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Volumn 79, Issue 9, 1998, Pages 1855-1870

Applying Neural Network Models to Prediction and Data Analysis in Meteorology and Oceanography

Author keywords

[No Author keywords available]

Indexed keywords

GEOGRAPHY; MATHEMATICAL MODEL; METEOROLOGY; NEURAL NETWORK;

EID: 0032466364     PISSN: 00030007     EISSN: None     Source Type: Journal    
DOI: 10.1175/1520-0477(1998)079<1855:ANNMTP>2.0.CO;2     Document Type: Review
Times cited : (349)

References (75)
  • 1
    • 0000752674 scopus 로고
    • Wind ambiguity removal by the use of neural network techniques
    • Badran, F., S. Thiria, and M. Crepon, 1991: Wind ambiguity removal by the use of neural network techniques. J. Geophys. Res., 96, 20521-20529.
    • (1991) J. Geophys. Res. , vol.96 , pp. 20521-20529
    • Badran, F.1    Thiria, S.2    Crepon, M.3
  • 2
    • 0028603789 scopus 로고
    • Cloud classification of A VHRR imagery in maritime regions using a probabilistic neural network
    • Bankert, R. L., 1994: Cloud classification of A VHRR imagery in maritime regions using a probabilistic neural network. J. Appl. Meteor., 33, 909-918.
    • (1994) J. Appl. Meteor. , vol.33 , pp. 909-918
    • Bankert, R.L.1
  • 3
    • 0000123158 scopus 로고
    • Origins and levels of monthly and seasonal forecast skill for United States surface air temperatures determined by canonical correlation analysis
    • Barnett, T. P., and R. Preisendorfer, 1987: Origins and levels of monthly and seasonal forecast skill for United States surface air temperatures determined by canonical correlation analysis. Mon. Wea. Rev., 115, 1825-1850.
    • (1987) Mon. Wea. Rev. , vol.115 , pp. 1825-1850
    • Barnett, T.P.1    Preisendorfer, R.2
  • 4
    • 0027799092 scopus 로고
    • ENSO and ENSO-related predictability. Part I: Prediction of equatorial Pacific sea surface temperature with a hybrid coupled ocean-atmosphere model
    • _, M. Latif, N. Graham, M. Flugel, S. Pazan, and W. White, 1993: ENSO and ENSO-related predictability. Part I: Prediction of equatorial Pacific sea surface temperature with a hybrid coupled ocean-atmosphere model. J. Climate, 6, 1545-1566.
    • (1993) J. Climate , vol.6 , pp. 1545-1566
    • Latif, M.1    Graham, N.2    Flugel, M.3    Pazan, S.4    White, W.5
  • 5
    • 0027070241 scopus 로고
    • Prediction of ENSO episodes using canonical correlation analysis
    • Barnston, A. G., and C. F. Ropelewski, 1992: Prediction of ENSO episodes using canonical correlation analysis. J. Climate, 5, 1316-1345.
    • (1992) J. Climate , vol.5 , pp. 1316-1345
    • Barnston, A.G.1    Ropelewski, C.F.2
  • 6
    • 0028669614 scopus 로고
    • Long-lead seasonal forecasts - Where do we stand?
    • _, and Coauthors, 1994: Long-lead seasonal forecasts - where do we stand? Bull. Amer. Meteor. Soc., 75, 2097-2114.
    • (1994) Bull. Amer. Meteor. Soc. , vol.75 , pp. 2097-2114
  • 8
    • 0024220237 scopus 로고
    • Auto-association by multilayer perceptrons and singular value decomposition
    • Bourlard, H., and Y. Kamp, 1988: Auto-association by multilayer perceptrons and singular value decomposition. Biol. Cybern., 59, 291-294.
    • (1988) Biol. Cybern. , vol.59 , pp. 291-294
    • Bourlard, H.1    Kamp, Y.2
  • 10
    • 0030211964 scopus 로고    scopus 로고
    • Bagging predictions
    • Breiman, L., 1996: Bagging predictions. Mach. Learning, 24, 123-140.
