A numerical investigation of mesoscale predictability
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Authors
Beattie, Jodi C.
Subjects
Mesoscale modeling
Model Verification
Predictability
MM5
Model Verification
Predictability
MM5
Advisors
Nuss, Wendell A.
Brown, David S.
Date of Issue
2003-03
Date
Publisher
Monterey, California. Naval Postgraduate School
Language
Abstract
As mesoscale models increase in resolution there is a greater need to understand predictability on smaller scales. The predictability of a model is related to forecast skill. It is possible that the uncertainty of one scale of motion can affect the other scales due to the nonlinearity of the atmosphere. Some suggest that topography is one factor that can lead to an increase of forecast skill and therefore predictability. This study examines the uncertainty of a mesoscale model and attempts to characterize the predictability of the wind field. The data collected is from the summer, when the synoptic forcing is relatively benign. Mesoscale Model 5 (MM5) lagged forecasts are used to create a three-member ensemble over a 12-hour forecast cycle. The differences in these forecasts are used to determine the spread of the wind field. Results show that some mesoscale features have high uncertainty and others have low uncertainty, shedding light on the potential predictability of these features with a mesoscale model. Results indicate that topography is a large source of uncertainty. This is seen in all data sets, contrary to other studies. The ability of the model to properly forecast the diurnal cycle also impacted substantially on the character and evolution of forecast spread. The persistent mesoscale features were represented reasonably well, however the detailed structure of these features had a fair amount of uncertainty.
Type
Thesis
Description
Series/Report No
Department
Meteorology
Organization
Identifiers
NPS Report Number
Sponsors
Funder
Format
xiv, 79 p. : ill. (some col.), maps ;
Citation
Distribution Statement
Approved for public release; distribution is unlimited.
Rights
This publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. Copyright protection is not available for this work in the United States.