人类活动对气候变化的影响：减少数值模拟不确定性的方法及其应用研究

项目名称： 人类活动对气候变化的影响：减少数值模拟不确定性的方法及其应用研究

项目编号： No.41330527

项目类型： 重点项目

立项/批准年度： 2014

项目学科： 天文学、地球科学

项目作者： 董文杰

作者单位： 北京师范大学

项目金额： 280万元

中文摘要： 利用数值模拟方法研究人类活动对气候变化影响时所要模拟的两类状态中，有一类状态是有观测和分析资料的，实际上是已知的。针对这类问题本项目提出可采用分段积分方法代替传统的连续积分模拟方法，这种分段积分方法通过不断地再初始化将已知的分析场引入模拟过程，避免因长期时间积分后模式和初始场误差造成的模拟状态的严重漂移，从而减少模拟结果的不确定性。在用于模拟的气候模式上建立基于动力张弛技术的资料同化系统来产生再初始化需要的分析场，避免再初始化可能产生的振荡。利用NCAR/CESM和BNU-ESM模式采用上述方法模拟研究近60年来温室气体排放和土地利用/覆盖变化对全球气候变化的贡献，并和传统模拟方法的模拟结果进行比较，期望能更清晰地揭示最近半个多世纪来人类活动对气候变化影响的幅度和机理，也期望通过这一探索使这一模拟研究方法在真实的气候系统模式中得以实现，显著减小地球系统模式数值模拟的不确定性。

中文关键词： 气候变化;人类活动;数值模拟;不确定性;

英文摘要： In the two statuses required to simulate in the numerical simulation studies to identify the effects of anthropogenic forcing on climate change, the observation or analyses data for one status are often available.For this kind of subject,this project proposes a piecewise integration method to replace the traditionally continuous integration method in the numerical simulation. In this novel method, the given observed information will be lead into the simulation through re-initialization to avoid the climate state shift in the numerical simulation due to the fast increase of initial error and model error in a long-time integration and reduce uncertainty in the simulations. In order to avoid the oscillation in the re-initialization, a nudging-based data assimilation system will be established for the climate models to produce the analyses data required by the re-initialization. Based on the proposed method, two climate models (NCAR/CESM and BUN-ESM) will be utilized to perform numerical experiments to evaluate the contributions of greenhouse gas emission and land use to global climate change during the past 60 years. The simulation results will be compared with other simulation results based on standard simulation method. The research will contribute to reduce the uncertainty in the climate simulation study and reveal more clearly the strength and mechanism of the influence of human activity on climate change.

英文关键词： climate change;human activities;numerical simulation;uncertainty