Accession Number:

ADA517519

Title:

Probabilistic Prediction for Improved Scientific Understanding and Improved Decision Making

Descriptive Note:

Journal article

Corporate Author:

NAVAL RESEARCH LAB WASHINGTON DC

Report Date:

2008-01-01

Pagination or Media Count:

4.0

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.

Subject Categories:

  • Meteorology
  • Physical and Dynamic Oceanography
  • Statistics and Probability

Distribution Statement:

APPROVED FOR PUBLIC RELEASE