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(EA)降水变化的人为和自然驱动因素，以及气候变化对生态系统和水资源的影响。青藏高原是亚洲主要水系的源头，这些水系养活了下游10亿多人。这项研究的结果将为地表水文学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。该EA研究的工具可用于全球和其他区域研究，在该项目中开发的最先进的模型将向研究界发布。该项目还将为一些教育宣传活动作出贡献。一个完全耦合的大气/海洋全球气候变化/生物物理和生物地球化学模式/动态植被模式，以：参照其中一个或多个过程和相互作用被忽略的预测，审查地表强迫，包括土地利用和土地覆被变化以及尘埃和黑碳效应及其双向相互作用对气候变化和变化的预测的改进；评估和确定这些因素和机制在气候变化中发挥的作用；检查这些过程对该区域气候未来预测的影响；并通过一系列实验估计不确定性。来自不同来源的数据，特别是来自青藏高原(TP)的观测数据，将被用于评估模型预测。此外，一个高分辨率的区域气候模式将被用来评估地表-大气相互作用对EA的气候和生态系统，特别是TP的影响的区域细节。通过在EASM中呈现关键的非线性反馈过程，该项目有可能极大地提高预测能力，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的气候变异性和变化做出贡献。

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.