Ambiguity in ensemble forecasting: evolution, estimate validation and value
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Authors
Allen, Mark S.
Subjects
Ensemble Forecast
Ambiguity
Uncertainty
Ensemble-of-Ensemble
Calibrated Error Sampling
Randomly Calibrated Resampling
Optimal Decision Making
Cost-Loss
Uncertainty-Folding
Secondary Criteria
Lorenz '96
Ensemble Prediction Systems;
Ambiguity
Uncertainty
Ensemble-of-Ensemble
Calibrated Error Sampling
Randomly Calibrated Resampling
Optimal Decision Making
Cost-Loss
Uncertainty-Folding
Secondary Criteria
Lorenz '96
Ensemble Prediction Systems;
Advisors
Eckel, F. Anthony
Date of Issue
2009-09
Date
September 2009
Publisher
Monterey, California: Naval Postgraduate School
Language
Abstract
An ensemble prediction system (EPS) generates flow-dependent estimates of uncertainty (i.e., random error due to analysis and model errors) associated with a numerical weather prediction model to provide information critical to optimal decision making. Ambiguity, or uncertainty in the prediction of forecast uncertainty, arises due to EPS deficiencies, including finite sampling and inadequate representation of the sources of forecast uncertainty. An EPS based on a low-order dynamical system was used to investigate the behavior of ambiguity, validate two practical estimation methods against a theoretical (impractical) technique, and apply ambiguity in decision making. Ambiguity generally decreased with increasing lead time and was found to depend strongly on ensemble forecast variance and the variability of ensemble mean error. The practical estimation techniques provided reasonably accurate ambiguity estimates, although they were too low at early lead times. The theoretical ambiguity estimate added significant value when combining ambiguity with forecast uncertainty to provide a single normative decision input. Additionally, value added to secondary user criteria (e.g., minimizing repeat false alarms), was explored using the practical estimations. Repeat false alarms were significantly reduced while maintaining primary value by using ambiguity information to selectively reverse normative decisions to take protective action, which effectively redistributed negative outcomes.
Type
Description
Series/Report No
Department
Meteorology
Organization
Identifiers
NPS Report Number
Sponsors
Funder
Format
xxvi, 209 p. : ill. ; 28 cm.
Citation
Distribution Statement
Approved for public release; distribution is unlimited.