The Department of Defense (DoD) Extreme Conditions Assessment Tool, or DECAT, was released department-wide in September 2020 by the Office of the Deputy Assistant Secretary of Defense, Energy Resilience and Optimization (ODASD(E&ER)). The DECAT enables personnel at all levels of the department — from installation planners to leadership — to understand each location's exposure to weather-related hazards of interest to Congress using historical data and future weather forecasts projections. Under DoD Policy, tools such as DECAT shall be updated at such intervals as necessary for appropriate technology transfer, data currency, and system functionality.

The DECAT international version treats international locations (those outside the Contiguous U.S. (CONUS), Alaska and Hawaii) as a single region to enable comparison of natural hazards exposure across all international installations, just as the CONUS-AK-HI locations are treated as a single region. This comparability requires that the same or very comparable data are used at each installation to enable an “apples-to-apples” comparison. The consequence of this is that that best available data globally is far coarser in resolution, and potentially of greater uncertainty, than may be available for some regions (Europe, Far East, Australia) and locations. To support the 2023 deliverables, the DCAT ODASD(E&ER) team requires an analysis of the effects of (1) splitting international locations into subregions; (2) adding additional, subregion-specific datasets; and (3) expanding the tool into other regions of the world. To address these concerns, there are four tasks within this project:

Task 1. Identify and Evaluate Authoritative Global, Regional and National Data for Inclusion in the DECAT

Task 2. Data Selection

Task 3. Data Delivery

Task 4. Report Delivery

The DECAT takes the position that natural hazard uncertainty is best reduced by reliance on model ensembles rather than one or a handful of models that might improve representation of certain processes at certain locations but have poorer fidelity for other processes and areas. Consequently, with respect to natural hazard data, the interest in this scope is at the model ensemble level, not at the level of individual  models. 

(Project Completion - 2024)