Sustainability is the contemporary philosophy for urban development which requires holistic consideration of the environmental, economic, and social dimensions. Global climate change is an important factor that affects sustainable urban development. On the one hand, climate change is posing various risks for the urban system and its supporting natural environment. On the other hand, different urban development plans have the potential to mitigate or amplify the adverse climate impacts. However, climate concerns often have a low impact on urban planning practice, due to the complexity of the system interactions. Therefore, a generic computational modeling framework is needed to address the causes and consequences of urban development plans, sustainability, and associated regional climate.The goal of this study is to build a coupled Human-Land-Atmospheric (HLA) modeling framework that supports urban sustainability assessment. The specific aims include (1) developing mid-term urban change scenarios and simulating their trajectories, (2) testing the sensitivity of regional climate to urban change trajectories, (3) assessing the impact of land cover data uncertainty on regional climate simulation, and (4) evaluating development strategies for sustainability from the climatic perspective. The city of Urumqi, China is selected as the case area for this study. Rapid economic and population growth are envisioned for the future of Urumqi, but its oasis environment is particularly vulnerable to future climate change and local disruptions.The coupled HLA modeling framework was constructed by combining statistical models for population, GDP, and urban area predictions, the Dyna-CLUE model which simulate land use change spatially, and the RAMS model which dynamically down-scales general circulation according to local land surface characteristics. Three urban development scenarios were developed based on different urban land demand models, yielding urban area increase of 20%, 70%, and 120%, respectively, from 2010 to 2030. Their spatial configurations were simulated using Dyna-CLUE. Local afforestation plans were later incorporated into the urban change scenarios. The land use prediction maps were then passed into RAMS to simulate their climatic consequences. The regional climate simulations were forced by the NASA-GISS-E2H General Circulation Model for the IPCC RCP 4.5 scenario in several hot years around 2030. The results were compared first among urban change scenarios and then with the RAMS simulations for the recent climate. The regional climate simulation results revealed interesting spatial patterns that associated to urban change scenarios, but the overall simulation quality was less than desirable. Finally, Urumqi's water supply/demand, agroclimatic resources, and agrometeorological risks were discussed based on literature, local statistics and simulated urban and climate change in an exploratory fashion.In conclusion, this study presented a coupled HLA modeling framework and an effort of evaluating sustainability-related topics using such framework. Although several research limitations prevent the specific results from supporting real-world decision-making, it made a constructive step towards a more comprehensive and scientifically founded sustainability assessment, especially for alternative urban development decisions. This framework can be expanded in the future to include more sustainability-related subsystems.
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