    • (1996) Mach. Learning , vol.24 , pp. 123-140
    • Breiman, L.1
  • 11
    • 0000825696 scopus 로고
    • An inter-comparison of methods for finding coupled patterns in climate data
    • Bretherton, C. S., C. Smith, and J. M. Wallace, 1992: An inter-comparison of methods for finding coupled patterns in climate data. J. Climate, 5, 541-560.
    • (1992) J. Climate , vol.5 , pp. 541-560
    • Bretherton, C.S.1    Smith, C.2    Wallace, J.M.3
  • 12
    • 0030467801 scopus 로고    scopus 로고
    • Retrieving atmospheric temperature parameters from dmsp ssm/t-1 data with a neural network
    • Butler, C. T., R. V. Meredith, and A. P. Stogryn, 1996: Retrieving atmospheric temperature parameters from dmsp ssm/t-1 data with a neural network. J. Geophys. Res., 101, 7075-7083.
    • (1996) J. Geophys. Res. , vol.101 , pp. 7075-7083
    • Butler, C.T.1    Meredith, R.V.2    Stogryn, A.P.3
  • 13
    • 85025505893 scopus 로고
    • Generalization performance of overtrained back-propagation networks
    • L. B. Almeida and C. J. Wellekens, Eds., Springer-Verlag
    • Chauvin, Y., 1990: Generalization performance of overtrained back-propagation networks. Neural Networks. EURASIP Workshop Proceedings, L. B. Almeida and C. J. Wellekens, Eds., Springer-Verlag, 46-55.
    • (1990) Neural Networks. EURASIP Workshop Proceedings , pp. 46-55
    • Chauvin, Y.1
  • 14
    • 0024490816 scopus 로고
    • The recent excitement about neural networks
    • Crick, F., 1989: The recent excitement about neural networks. Nature, 337, 129-132.
    • (1989) Nature , vol.337 , pp. 129-132
    • Crick, F.1
  • 15
    • 0024861871 scopus 로고
    • Approximation by superpositions of a sigmoidal function
    • Cybenko, G., 1989: Approximation by superpositions of a sigmoidal function. Math. Control, Signals, Syst., 2, 303-314.
    • (1989) Math. Control, Signals, Syst. , vol.2 , pp. 303-314
    • Cybenko, G.1
  • 17
    • 0028594236 scopus 로고
    • Prediction of El Niño events in the Pacific by means of neural networks
    • Derr, V. E., and R. J. Slutz, 1994: Prediction of El Niño events in the Pacific by means of neural networks. AI Applic., 8, 51-63.
    • (1994) AI Applic. , vol.8 , pp. 51-63
    • Derr, V.E.1    Slutz, R.J.2
  • 18
    • 0026448657 scopus 로고
    • Nonlinear prediction, chaos, and noise
    • Corrigendum, 74, 243
    • Elsner, J. B., and A. A. Tsonis, 1992: Nonlinear prediction, chaos, and noise. Bull. Amer. Meteor. Soc., 73, 49-60; Corrigendum, 74, 243.
    • (1992) Bull. Amer. Meteor. Soc. , vol.73 , pp. 49-60
    • Elsner, J.B.1    Tsonis, A.A.2
  • 19
    • 0027294340 scopus 로고
    • Improving model selection by nonconvergent methods
    • Finnoff, W., F. Hergert, and H. G. Zimmermann, 1993: Improving model selection by nonconvergent methods. Neural Networks, 6, 771-783.
    • (1993) Neural Networks , vol.6 , pp. 771-783
    • Finnoff, W.1    Hergert, F.2    Zimmermann, H.G.3
  • 20
    • 0027007868 scopus 로고
    • Rainfall forecasting in space and time using a neural network
    • French, M. N., W. F. Krajewski, and R. R. Cuykendall, 1992: Rainfall forecasting in space and time using a neural network. J. Hydrol. 137, 1-31.
    • (1992) J. Hydrol. , vol.137 , pp. 1-31
    • French, M.N.1    Krajewski, W.F.2    Cuykendall, R.R.3
  • 21
    • 0001740245 scopus 로고
    • Regression towards mediocrity in hereditary stature
    • Galton, F. J., 1885: Regression towards mediocrity in hereditary stature. J. Anthropological Inst., 15, 246-263.
