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Exploring historical and future urban climate in the Earth System Modeling framework: 1. Model development and evaluation
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2016
Source: Journal of Advances in Modeling Earth Systems 8(2), 917-935, 2016
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Journal Title:Journal of Advances in Modeling Earth Systems
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Description:A number of recent studies investigated impacts of Land-Use and Land-Cover Changes (LULCC) on climate with global Earth System Models (ESMs). Yet many ESMs are still missing a representation of the most extreme form of natural landscape modification - urban settlements. Moreover, long-term (i.e., decades to century) transitions between build-up and other land cover types due to urbanization and de-urbanization have not been examined in the literature. In this study we evaluate a new urban canopy model (UCM) that characterizes urban physical and biogeochemical processes within the subgrid tiling framework of the Geophysical Fluid Dynamics Laboratory (GFDL) land model, LM3. The new model LM3-UCM is based on the urban canyon concept and simulates exchange of energy, water (liquid and solid), and carbon between urban land and the atmosphere. LM3-UCM has several unique features, including explicit treatment of vegetation inside the urban canyon and dynamic transition between urban, agricultural and unmanaged tiles. The model is evaluated using observational data sets collected at three urban sites: Marseille in France, Basel in Switzerland and Baltimore in the United States. It is found that LM3-UCM satisfactorily reproduces canyon air temperature, surface temperatures, radiative fluxes, and turbulent heat fluxes at the three urban sites. LM3-UCM can capture urban features in a computationally efficient manner and is incorporated into the land component of GFDL ESMs. This new capability will enable improved understanding of climate change effects on cities and the impacts of urbanization on climate.
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Source:Journal of Advances in Modeling Earth Systems 8(2), 917-935, 2016
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Rights Information:CC BY-NC-ND
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Compliance:PMC
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Main Document Checksum:urn:sha256:d7f768c56f1adac62a229c96415740a2f5b35ee3bd2ea2c6dcd1806b0d11595f
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