Linear and nonlinear post-processing of numerically forecasted surface temperature

Nonlinear Processes in Geophysics

Volumn 10, Issue 4-5, 2003, Pages 373-383

  Casaioli, M ^a   Mantovani, R ^b   Proietti Scorzoni, F ^c   Puca, S ^c   Speranza, A ^d   Tirozzi, B ^c  

^a CNR   (Italy)

^b UNIVERSITY OF BOLOGNA   (Italy)

^c UNIVERSITÀ DI ROMA LA SAPIENZA   (Italy)

^d UNIVERSITY OF CAMERINO   (Italy)

Author keywords

[No Author keywords available]

Indexed keywords

AIR TEMPERATURE; FORECASTING METHOD; SURFACE TEMPERATURE; WEATHER FORECASTING;

EID: 0042355241     PISSN: 10235809     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Article

References (15)

1. Cacciamani, C.: Extreme daily temperature forecasts in the Emilia Romagna region (North Italy) by Kalman filter technique of direct numerical weather prediction model outputs, LAM Newsletter, 22, 196-209, 1993.
2. Carlson, P. Danielsson, M., Dejardin, M., Jon-And, K., and Sjölin, J.: Simulated annealing and neural network as alternative methods for nonlinear constrained optimization, Nucl. Instrum. Methods Phys. Res., Sect. A, 381, 152-156, 1996.
3. Cohen, B., Saad, D., and Marom, E.: Efficient training of recurrent neural network with time delays, Neural Networks, 10, 51-59, 1997.
4. Deidda, R., Marrocu. M., and Speranza, A.: Meteorological forecasting for the European Southern Observatory in Chile, Nuovo Cimento C. 23, 1-23, 2000.
5. Geman, S. and Geman, D.: Stochastic relaxation, Gibbs distribution and bayesian restoration of image, IEEE Trans. PAMI, 6, 721-741, 1984.
6. Hall, T., Brooks, H. E., and Doswell, C. A.: Precipitation forecasting using a neural network, Wea. Forecasting, 14, 338-345, III, 1999.
7. Hertz, J., Krogh, A., and Palmer, R. G.: Introduction to the Theory of Neural Computation, Addison-Wesley, 321 pp, 1993.
8. Hsieh, W. W. and Tang, B.: Applying neural network models to prediction and data analysis in meteorology and oceanography, Bull. Amer. Meteor. Soc., 79, 1855-1870, 1998.
9. Koizumi, K.: An objective method to modify numerical model forecasts with newly given weather data using an artificial neural network, Wea. Forecasting, 14, 109-118, 1999.
10. Marzban, C. and Stumpf, G. J.: A neural network for damaging wind prediction, Wea. Forecasting, 13, 151-163, 1998.
11. Massie. D. R. and Rose, M. A.: Predicting daily maximum temperatures using linear regression and Eta geopotential thickness forecasts, Wea. Forecasting, 12, 799-807, 1997.
12. Mhaskar, H. N: Neural Networks for optimal approximation of smooth and analytic functions, Neural Computation, 8, 164-177, 1996.
13. Narasimhan, R., Keller, J., Subramaniam. G., Raasch, E., Croley, B., Duncan, K., and Potter, W. T.: Ozone modeling using neural networks, J. Appl. Meteor., 39, 291-296, 2000.
14. Shao, J.: Improving nowcasts of road surface temperature by a back-propagation neural network, Wea. Forecasting, 13, 164-171, 1998.
15. Tang, B., Hsieh, W. W., Monahan, A. H., and Tangang, F. T.: Skill comparisons between neural networks and canonical correlation analysis in predicting the equatorial pacific sea surface temperatures, J. Climate, 13, 287-293, 2000.