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

本研究利用统计工具对社区气候系统模式（CCSM）中化学成分输运的模拟进行了评价。评估气候模式表示组成气体输运能力的传统方法依赖于模拟输运和观测场的简单相关性和平均量分析。pi的新方法是使用离线化学模型，该模型包括与CCSM大气模型（CAM）中使用的平流、对流转移和边界层混合相同的表示（物理）。离线化学输运模型非常有效，可以在相对较短的计算机时钟时间内进行长时间模拟。将要开发的诊断工具将能够改进对模拟组分输送的时空变异性的分析，根据几十年的再分析数据进行测量，包括更好地评价模型结果的统计意义。更广泛的影响：提高气候模式模拟辐射活性微量气体大气输送的能力对未来气候预估很重要；有利于环境管理者和政策制定者努力理解和管理气候变化。许多大学气候科学家都在使用CCSM，他们应该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.