Passive acoustic detection of ground targets is governed by both local and regional weather conditions such as wind and temperature. The wind speed generally increases with height and can also change direction, making accurate assessment of detection coverage a real challenge. In the absence of wind, the temperature profile, or variation with height, changes the refractive index such that sound will tend to refract towards the cooler air (the sound speed is slower there). A new ground sensor technology has been developed under DARPA's IUGS program which integrates temperature, temperature gradient, humidity, barometric pressure, wind speed and direction, and insolation (solar radiation/reflection) from a ground sensor measurement site with upper level wind and temperature data from weather databases. This data is used to model the sound velocity profile from the surface to a height approximately one-tenth the propagation range of interest. A parabolic equation sound propagation model then creates a table for the sound transmission loss variability with range, frequency, and direction. For a given target and background noise, one can then reasonably predict detection range for a specific sensor design. When the ground sensor has 'environmental intelligence,' it can alter its integration and detection algorithms for improved performance in a dynamic weather environment.