The application of an evolutionary algorithm to the optimization of a mesoscale meteorological model

Journal of Applied Meteorology and Climatology

Volumn 48, Issue 2, 2009, Pages 317-329

  O'Steen, Lance ^a   Werth, David ^a  

^a SAVANNAH RIVER NATIONAL LABORATORY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ATMOSPHERIC MODEL; COMPUTER RESOURCES; MESOSCALE; MESOSCALE METEOROLOGICAL MODEL; MESOSCALE SIMULATION; METEOROLOGICAL VARIABLES; REGIONAL ATMOSPHERIC MODELING SYSTEMS; RMS ERRORS; ROOT-MEAN-SQUARE ERRORS; SYNTHETIC DATA;

COST FUNCTIONS; EVOLUTIONARY ALGORITHMS; OPTIMIZATION; RANDOM ACCESS STORAGE; SIMULATORS;

SET THEORY;

ALGORITHM; ATMOSPHERIC MODELING; COMPUTER SIMULATION; MESOSCALE METEOROLOGY; OPTIMIZATION; PARAMETERIZATION;

EID: 66149148324     PISSN: 15588424     EISSN: None     Source Type: Journal    
DOI: 10.1175/2008JAMC1967.1     Document Type: Article

References (16)

1. André, J. C., G. De Moor, P. Lacarrère, G. Therry, and R. du Vachat, 1978: Modeling the 24-hour evolution of the mean and turbulent structures of the planetary boundary layer. J. Atmos. Sci., 35, 1861-1883.
2. Bäck, T., U. Hammel, and H. P. Schwefel, 1997: Evolutionary computation: Comments on the history and current state. IEEE Trans. Evol. Comput., 1, 3-17.
3. Doran, J. C., J. D. Fast, and J. Horel, 2002: The VTMX 2000 campaign. Bull. Amer. Meteor. Soc., 83, 537-551.
4. Fogel, D. B., 2000: Evolutionary Computation: Principles and Practice for Signal Processing. SPIE Press, 168 pp.
5. Haupt, S. E., 2005: A demonstration of coupled receptor/dispersion modeling with a genetic algorithm. Atmos. Environ., 39, 7181-7189.
6. Kalnay, E., M. Kanamitsu, and W. E. Baker, 1990: Global numerical weather prediction at the National Meteorological Center. Bull. Amer. Meteor. Soc., 71, 1410-1428.
7. Kanamitsu, M., 1989: Description of the NMC Global Data Assimilation and Forecast System. Wea. Forecasting, 4, 335-342.
8. Lin, C.-L., T. Chai, and J. Sun, 2001: Retrieval of flow structures in a convective boundary layer using an adjoint model: Identical twin experiments. J. Atmos. Sci, 58, 1767-1783.
9. Mellor, G. L., and T. Yamada, 1974: A hierarchy of closure models for planetary boundary layers. J. Atmos. Sci., 31, 1791-1806.
10. Pielke, R. A., and Coauthors, 1992: A comprehensive meteorological modeling system-RAMS. Meteor. Atmos. Phys., 49, 69-91.
11. Qin, J., and W. Robinson, 1995: The impact of tropical forcing on extratropical predictability in a simple global model. J. Atmos. Sci., 52, 3895-3910.
12. Schwefel, H.-P., 1995: Evolution and Optimum Seeking. John Wiley and Sons, 456 pp.
13. Sela, J., 1980: Spectral modeling at NMC. Mon. Wea. Rev., 108, 1279-1292.
14. Vekaria, K., and C. Clack, 1998: Selective crossover in genetic algorithms: An empirical study. Proceedings of the 5th International Conference on Parallel Problem Solving from Nature - PPSN V, A. E. Eiben et al., Eds., Lecture Notes in Computer Science, Vol. 1498, Springer-Verlag, 438-447.
15. Warner, T. T., R. A. Peterson, and R. E. Treadon, 1997: A tutorial on lateral boundary conditions as a basic and potentially serious limitation to regional numerical weather prediction. Bull. Amer. Meteor. Soc.,78, 2599-2617.
16. Zhong, S., and J. D. Fast, 2003: An evaluation of the MM5, RAMS, and Meso-Eta models at subkilometer resolution using VTMX field campaign data in the Salt Lake valley. Mon. Wea. Rev., 131, 1301-1322.