A new meteorological instrumentation array is being designed to support chem-bio field tests at Dugway Proving Grounds. In order to optimze the design of the instrument array from a scientific perspective we use a three component approach:

- Define typical days during which a test would be conducted

- Analyze the spatial variability of the typical test days, which is used to define the spatial density and placement of instrumentation

- Use observing system simulation experiments (OSSE) to quantify the ability of a candidate array to observe the meteorological conditions

We use a self orginizing map analysis to characterize the common weather regimes in the historical record that satisfy the go conditions under which a test would be conducted. We then classify the observations into the weather regimes and select days for case studies that represent each regime. The case studies are modeled using the RTFDDA-MM5 to develop truth atmospheres. The spatial variability of each field (wind components, temperature, humidity, etc.) is determined to establish a mean density of instruments required to measure that field. The spatial variability and correlation distance of the field guides placement of candidate instruments in the candidate array. To evaluate the effectiveness of a candidate instrumentation array we use the OSSE framework. Pseudo-observations (point, profile, volume) corresponding to the locations of a proposed instrumentation array are extracted from the case studies and then ingested into an analysis system and the resulting analysis is compared to the case study truth. The comparison metrics form one component in the overall cost benefit analysis of each proposed instrumentation array.