    • (1885) J. Anthropological Inst. , vol.15 , pp. 246-263
    • Galton, F.J.1
  • 24
    • 84956694585 scopus 로고
    • An investigation of the El Niño-Southern Oscillation cycle with statistical models, 1, predictor field characteristics
    • Graham, N. E., J. Michaelsen, and T. P. Barnett, 1987: An investigation of the El Niño-Southern Oscillation cycle with statistical models, 1, predictor field characteristics. J. Geophys. Res., 92, 14251-14270.
    • (1987) J. Geophys. Res. , vol.92 , pp. 14251-14270
    • Graham, N.E.1    Michaelsen, J.2    Barnett, T.P.3
  • 25
    • 0028571018 scopus 로고
    • Reconstruction of the El Niño Attractor with neural Networks
    • Grieger, B., and M. Latif, 1994: Reconstruction of the El Niño Attractor with neural Networks. Climate Dyn., 10, 267-276.
    • (1994) Climate Dyn. , vol.10 , pp. 267-276
    • Grieger, B.1    Latif, M.2
  • 26
    • 0029509566 scopus 로고
    • Prediction of the summer rainfall over south Africa
    • Hastenrath, S., L. Greischar, and J. van Heerden, 1995: Prediction of the summer rainfall over south Africa. J. Climate, 8, 1511-1518.
    • (1995) J. Climate , vol.8 , pp. 1511-1518
    • Hastenrath, S.1    Greischar, L.2    Van Heerden, J.3
  • 28
    • 0031207768 scopus 로고    scopus 로고
    • El Nino, La Nina, and the nonlinearity of their teleconnections
    • Hoerling, M. P., A. Kumar, and M. Zhong, 1997: El Nino, La Nina, and the nonlinearity of their teleconnections. J. Climate, 10, 1769-1786.
    • (1997) J. Climate , vol.10 , pp. 1769-1786
    • Hoerling, M.P.1    Kumar, A.2    Zhong, M.3
  • 29
    • 0024880831 scopus 로고
    • Multilayer feedforward networks are universal approximators
    • Hornik, K., M. Stinchcombe, and H. White, 1989: Multilayer feedforward networks are universal approximators. Neural Networks, 2, 359-366.
    • (1989) Neural Networks , vol.2 , pp. 359-366
    • Hornik, K.1    Stinchcombe, M.2    White, H.3
  • 30
    • 0000107975 scopus 로고
    • Relations between two sets of variates
    • Hotelling, H., 1936: Relations between two sets of variates. Biometrika, 28, 321-377.
    • (1936) Biometrika , vol.28 , pp. 321-377
    • Hotelling, H.1
  • 32
    • 0002781783 scopus 로고    scopus 로고
    • Securing information with optical technologies
    • Javidi, B., 1997: Securing information with optical technologies. Physics Today, 50, 27-32.
    • (1997) Physics Today , vol.50 , pp. 27-32
    • Javidi, B.1
  • 33
    • 0026113980 scopus 로고
    • Nonlinear principal component analysis using autoassociative neural networks
    • Kramer, M. A., 1991: Nonlinear principal component analysis using autoassociative neural networks. AIChE J., 37, 233-243.
    • (1991) AIChE J. , vol.37 , pp. 233-243
    • Kramer, M.A.1
  • 34
    • 0029472420 scopus 로고
    • A neural network as a nonlinear transfer function model for retrieving surface wind speeds from the special sensor microwave imager
    • Krasnopolsky, V. M., L. C. Breaker, and W. H. Gemmill, 1995: A neural network as a nonlinear transfer function model for retrieving surface wind speeds from the special sensor microwave imager. J. Geophys. Res., 100, 11033-11045.
