Verification of Weather Running Estimate-Nowcast (WRE-N) Forecasts Using a Spatial-Categorical Method

Abstract

Spatial forecasts from Numerical Weather Prediction (NWP) models of meteorological variables to support US Army operations on the battlefield have become an integral part of the products available for the Staff Weather Officer to use in providing mission planning and execution forecasts. These forecasts are ingested by certain Army tactical decision aids (TDAs) and are fused with information on the operational weather thresholds, which impact the performance of Army systems and missions. Such a TDA generates spatial and temporal forecasts of these impacts for user-specified systems and/or missions. This report presents the results from applying a method to verify forecast fields of meteorological variables that have been filtered by the application of a threshold, similar to the method used by the TDA. A threshold applied to a continuous variable field becomes a categorical forecast for which there are traditional and nontraditional methods for verification. This study evaluates the ability of the NWP model to predict multiple categories of the spatial variable. Preliminary results suggest the skill of the model when predicting objects defined by lower thresholds is greater than the skill for objects defined by higher thresholds.

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Jul 01, 2017
Accession Number
AD1036722

Entities

People

  • John W. Raby

Organizations

  • United States Army Research Laboratory

Tags

Communities of Interest

  • Cyber
  • Energy and Power Technologies
  • Weapons Technologies

DTIC Thesaurus Topics

  • Air Force
  • Army Operations
  • Atmospheric Sciences
  • Boundary Layer
  • California
  • Case Studies
  • Data Sets
  • Geographic Information Systems
  • Information Science
  • Information Systems
  • Meteorology
  • Military Research
  • Spatial Distribution
  • Statistics
  • Tactical Decision Aids
  • Verification
  • Weather Forecasting

Fields of Study

  • Environmental science

Readers

  • Atmospheric Science/Meteorology
  • Computational Modeling and Simulation