19 Mar 2026

Arctic and Subarctic Zonal Characterization and Operational Thresholding (AZCOT)

Abstract: The US military develops and updates environmental parameters specified for the sustainment of operations throughout the world. These requirements are generally based on environmental data providing a baseline of temperature, wind, and precipitation expectations for each location. Observational data for Arctic regions is limited because of the remote and sparsely occupied geographical conditions. To address the need for updating these requirements, a 30-year analysis of meteorological conditions was conducted using a European Centre for Medium-Range Weather Forecasts (ECMWF) global reanalysis dataset over the Arctic and Subarctic region, defined by latitude 60°–90° North for this project. Raw hourly datasets were acquired, and the minimum temperatures, maximum wind speeds, maximum snow depths, and averages were determined over the period 1991–2020 between the months of October and March for each parameter. These were then visualized with geospatial analysis, producing a variety of maps designed to assist with the classification of parameters in Arctic zones of operation across a range of temporal resolutions. Finally, a review of operational limits for military equipment was conducted to match northern zones of operation with suitable capabilities dependent on environmental conditions.

10 Oct 2025

Development and Management of Arctic Zonal Characterization Products: Geospatial Database

Abstract: Environmental parameters for operational planning in extreme conditions require accurate knowledge of prevailing meteorological conditions. However, the Arctic region presents unique challenges due to limited observational data and unique geographical conditions. To address the need for such knowledge, this study presents an analysis of Arctic prevailing-conditions using European Center for Medium-Range Weather Forecasting (ECMWF) Reanalysis v5 (ERA5) Data from 1991 to 2020. A custom Python-based framework was developed to process and analyze hourly datasets, identifying zones of extreme events and their frequency across multiple temporal scales. The framework uses ArcPy to automate the generation of nearly 40,000 mapped classifications for land masses 60°N and above. This automated pipeline enables both static and dynamic map generation capabilities for operational planning now and in the future. The resulting dataset provides critical spatial and temporal resolution of Arctic prevailing-conditions, enabling more refined characterization of extreme prevailing-conditions across the circumpolar region.

6 Jan 2022

A Study on the Delta-Bullington Irregular Terrain Radiofrequency Propagation Model: Assessing Model Suitability for Use in Decision Support Tools

ABSTRACT: Modeling the propagation of radiofrequency signals over irregular terrain is both challenging and critically important in numerous Army applications. One application of particular importance is the performance and radio connectivity of sensors deployed in scenarios where the terrain and the environment significantly impact signal propagation. This report investigates both the performance of and the algorithms and assumptions underlying the Delta-Bullington irregular terrain radiofrequency propagation model discussed in International Telecommunications Union Recommendation P.526-15. The aim is to determine its suitability for use within sensor-planning decision support tools. After reviewing free-space, spherical earth diffraction, and terrain obstacle diffraction losses, the report discusses several important tests of the model, including reciprocity and geographic continuity of propagation loss over large areas of rugged terrain. Overall, the Delta-Bullington model performed well, providing reasonably rapid and geographically continuous propagation loss estimates with computational demands appropriate for operational use.