    • (1995) J. Geophys. Res. , vol.100 , pp. 11033-11045
    • Krasnopolsky, V.M.1    Breaker, L.C.2    Gemmill, W.H.3
  • 37
    • 0031438596 scopus 로고    scopus 로고
    • Estimating longwave net radiation at sea surface from the Special Sensor Microwave/Imager (SSM/I)
    • Liu, Q. H., C. Simmer, and E. Ruprecht, 1997: Estimating longwave net radiation at sea surface from the Special Sensor Microwave/Imager (SSM/I). J. Appl. Meteor., 36, 919-930.
    • (1997) J. Appl. Meteor. , vol.36 , pp. 919-930
    • Liu, Q.H.1    Simmer, C.2    Ruprecht, E.3
  • 38
    • 0003371456 scopus 로고
    • Empirical orthogonal functions and statistical weather prediction
    • Dept. of Meteorology, Massachusetts Institute of Technology, Cambridge, MA
    • Lorenz, E. N., 1956: Empirical orthogonal functions and statistical weather prediction. Statistical Forecasting Project, Dept. of Meteorology, Massachusetts Institute of Technology, Cambridge, MA, 49 pp.
    • (1956) Statistical Forecasting Project , pp. 49
    • Lorenz, E.N.1
  • 39
    • 0000241853 scopus 로고
    • Deterministic nonperiodic flow
    • _, 1963: Deterministic nonperiodic flow. J. Atmos. Sci., 20, 130-141.
    • (1963) J. Atmos. Sci. , vol.20 , pp. 130-141
  • 40
    • 0031402774 scopus 로고    scopus 로고
    • Adjoint data assimilation in coupled atmosphere-ocean models: Determining model parameters in a simple equatorial model
    • Lu, J., and W. W. Hsieh, 1997: Adjoint data assimilation in coupled atmosphere-ocean models: Determining model parameters in a simple equatorial model. Quart. J. Roy. Meteor. Soc., 123, 2115-2139.
    • (1997) Quart. J. Roy. Meteor. Soc. , vol.123 , pp. 2115-2139
    • Lu, J.1    Hsieh, W.W.2
  • 41
    • 0041175235 scopus 로고    scopus 로고
    • Adjoint data assimilation in coupled atmosphere-ocean models: Determining initial conditions in a simple equatorial model
    • in press
    • _, and _, 1998a: Adjoint data assimilation in coupled atmosphere-ocean models: Determining initial conditions in a simple equatorial model. J. Meteor. Soc. Japan, in press.
    • (1998) J. Meteor. Soc. Japan
  • 42
    • 0542428734 scopus 로고    scopus 로고
    • On determining initial conditions and parameters in a simple coupled atmosphere-ocean model by adjoint data assimilation
    • in press
    • _, and _, 1998b: On determining initial conditions and parameters in a simple coupled atmosphere-ocean model by adjoint data assimilation. Tellus, in press.
    • (1998) Tellus
  • 43
    • 0031646493 scopus 로고    scopus 로고
    • Limitations of nonlinear PCA as performed with generic neural networks
    • Malthouse, E. C., 1998: Limitations of nonlinear PCA as performed with generic neural networks. IEEE Trans. Neural Networks, 9, 165-173.
    • (1998) IEEE Trans. Neural Networks , vol.9 , pp. 165-173
    • Malthouse, E.C.1
  • 44
    • 0001712213 scopus 로고    scopus 로고
    • A neural network for tornado prediction based on Doppler radar-derived attributes
    • Marzban, C., and G. J. Stumpf, 1996: A neural network for tornado prediction based on Doppler radar-derived attributes. J. Appl. Meteor., 35, 617-626.
    • (1996) J. Appl. Meteor. , vol.35 , pp. 617-626
    • Marzban, C.1    Stumpf, G.J.2
  • 45
    • 51249194645 scopus 로고
    • A logical calculus of the ideas immanent in neural nets
    • McCulloch, W. S., and W. Pitts, 1943: A logical calculus of the ideas immanent in neural nets. Bull. Math. Biophys., 5, 115-137.
    • (1943) Bull. Math. Biophys. , vol.5 , pp. 115-137
    • McCulloch, W.S.1    Pitts, W.2
  • 47
    • 0028584611 scopus 로고
    • Predicting Indian monsoon rainfall - A neural network approach
    • Navone, H. D., and H. A. Ceccatto, 1994: Predicting Indian monsoon rainfall - A neural network approach. Climate Dyn., 10, 305-312.
