Probabilistic Prediction for Improved Scientific Understanding and Improved Decision Making

Abstract

In recognition of the importance of quantifying uncertainty in atmosphere-ocean forecasting for the purpose of managing operational risk, NRL-Monterey (MRY) is involved in several related efforts in support of the design, utility, and evaluation of forecasts that utilize and quantify uncertainty. NRL-MRY recently stood up the Probabilistic Prediction Research Office (PRO) to help facilitate and coordinate these efforts. The PRO also reaches out to users, decision makers, and funding agencies to better understand the environment in which meteorology and oceanography (METOC)-related decisions are made and to identify situations in which probabilistic environmental information can be utilized. NRL-MRY research efforts that attempt to exploit uncertainty information for improved understanding and decision making include the following: research on the design of the global atmospheric ensemble forecast system; research in the use of stochastic parameterizations to account for model uncertainty, which holds promise for improved ensemble forecasting of tropical cyclone track forecasts; the design of a new mesoscale atmospheric ensemble forecasting system, which accounts for model uncertainty through varying parameters in the physical parameterization schemes and perturbing sea surface and land surface forcing; use of ensemble-based covariances for data assimilation and adaptive observing applications; use of ensemble forecasts at the urban scale to quantify risk in the event of a toxic release; and the use of ensembles to learn about and improve model parameterizations. Some of these efforts are described in this article under the subheadings of global modeling and high-resolution regional modeling.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 2008
Accession Number
ADA517519

Entities

People

  • C. Reynolds
  • Cleo L. Bishop
  • J. S. Goerss
  • James D. Doyle
  • Justin McLay
  • O. Hansen
  • T. R. Holt

Organizations

  • United States Naval Research Laboratory

Tags

Communities of Interest

  • Human Systems
  • Space

DTIC Thesaurus Topics

  • Boundaries
  • Boundary Layer
  • Cyclones
  • Data Science
  • Delphi Method
  • High Resolution
  • Marine Meteorology
  • Meteorology
  • Military Research
  • Oceans
  • Recognition
  • Sea Surface Temperature
  • Statistics
  • Surface Temperature
  • Tropical Cyclones
  • Uncertainty
  • Weather Forecasting

Fields of Study

  • Environmental science

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Ocean-Atmosphere Mesoscale Modeling, Data Assimilation, and Flux Boundary Layers
  • Team-Based Human-Centered Cognitive Task Decision Making and Information Performance.