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  • 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.
  • Procedures for Obtaining US Air Force Global Air-Land Weather Exploitation Model (GALWEM) Data for Hydrological Modeling Applications: An Overview of the GALWEM Acquisition System (GAS) v1.0 and v2.0

    Abstract: The Global Air Land Weather Exploitation Model (GALWEM) Acquisition System (GAS) is a software platform that serves to automate and simplify the procurement of numerical weather prediction model data from the 557th Weather Squadron. GAS allows for the download of meteorological and other environmental parameters from the GALWEM, an operational Numerical Weather Prediction capability operated by the 557th Weather Squadron for use by both Air Force and Army interests. GAS provides the ability to archive GALWEM data so that it may be used by the US Army Engineer Research and Development Center (ERDC) and other researchers. The report describes multiple methodologies for data access as well as suggestions for future work to improve computational efficiency and customer access.
  • 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.
  • Corps of Engineers partners with community as it expands environmental sampling beyond Hanover lab site

    HANOVER, NH – The U.S. Army Environmental Command and the U.S. Army Corps of Engineers are working with the New Hampshire Department of Environmental Services (NHDES), Dartmouth College, the Town of Hanover, and School Administrative Unit #70, public schools of Hanover, as they expand their continuing, on-site environmental monitoring program to