    • (1994) Climate Dyn. , vol.10 , pp. 305-312
    • Navone, H.D.1    Ceccatto, H.A.2
  • 48
    • 0027009587 scopus 로고
    • Toward automated interpretation of satellite imagery for navy shipboard applications
    • Peak, J. E., and P. M. Tag, 1992: Toward automated interpretation of satellite imagery for navy shipboard applications. Bull. Amer. Meteor. Soc., 73, 995-1008.
    • (1992) Bull. Amer. Meteor. Soc. , vol.73 , pp. 995-1008
    • Peak, J.E.1    Tag, P.M.2
  • 49
    • 0028578467 scopus 로고
    • Segmentation of satellite imagery using hierarchical thresholding and neural networks
    • _, and _, 1994: Segmentation of satellite imagery using hierarchical thresholding and neural networks. J. Appl. Meteor., 33, 605-616.
    • (1994) J. Appl. Meteor. , vol.33 , pp. 605-616
  • 50
    • 0000325341 scopus 로고
    • On lines and planes of closest fit to system of points in space
    • Pearson, K., 1901: On lines and planes of closest fit to system of points in space. Philos. Mag., Ser. 6, 2, 559-572.
    • (1901) Philos. Mag., Ser. , vol.6 , Issue.2 , pp. 559-572
    • Pearson, K.1
  • 51
    • 0024874304 scopus 로고
    • Random forcing and forecasting using principal oscillation pattern analysis
    • Penland, C., 1989: Random forcing and forecasting using principal oscillation pattern analysis. Mon. Wea. Rev., 117, 2165-2185.
    • (1989) Mon. Wea. Rev. , vol.117 , pp. 2165-2185
    • Penland, C.1
  • 57
    • 0000646059 scopus 로고
    • Learning internal representations by error propagation
    • D. E. Rumelhart, J. L. McClelland, and P. R. Group, Eds., MIT Press
    • Rumelhart, D. E., G. E. Hinton, and R. J. Williams, 1986: Learning internal representations by error propagation. Parallel Distributed Processing, D. E. Rumelhart, J. L. McClelland, and P. R. Group, Eds., Vol. 1, MIT Press, 318-362.
    • (1986) Parallel Distributed Processing , vol.1 , pp. 318-362
    • Rumelhart, D.E.1    Hinton, G.E.2    Williams, R.J.3
  • 58
    • 0000383868 scopus 로고
    • Parallel networks that learn to pronounce English text
    • Sejnowski, T. J., and C. R. Rosenberg, 1987: Parallel networks that learn to pronounce English text. Complex Syst., 1, 145-168.
    • (1987) Complex Syst. , vol.1 , pp. 145-168
    • Sejnowski, T.J.1    Rosenberg, C.R.2
  • 59
    • 0000421521 scopus 로고    scopus 로고
    • Skill of seasonal climate forecasts in Canada using canonical correlation analysis
    • Shabbar, A., and A. G. Barnston, 1996: Skill of seasonal climate forecasts in Canada using canonical correlation analysis. Mon. Wea. Rev., 124, 2370-2385.
    • (1996) Mon. Wea. Rev. , vol.124 , pp. 2370-2385
    • Shabbar, A.1    Barnston, A.G.2
  • 60
    • 0028195336 scopus 로고
    • Ocean surface wind retrievals from Special Sensor Microwave Imager data with neural networks
    • Stogryn, A. P., C. T. Butler, and T. J. Bartolac, 1994: Ocean surface wind retrievals from Special Sensor Microwave Imager data with neural networks. J. Geophys Res., 99, 981-984.
    • (1994) J. Geophys Res. , vol.99 , pp. 981-984
    • Stogryn, A.P.1    Butler, C.T.2    Bartolac, T.J.3
  • 61
    • 0029519567 scopus 로고
    • Periods of linear development of the ENSO cycle and POP forecast experiments
    • Tang, B., 1995: Periods of linear development of the ENSO cycle and POP forecast experiments. J. Climate, 8, 682-691.
