Data Warehouse Techniques to Support Global On-Demand Weather Forecast Metrics

Abstract

Air Force pilots and other operators make crucial mission planning decisions based on weather forecasts; therefore, the ability to forecast the weather accurately is a critical issue to Air Force Weather (AFW) and its customers. The goal of this research is to provide Air Force Weather with a methodology to automate statistical data analysis for the purpose of providing on-demand metrics. A data warehousing methodology is developed and applied to the weather metrics problem in order to present an option that will facilitate on-demand metrics. On-line analytical processing (OLAP) and data mining solutions are also discussed.

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Mar 01, 2000
Accession Number
ADA380727

Entities

People

  • Meriellen C. Joga

Organizations

  • Air Force Institute of Technology

Tags

Communities of Interest

  • Biomedical
  • Energy and Power Technologies
  • Human Systems
  • Weapons Technologies

DTIC Thesaurus Topics

  • Air Force
  • Computer Programming
  • Data Analysis
  • Data Integration
  • Data Mining
  • Data Warehousing
  • Databases
  • Domain Specific Programming Languages
  • Information Processing
  • Information Science
  • Information Systems
  • Network Science
  • Relational Database Management Systems
  • Software Development
  • Statistical Analysis
  • Statistics
  • Test And Evaluation

Fields of Study

  • Environmental science

Readers

  • Computational Modeling and Simulation
  • Distributed Systems and Data Platform Development
  • Ocean-Atmosphere Mesoscale Modeling, Data Assimilation, and Flux Boundary Layers

Technology Areas

  • AI & ML
  • AI & ML - DoD AI Strategy