Modeling influences of tree cover change on below-canopy urban air temperature

An objective of our work with the Baltimore Ecosystem Study, a Long Term Ecological Research site, is to model and map the influence of tree cover on air temperature in the urban landscape. Air temperature is important for its effects on space-conditioning energy use, carbon and water cycling, soil and stream temperatures, ozone formation, human thermal comfort, and human health.

We made measurements of air temperature and humidity at the 1.5-m height at five sites in a variety of land uses near Baltimore. Data are also available from National Weather Service stations in downtown Baltimore (call sign DMH) and at the Baltimore/Washington International Airport. For one summer, we used regression analysis to develop prediction equations for hourly temperature difference (ΔT) between DMH and each of the other sites. Predictors of land cover influences on ΔT were derived from 2-dimensional analysis of the differences upwind tree, impervious, and water cover from the 30-m resolution National Land Cover Data 2001. Additional predictors of ΔT were atmospheric stability estimated by Turner Class, vapor pressure deficit, antecedent precipitation, elevation, topographic differences near the sites, and water temperature. Results showed the DMH site to be warmer than the other sites, with ΔT as large as 11 °C at night with clear skies and low wind speed.

We used the regression results to create GIS maps that illustrate the variation in the urban heat island throughout a day. Another use is to predict the influence on temperature regimes of large-scale changes to tree cover. This analysis is carried out by leaving one area within the modeling domain with current tree cover as a reference and simulating changed tree cover in another part of the domain. The modified tree covers are designed to provide tree covers that best reduce thermal stress in urban populations and maximize air temperature benefits from trees. Future temperature modeling will use higher-resolution land cover and LiDAR tree and building heights to produce an analysis based on three-dimensional urban structure.