Ea SM-3: Collaborative Res: Surface-induced Forcing and Decadal Variability and Change of the East Asian Climate, Surface Hydrology & Agriculture-A Modeling and Data Approach

该项目将有助于确定东亚降水变化归因于人为和自然驱动因素，以及气候变异对生态系统和水资源的影响。青藏高原是亚洲主要河流系统的源头，为下游10亿多人提供支持。这项研究的结果将为地表水文和农业提供有用的信息，这对世界上人口众多、经济活跃的地区至关重要。本EA研究的工具可用于全球和其他区域研究，本项目中开发的最先进模型将发布给研究界。这一项目还将促进一些教育推广活动。一个完全耦合的大气/海洋GCM/生物物理和生物地球化学模式/动态植被模式，以：参照忽略一个或多个过程和相互作用的预测，审查对EA气候变率和由于地表引起的强迫引起的变化的预测的改进，包括土地利用和土地覆盖变化以及灰尘和黑碳效应及其双向相互作用;评估和属性的作用，在EA气候变率的这些因素和机制;检查这些过程对该区域气候的未来预测的影响;并估计通过一系列实验的不确定性。来自不同来源的数据，特别是来自青藏高原（TP）的观测数据，将用于评估模式的预测。此外，一个高分辨率的区域气候模式将被应用于评估的地面-大气相互作用对EA的气候和生态系统的影响，特别是TP的区域细节。通过在EaSM的关键非线性反馈过程的代表性，该项目有可能大大提高预测能力，并进一步解释不同的地球过程和人类活动如何在上个世纪的大部分时间里对EA气候变率和变化做出贡献。

This project will contribute to identifying the attribution of East Asian (EA) precipitation changes to anthropogenic and natural drivers and the effects of climate variability on the ecosystem and water resources. The Tibetan Plateau is the source of major Asian river systems that support more than a billion people downstream. The results from this study will provide useful information for surface hydrology and agriculture, critical for a populous and economically vibrant part of the world. The tools for this EA study can be used for global and other regional studies and the state-of-the-art models developed in this project will be released to the research community. This project will also contribute to a number of educational outreach activities. A fully-coupled Atmospheric/Ocean GCM/biophysical and biogeochemical models/dynamic vegetation model to: examine the improvements in predictions of EA climate variability and change due to surface-induced forcings, including land use and land cover change (LULCC) and dust and black carbon effects and their two-way interactions in reference to predictions in which one or more of those processes and interactions are neglected; to evaluate and attribute the role played in the EA climate variability by these factors and mechanisms; to examine the effects of those processes on future projections of that regional climate; and to estimate uncertainty through a set of experiments. Data from different sources, especially from observations in the Tibetan Plateau (TP), will be applied to evaluate model predictions. In addition, a regional climate model with high resolution will be applied to assess the regional details of effects of surface-atmosphere interactions on the climate and ecosystem of EA, the TP in particular. Through the representation of key non-linear feedback processes in the EaSM, this project has the potential to substantially improve predictive capabilities and to further explain how different Earth processes and human activities have contributed to EA climate variability and changes over much of the last century.