This study investigated the relationship between weather and aggressive crime for the period from 1999 through 2004 for the city of Cleveland, Ohio. The majority of the analysis focused on meteorological summer (June-August), because this is the time when the most oppressive conditions occur. Citywide analysis (nonspatial) was performed for many temporal variations, which accounted for season, time of day, and day of week (weekend or weekday). The linear regression model explored the relationship between apparent temperature and aggressive crime counts. Results show that summer has the highest aggressive crime counts, while winter has the lowest crime counts. Aggressive crime generally increases linearly as apparent temperature increases, with nonaggravated assaults and domestic violence assaults having the largest response as the weather becomes hotter. The midday and early night hours (i.e., 0300-1200 LT) have the greatest significant findings relating apparent temperature to aggressive crime.Further analysis was performed at the subcity level. A threshold of mean apparent temperature of 248C was used in order to investigate spatial patterns of aggressive crime when it is ''hot'' compared to when it is ''cold.'' Overall, the spatial patterns of crime counts are minimally influenced by hotter weather. Despite the numerous different spatial analyses that were performed, there was no significant evidence suggesting that spatial patterns of aggressive crime are greatly affected by hotter weather. Rather, it appears that warmer weather brings relatively similar percentage increases in aggressive crime activity citywide. Further exploration and analysis of the weather-crime relationship could be of significant benefit to law enforcement officials and emergency response personnel, who increasingly use geographic information system (GIS)-based tools in their work to assist in determining where and when intervention is most beneficial.