    • (1995) J. Climate , vol.8 , pp. 682-691
    • Tang, B.1
  • 62
    • 21844503359 scopus 로고
    • A study of Arctic sea ice and sea-level pressure using POP and neural network methods
    • _, G. M. Flato, and G. Holloway, 1994: A study of Arctic sea ice and sea-level pressure using POP and neural network methods. Atmos.-Ocean, 32, 507-529.
    • (1994) Atmos.-Ocean , vol.32 , pp. 507-529
    • Flato, G.M.1    Holloway, G.2
  • 63
    • 84872545361 scopus 로고    scopus 로고
    • "Cleaning" neural networks with continuity constraint for prediction of noisy time series
    • Hong Kong, China
    • _, W. Hsieh, and F. Tangang, 1996: "Cleaning" neural networks with continuity constraint for prediction of noisy time series. Proc. Int. Conf. on Neural Information Processing, Hong Kong, China, 722-725.
    • (1996) Proc. Int. Conf. on Neural Information Processing , pp. 722-725
    • Hsieh, W.1    Tangang, F.2
  • 64
    • 0026258339 scopus 로고
    • Time series forecasting using neural networks vs. Box-Jenkins methodology
    • Tang, Z., C. de Almeida, and P. A. Fishwick, 1991: Time series forecasting using neural networks vs. Box-Jenkins methodology. Simulation, 57, 303-310.
    • (1991) Simulation , vol.57 , pp. 303-310
    • Tang, Z.1    De Almeida, C.2    Fishwick, P.A.3
  • 65
    • 0001275437 scopus 로고    scopus 로고
    • Forecasting the equatorial Pacific sea surface temperatures by neural network models
    • Tangang, F. T., W. W. Hsieh, and B. Tang, 1997: Forecasting the equatorial Pacific sea surface temperatures by neural network models. Climate Dyn., 13, 135-147.
    • (1997) Climate Dyn. , vol.13 , pp. 135-147
    • Tangang, F.T.1    Hsieh, W.W.2    Tang, B.3
  • 66
    • 0032522032 scopus 로고    scopus 로고
    • Forecasting the regional sea surface temperatures of the tropical Pacific by neural network models, with wind stress and sea level pressure as predictors
    • _, _, and _, 1998a. Forecasting the regional sea surface temperatures of the tropical Pacific by neural network models, with wind stress and sea level pressure as predictors. J. Geophys. Res., 103, 7511-7522.
    • (1998) J. Geophys. Res. , vol.103 , pp. 7511-7522
  • 67
    • 0031777214 scopus 로고    scopus 로고
    • Forecasting ENSO events: A neural network - Extended EOF approach
    • _, B. Tang, A. H. Monahan, and W. W. Hsieh, 1998b. Forecasting ENSO events: A neural network - extended EOF approach. J. Climate, 11, 29-41.
    • (1998) J. Climate , vol.11 , pp. 29-41
    • Tang, B.1    Monahan, A.H.2    Hsieh, W.W.3
  • 69
    • 0031396582 scopus 로고    scopus 로고
    • Performance of an advanced MOS system in the 1996-97 National Collegiate Weather Forecasting Contest
    • Vislocky, R. L., and J. M. Fritsch, 1997: Performance of an advanced MOS system in the 1996-97 National Collegiate Weather Forecasting Contest. Bull. Amer. Meteor. Soc., 78, 2851-2857.
    • (1997) Bull. Amer. Meteor. Soc. , vol.78 , pp. 2851-2857
    • Vislocky, R.L.1    Fritsch, J.M.2
  • 71
    • 0020347855 scopus 로고
    • Example of extended empirical orthogonal functions
    • Weare, B. C., and J. S. Nasstrom, 1982: Example of extended empirical orthogonal functions. Mon. Wea. Rev., 110, 481-485.
    • (1982) Mon. Wea. Rev. , vol.110 , pp. 481-485
    • Weare, B.C.1    Nasstrom, J.S.2


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