The first author of the paper wishes to express his sincere appreciation to D. B. Rao for his reviews of the manuscript and for his continual encouragement throughout the course of this investigation. He would also like to thank V. Krasnopolsky for his clarification on the discussions of the OMBNN neural network algorithm and for his help in the preparation of Table 1 and Fig. 1. Thanks also go to W. Gemmill for his programming support in the implementation of OMBNN wind algorithm in the parallel testing experiment.
Bose, N. K., and P. Liang, 1996: Neural Network Fundamentals with Graphs Algorithms and Applications. McGraw-Hill, 478 pp.
Caplan, P., J. Derber, W. Gemmill, S.-Y. Hong, H.-L. Pan, and D. Parrish, 1997: Changes to the 1995 NCEP operational Medium- Range Forecast model analysis–forecast system. Wea. Forecasting,12, 581–594.
Goerss, J., and P. Phoebus, 1992: The assimilation of DMSP retrieval products into the Navy’s atmospheric prediction system. Abstracts, NMC/NESDIS/DOD Conf. on DMSP Retrieval Products, Washington DC, NMC/NESDIS/DOD. [Available from National Centers for Environmental Prediction, Washington, DC 20233.].
Goodberlet, M. A., C. T. Swift, and J. Wikerson, 1989: Remote sensing of ocean surface winds with the Special Sensor Microwave/Imager. J. Geophys. Res.,94, 547–555.
Kanamitsu, M., 1989: Description of the NMC global data assimilation and forecast system. Wea. Forecasting,4, 334–342.
——, and Coauthors, 1991: Recent changes implemented into the global forecast system at NMC. Wea. Forecasting,6, 422–435.
Krasnopolsky, V., L. Breaker, and W. Gemmill, 1995a: A neural network as a nonlinear transfer function model for retrieving surface winds speeds from the special sensor microwave imager. J. Geophys. Res.,100, 11033–11045.
——, W. Gemmill, and L. Breaker, 1995b: Improved SSM/I wind speed retrievals at high wind speeds. NCEP Tech. Note, OMB Contribution 111, 46 pp. [Available from National Centers for Environmental Prediction, Washington, DC 20233.].
——, ——, and ——, 1996:A new transfer function for SSM/I based on an expanded neural network architecture. NCEP Tech. Note 137, 38 pp. [Available from National Centers for Environmental Prediction, Washington, DC 20233.].
Parrish, D., and J. Derber, 1992: The National Meteorological Center’s Spectral Statistical-Interpolation Analysis System. Mon. Wea. Rev.,120, 1747–1763.
Petty, G. W., and K. B. Katsaros, 1993: The response of the SSM/I to the marine environment. Part I: An analytic model for the atmospheric component of observed brightness temperatures. J. Atmos. Oceanic Technol.,10, 746–761.
——, and ——, 1994: The response of the SSM/I to the marine environment. Part II: A parameterization of the effect of the sea surface slope distribution on emission and reflection. J. Atmos. Oceanic Technol.,11, 617–628.
Phoebus, P., and J. Goerss, 1991: The operational assimilation of SSM/I wind speed data. Preprints, Ninth Conf. on Numerical Weather Prediction, Denver, CO, Amer. Meteor. Soc., 569–572.
Stogryn, A., C. Butler, and T. Bartolac, 1994: Ocean surface wind retrievals from special sensor microwave imager data with neural networks. J. Geophys. Res.,99, 981–984.
Yu, T.-W., and D. Deaven, 1991: Use of SSM/I wind speed data at NMC’s GDAS. Preprints, Ninth Conf. on Numerical Weather Prediction, Denver, CO, Amer. Meteor. Soc., 416–417.
——, W. Gemmill, and J. Woollen, 1992: Use of SSM/I wind speed data in the operational numerical weather prediction system at NMC. Abstracts, NMC/NESDIS/DOD Conf. on DMSP Retrieval Products, Washington DC, NMC/NESDIS/DOD. [Available from National Centers for Environmental Prediction, Washington, DC 20233.].