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Inclusion of Urban Landscape in a Climate Model: How Can Satellite Data Help?

Reference Type
Journal, Research (Article)

"Urban regions, which cover only approximately 0.2% of the earth’s land surface, contain about half of the human population (UNPD 2001). Modeling urban weather and climate is critical for human welfare, but has been hampered for at least two reasons: i) no urban landscape has been included in global and regional climate models (GCMs and RCMs, respectively), and ii) detailed information on urban characteristics is hard to obtain. With the advance of satellite observations, adding urban schemes into climate models in order to scale projections of global/regional climate to urban areas becomes essential. Inclusion of urbanized landscape into climate models was discussed in depth at the fall American Geophysical Union (AGU) meeting of 2003 in the session entitled "Human-induced climate variations linked to urbanization: From observations to modeling," which took place on 12 December 2003 in San Francisco, California (most of the presentations of this session can be found online at www.atmos.umd.edu/~mjin/AGU03urban.html). The following notes summarize what is known and what needs to be advanced on this topic." [Introduction to the meeting summary]

Discusses (advocates) for a more complete climate model and urban landscape scheme which includes measures of landscape roughness. The urban land surface model uses LAI (leaf area index) and fractional vegetation cover (e.g. canopy cover). By replacing original vegetated surface with buildings, roads, or parking lots, LAI and fractional vegetation cover are dramatically reduced.

Authors
M. Jin, J.M. Shepherd
Date Published
2005
Journal/Conference
Bulletin of the American Meteorological Society (BAMS)
Publisher
American Meteorological Society
Publisher Location
Boston, MA (US)
ISBN/ISSN
1520-0477
Volume/Issue/Number
86/may 2005/5
Start Page
681
End Page
689
Pages
9
Sub-Topics
Air Quality/Pollution, Heat Island, Modeling (spatial)
State(s)/Region(s)
National
Keywords
Climate model, GCM, Heat island, RCM, SIP, UHI
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