SGER: Evaluation of Community Climate System Model (CCSM) Constituent Transport Variability

本研究使用统计工具对社区气候系统模式(CCSM)中的化学成分输送模拟进行评估。传统的评估气候模式描述组成气体输送能力的方法依赖于对模拟输送和观测场的简单相关和平均值分析。PIS的新方法是使用离线化学模式，该模式包括与CCSM大气模式(CAM)相同的对流、对流输送和边界层混合的表示(物理)。离线化学传输模型非常有效，能够在相对较短的计算机时钟时间内进行长时间模拟。将开发的诊断工具将能够改进对模拟成分运输的空间和时间变异性的分析，对照数十年的再分析数据进行衡量，包括更好地评估模型结果的统计意义。更广泛的影响：提高气候模型模拟具有辐射活性的痕量气体在大气中传输的能力，对于未来的气候预测非常重要；环境管理人员和政策制定者在努力了解和管理气候变化方面是有益的。CCSM被许多大学气候科学家使用，他们应该会从这项研究的结果中受益。

This research uses statistical tools to evaluate the simulation of chemical constituent transport in the Community Climate System Model (CCSM). Traditional methods for evaluating the ability of climate models to represent the transport of constituent gases rests on simple correlation and mean quantity analyses of simulated transports and observed fields. The new approach of the PIs is to use an off-line chemical model that includes the same representations (physics) for advection, convective transfer and boundary layer mixing as used in the CCSM atmospheric model (CAM). The off-line chemical transport model is very efficient, enabling long simulations in relatively short computer wall-clock time. The diagnostics tools to be developed will enable improved analyses of the spatial and temporal variability of the simulated constituent transports, as measured against decades of reanalysis data, including better evaluations of the statistical significance of the model results. Broader Impacts:Improvements in the ability of climate models to simulate the atmospheric transport of radiatively active trace gases is important for future climate projections; a benefit for environmental managers and policy makers in their efforts to understand and manage climate change. The CCSM is used by many university climate scientists who should benefit through the results of this research.