NDLI: Development and testing of a coupled ocean–atmosphere mesoscale ensemble prediction system

Content Provider	Springer Nature Link
Author	Holt, Teddy R. Cummings, James A. Bishop, Craig H. Doyle, James D. Hong, Xiaodong Chen, Sue Jin, Yi
Copyright Year	2011
Abstract	A coupled ocean–atmosphere mesoscale ensemble prediction system has been developed by the Naval Research Laboratory. This paper describes the components and implementation of the system and presents baseline results from coupled ensemble simulations for two tropical cyclones. The system is designed to take into account major sources of uncertainty in: (1) non-deterministic dynamics, (2) model error, and (3) initial states. The purpose of the system is to provide mesoscale ensemble forecasts for use in probabilistic products, such as reliability and frequency of occurrence, and in risk management applications. The system components include COAMPS® (Coupled Ocean/Atmosphere Mesoscale Prediction System) and NCOM (Navy Coastal Ocean Model) for atmosphere and ocean forecasting and NAVDAS (NRL Atmospheric Variational Data Assimilation System) and NCODA (Navy Coupled Ocean Data Assimilation) for atmosphere and ocean data assimilation. NAVDAS and NCODA are 3D-variational (3DVAR) analysis schemes. The ensembles are generated using separate applications of the Ensemble Transform (ET) technique in both the atmosphere (for moving or non-moving nests) and the ocean. The atmospheric ET is computed using wind, temperature, and moisture variables, while the oceanographic ET is derived from ocean current, temperature, and salinity variables. Estimates of analysis error covariance, which is used as a constraint in the ET, are provided by the ocean and atmosphere 3DVAR assimilation systems. The newly developed system has been successfully tested for a variety of configurations, including differing model resolution, number of members, forecast length, and moving and fixed nest options. Results from relatively coarse resolution (∼27-km) ensemble simulations of Hurricanes Hanna and Ike demonstrate that the ensemble can provide valuable uncertainty information about the storm track and intensity, though the ensemble mean provides only a small amount of improved predictive skill compared to the deterministic control member.
Starting Page	1937
Ending Page	1954
Page Count	18
File Format	PDF
ISSN	16167341
Journal	Deutsche Hydrografische Zeitschrift
Volume Number	61
Issue Number	11
e-ISSN	16167228
Language	English
Publisher	Springer-Verlag
Publisher Date	2011-06-28
Publisher Place	Berlin, Heidelberg
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Ensembles Coupled ocean–atmosphere modeling Tropical cyclones Variational analyses Probabilistic prediction Environmental Monitoring/Analysis Fluid- and Aerodynamics Oceanography Geophysics/Geodesy Meteorology/Climatology
Content Type	Text
Resource Type	Article
Subject	Oceanography

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