Extended Abstract (600K)J2.7
Empirical modeling and mapping of below-canopy air temperatures in Baltimore, MD and vicinity
Gordon M. Heisler, USDA Forest Service, Syracuse, NY; and J. Walton, I. Yesilonis, D. Nowak, R. Pouyat, R. H. Grant, S. Grimmond, K. Hyde, and G. Bacon
As a contribution to the Baltimore Ecosystem Study (BES), a Long Term Ecological Research site, we began continuous measurements of air temperature and humidity at the 1.5-m height at five sites near the city of Baltimore, MD in June 2003. These sites are in a large open pasture, a woodlot near the pasture, a residential area with heavy tree cover but few buildings, a lawn area with nearby trees between two large apartment complexes, and a residential area with some trees and large lawn areas. An object of the measurements is to develop a spatially explicit, empirical model of below-canopy air temperature expressed as the temperature difference, DT, from a reference site. Such a model is important for evaluating urban structural and vegetation influences on air temperature for other studies related to human thermal comfort, carbon cycling, soil and stream temperatures, ozone formation, and effects of UV radiation for human health. The model will also permit mapping of the temperature pattern across the city. In addition to our measurements, data are available from two National Weather Service Automated Surface Observing System (ASOS) sites—in downtown Baltimore and at the Baltimore/Washington International Airport (BWI). We used the downtown ASOS site as the reference point for DT on an hourly basis between each site and the reference, which was related by regression analysis to independent variables derived from differences in upwind tree, impervious, and water cover from the National Land Cover Data (NLCD) 2001 database. Additional predictor variables for DT were atmospheric stability (Turner Class, derived from BWI cloud and wind speed data), vapor pressure deficit, antecedent precipitation, and descriptors of topography. Interactions between stability and the other predictor variables were included to account for the other influences varying with stability. In an initial analysis for one summer, the downtown site was generally warmer than the other sites, with DT being as large as 11 ºC. Although land use was significantly related to DT, the most significant influence was atmospheric stability. Topographic relationships, which included elevation differences between the sites and indicators of potential for cold air drainage, were significant in interacting with stability to influence temperature. An interaction of water cover and Chesapeake Bay water temperature was also a significant predictor variable. The most significant prediction equations were found with stable atmospheric conditions, which occur at night with clear skies and low wind speed.
We used wedge-shaped focal analysis functions in ESRI ArcGIS for cover analysis to prepare GIS maps from predicted DT for every cell in 30-m-resolution vegetation and DEM images of the Baltimore region. Despite the numerous sources of variability in the regression modeling, the method produced reasonable map patterns of DT.
Supplementary URL: http://www.fs.fed.us/ne/syracuse/Pubs/pubs_prod.htm#powerpoint
Joint Session J2, Characterizing the Urban and Coastal Climate: Thermal and Boundary Layer Structure and Atmospheric Responses
Monday, 10 September 2007, 1:00 PM-3:00 PM, Kon Tiki Ballroom
Previous paper Next paper