2012-03-012024-05-18https://scholars.lib.ntu.edu.tw/handle/123456789/711611摘要：本研究主要目的在於了解陸地水文過程對氣候的影響，並進一步改善氣候模式。相較於表層土壤水分與大氣之間的快速交互作用，地下水扮演相當重要的緩衝角色。然而，現今的陸地模式，由於缺乏完整的地下水與土壤水分相互作用的參數化過程，因而無法合理地模擬地下水對於氣候的影響，尤其是人類活動引起的地下水水位的改變（例如地下水抽取）對於大氣在空間與時間所扮演的角色。本研究將對於NCAR 陸地模式（Community Land Model, CLM）中的地下水模式進行優化，並結合NCAR 大氣模式（Community Atmosphere Model, CAM）來探討人類活動所引起的地下水變化對於區域和全球氣候的影響。 首先，本研究將針對現有的CLM 發展一套最佳的陸地模式參數，此參數將可因地制宜地適用於高度異質性的陸地區域。其次，利用衛星遙測（Gravity Recovery andClimate Experiment, GRACE）和全球陸地數據同化系統（Global Land Data AssimilationSystem, GLDAS）的模式輸出將可量化人類效應所引起之地下水變化，並將量化之結果加入CLM，於非耦合模式（offline simulations）中探討人類活動對於水文收支的影響。最後，以耦合的氣候模式（online simulations，即 NCAR 的Community EarthSystem Model, CESM) 來充分了解地下水在氣候系統中所扮演的角色。此一研究將建立一個完整且詳盡的地下水模型，而此一模型不僅可以優化CLM，更可用在不同的陸地模式中。另一方面，此模式將可評估人類活動所導致地下水的變化以及其對於氣候的回饋效應，並可用以預測全球未來的地下水資源，以及由於地下水抽取所造成的海平面上升的高度。此研究將改善既有模型之不足，對陸地水文研究提供新的進展。<br> Abstract: Understanding how land hydrological processes affect climate can help improve climate model simulations. Groundwater plays more important roles in modulating climate at longer time scales than the fast interactions associated with surface soil moisture. However, impacts of natural- and human-induced groundwater changes on the spatiotemporal variability of atmospheric hydrological variables have not been fully addressed. The major reason for this is a lack of a realistic physical groundwater representation in a global model that can realistically account for both natural and anthropogenic disturbances. This study will propose to explore impacts of natural- and human-induced groundwater changes on regional and global climate through model analyses. In order to achieve this goal, a realistic physical representation of soil moisture-groundwater interactions, and of human impacts on groundwater storage, are needed in global land models. This proposal will first develop optimal operating parameters for the existing groundwater model of the NCAR Community Land Model (CLM). Second, the remote sensing data (Gravity Recovery and Climate Experiment, GRACE) and Global Land Data Assimilation System (GLDAS) outputs will be used to quantify human induced groundwater changes, and incorporate into the CLM. Finally, a fully coupled atmosphere-land-groundwater model (i.e., NCAR Community Atmosphere Model (CAM) + CLM + groundwater model) with prescribed sea surface temperatures (SST) as well as with coupled ocean model will be utilized to fully understand the role of groundwater in the climate system. The expected results include the generation of a new groundwater model, that when coupled to CLM, can assess groundwater variations in response to related climate and human activities. Importantly, this work will open the door to more robust estimates of global change impacts on future groundwater resource, and of the impact of human groundwater use on the climate systems and sea level rise.衛星遙測氣候模式satellite remote sensingclimate model