Daily weather conditions for an entire city are usually represented by a single weather station, often located at a nearby airport. This resolution of atmospheric data fails to recognize the microscale climatic variability associated with land use decisions across and within urban neighborhoods. This study uses heat index, a measure of the combined effects of temperature and humidity, to assess the variability of heat exposure from ten weather stations across four urban neighborhoods and two control locations (downtown and in a nearby nature center) in Knoxville, Tennessee, USA. Results suggest that trees may negate a portion of excess urban heat, but are also associated with greater humidity. As a result, the heat index of locations with more trees is significantly higher than downtown and areas with fewer trees. Trees may also reduce heat stress by shading individuals from incoming radiation, though this is not considered in this study. Greater amounts of impervious surfaces correspond with reduced evapotranspiration and greater runoff, in terms of overall mass balance, leading to a higher temperature, but lower relative humidity. Heat index and relative humidity were found to significantly vary between locations with different tree cover and neighborhood characteristics for the full study time period as well as for the top 10% of heat index days. This work demonstrates the need for high-resolution climate data and the use of additional measures beyond temperature to understand urban neighborhood exposure to extreme heat, and expresses the importance of considering vulnerability differences among residents when analyzing neighborhood-scale impacts.

This paper represents an attempt to combine the output of several models that deal with future climatic, hydrologic and economic conditions in the Great Lakes and makes some predictions about the possible impact of one scenario of 2 • CO2 climate on Great Lakes shipping. It is realized that there is a great deal of uncertainty in all the models and that improvements are continually being made. Data from a General Circulation Model of future temperature and precipitation in the Great Lakes basin, a Great Lakes levels and flows model from the Canada Centre for Inland Waters and an International Joint Commision's Great Lakes economic model modified by the University of Wisconsin were used. The 1900-1976 period of lake levels and flows was used. The hydrologic model indicated that future mean lake levels may be reduced by one-half meter, and that the extreme low levels of the mid 1960's could occur 77% of the time in the future. No ice cover is predicted for any lake except Erie, permitting an eleven month shipping season. Five scenarios of future impact on shipping were evaluated. It was found that mean annual shipping costs may increase by 30% and the frequency of years when costs exceed those of the period of low lake levels (1963-65) could rise to 97%. Possible policy options in a future with climatically induced lower lake levels could include regulation to keep levels artificially high by diversions into the system, or increased dredging of the connecting channels.

No abstract

No abstract