SGER: Role of the Indian Ocean in Causing the Excessive Biennial El Nino-Southern Oscillation (ENSO) Tendency in NCAR's Community Climate Modeling System (CCSM3) Simulations

许多耦合的气候模式完全代表了大气和海洋，但无法准确模拟厄尔尼诺/南方涛动(ENSO)现象的空间结构和时间演变。ENSO是气候变化的主要模式，它影响着世界大部分地区的天气和气候。国家大气研究中心(NCAR)的社区气候系统模式(CCSM3)的当前版本产生了ENSO变化，但具有不切实际的两年或两年一次的周期。在用于预测全球气候变化的主要模型之一中，这一缺陷降低了此类预测的可靠性及其对预测区域气候变化的效用。基于他早期的模型研究，PI假设ENSO中这种不切实际的时间变化是热带太平洋和印度洋之间相互作用的结果。他将通过进行模型实验来检验这一假设，在模型实验中，不是模拟印度洋的海面温度，而是施加该盆地的温度；施加的温度将遵循生成的模型和观察到的年度周期。如果在这些实验中减少或消除ENSO的过度两年变率，将表明印度洋气候在整个模式中是问题的一个重要来源。这项工作将有助于纠正广泛使用的最先进气候模型中的一个重要问题，并将有助于培训一名研究生研究助理。

Many coupled climate models, those with full representations of the atmosphere and ocean, are unable to simulate accurately the spatial structure and time evolution of the El Nino/Southern Oscillation (ENSO) phenomenon. ENSO is a leading mode of climate variability that affects regional weather and climate over much of the world. The current version of the Community Climate System Model (CCSM3) at the National Center for Atmospheric Research (NCAR) produces ENSO variability, but with an unrealistically strong two-year, or biennial, cycle. This deficiency, in one of the leading models used for projections of global climate change, reduces the reliability of such projections and their utility for predicting changes in regional climates. Based on his earlier model studies the PI hypothesizes that this unrealistic temporal variability in ENSO is a result of interactions between the tropical Pacific and Indian Oceans. He will test this hypothesis by conducting model experiments in which, rather than simulating sea-surface temperatures in the Indian Ocean, temperatures in this basin are imposed; the imposed temperatures will follow both a model generated and an observed annual cycle. If the excessive biennial variability of ENSO is reduced or eliminated in these experiments, it will indicate that the Indian Ocean climate is a significant source of the problem in the full model. This work will help to correct an important problem in a widely used, state-of-the-art, climate model and will contribute to training a graduate research assistant.