很重要，因为它将增加对不同时间尺度气候变化的理解。

AbstractATM-0082131Ghil, MichaelUniversity of California, Los AngelesThe research bears on the problems of internal and external causes of climatic change. It emphasizes the role of the atmosphere in climate variability from months to years, of the oceans in variability from years to decades, and of the coupled ocean-atmosphere-ice-sheet system from decades to millennia. The methodology uses tools from fluid dynamics, dynamical systems theory, scientific computing and nonparametric statistics. The dynamical tools will be applied to a hierarchy of atmospheric, oceanic and coupled models. These models range from the simplest models with a small number of variables, such as box models of the ocean, to fully coupled general circulation models (GCMs).The PIs will study coupling of climate subsystems across timescales using various mathematical and statistical techniques. On the intraseasonal time scale of 10-100 days, the PIs will consider two complementary descriptions of low-frequency atmospheric variability, episodic and periodic, i.e. multiple weather regimes and intraseasonal oscillations. On the subannual-to-interannual time scale of 100 days to 10 or more years, the research emphasizes internal variability of the mid-latitude oceans' wind-driven circulation. This circulation is studied for prescribed time-constant and seasonally varying wind stress acting on ocean-only models, as well as for fully coupled ocean-atmosphere models. On time scales of decades-to-centuries and longer, the PIs will use comprehensive coupled models such as CSM and IPSL. The simulations will be analyzed and compared with instrumental and paleo-records to determine and describe the relative importance of natural variability and anthropogenic climate change on these time scales. The work is important because it will increase understanding of climate variability across various time scales.