Short Course Registration
Conference Registration*
Short Course Registration
Conference Registration
Conference Registration (continues through Thursday, 13 February)
Session 1 Generic AI Methods and Applications
| 9:00 AM | 1.1 | Paper moved to poster session 1, New paper number p1.7 | |
| 9:01 AM | 1.1a | GENETIC ALGORITHMS AND THEIR APPLICATIONS IN ENVIRONMENTAL SCIENCE  Sue Ellen Haupt, Utah State University, Logan, UT; and R. L. Haupt | |
| 9:45 AM | 1.2 | Neural networks for nonlinear post-processing of model output Caren Marzban, CAPS/Univ. of Oklahoma, Norman, OK and Univ. of Washington, Seattle, WA | |
| 10:30 AM | Coffee Break in poster session room | ||
| 10:45 AM | 1.3 | New formulations for estimating models from data Vladimir Cherkassky, University of Minnesota, Minneapolis, MN | |
| 11:30 AM | 1.4 | Strengths and limitations of artificial neural networks in the context of numerical weather prediction Frédéric Chevallier, ECMWF, Reading, Berkshire, United Kingdom | |
| 12:15 PM | Lunch Break | ||
| 1:45 PM | 1.5 | Support Vector Machines and their applications Dennis DeCoste, JPL, Pasadena, CA |
Joint Poster Session 1 Operational Applications and Artificial Intelligence (Joint between 12th Conference on Satellite Meteorology and Oceanography and Third Conference on Artificial Intelligence Applications to Environmental Science)
| JP1.1 | Real-time multi-satellite precipitation estimation and assimilation Mohan L. Nirala, NASA/GSFC, Greenbelt, MD; and P. Houser | |
| JP1.2 | Validation of an Operational Global Precipitation Analysis at Short Time Scales F. Joseph Turk, NRL, Monterey, CA; and E. E. Ebert, H. J. Oh, B.-J. Sohn, V. Levizzani, E. A. Smith, and R. Ferraro | |
| JP1.3 | Validation of a microwave-based tropical rainfall potential (TRaP) for landfalling tropical cyclones Michael A. Turk, NOAA/NESDIS, Washington, DC; and S. J. Kusselson, R. R. Ferraro, P. Pellegrino, S. Kidder, and J. Yang | |
| JP1.4 | Improvements in Real-Time Statistical Tropical Cyclone Intensity Forecasts Using Satellite Data Mark DeMaria, NOAA/NESDIS, Ft. Collins, CO; and M. Mainelli, L. K. Shay, J. A. Knaff, and J. P. Kossin | |
| JP1.5 | A demonstration of real-time transmission and display of GOES imagery aboard the NOAA P-3 aircraft during the 2002 hurricane season John A. Knaff, CIRA/Colorado State Univ., Fort Collins, CO; and N. Wang, M. DeMaria, R. M. Zehr, J. S. Griffin, and F. D. Marks | |
| JP1.6 | Status and development of GOES Wind Products at NOAA/NESDIS Jaime M. Daniels, NOAA/NESDIS/ORA, Camp Springs, MD; and C. Velden, G. A. Dengel, D. R. Stettner, and W. Bresky | |
| JP1.7 | Operational satellite-derived tropospheric winds for DoD models and applications Charles E. Skupniewicz, FNMOC, Monterey, CA; and C. S. Velden, G. Dengel, C. D. Schuett, and R. Pauley | |
| JP1.8 | Using GOES Satellite Products to Enhance National Weather Service Warning Operations Samuel L. Lashley, NOAA/NWS, Syracuse, IN | |
| JP1.9 | Experimental satellite products usage on AWIPS Kevin J. Schrab, NOAA/NWS, Salt Lake City, UT | |
| JP1.10 | Utilizing the Web to enhance availability and utilization of Polar-orbiting Operational Environmental Satellite (POES) Data and Products Diane Holmes, Mitretek Systems, Inc., Falls Church, VA; and S. L. Bunin and T. Schott | |
| JP1.11 | PAPER WITHDRAWN | |
| JP1.12 | Aerosol monitoring over the U.S. from GOES-8 Kenneth R. Knapp, CIRA and NOAA/NESDIS/ORA, Camp Springs, MD | |
| JP1.13 | A Near-Real Time AIRS Processing, Distribution, and Visualization System Walter Wolf, QSS Group Inc., Lanham, MD; and L. Zhou, M. Goldberg, Y. Qu, and M. Divakarla | |
| JP1.14 | MODIS/AIRS instrument direct broadcast products and applications Kathleen I. Strabala, CIMSS/Univ. of Wisconsin, Madison, WI; and L. E. Gumley, T. Rink, H.-L. Huang, and R. Dengel | |
| JP1.15 | Advanced-TOVS (ATOVS) sounding products from NOAA polar orbiting environmental satellites Anthony L. Reale, NOAA/NESDIS, Washington, DC; and M. W. Chalfant, A. S. Allegrino, F. H. Tilley, M. P. Ferguson, and M. E. Pettey | |
| JP1.16 | Theater snow depth estimates for Department of Defense applications Paul J. McCrone, Air Force Weather Agency, Offutt AFB, NE | |
| JP1.17 | An intelligent NN system for quality controlled retrieving the wind speed from SSM/I measurements Vladimir M. Krasnopolsky, SAIC and NOAA/NWS/NCEP, Camp Springs, MD | |
| JP1.18 | Satellite estimates of ocean surface latent heat flux Charles Jones, University of California, Santa Barbara, CA; and P. Peterson, C. Gautier, and W. T. Liu | |
| JP1.19 | Processing realtime satellite information to nowcast convective initiation and its characteristics John R. Mecikalski, CIMSS/Univ. of Wisconsin, Madison, WI; and R. D. Roberts, C. J. Kessinger, K. M. Bedka, B. L. DeWolf, and S. M. Thomas | |
| JP1.20 | Using the NCAR Auto-NowCast System to Nowcast Oceanic Convection Cathy Kessinger, NCAR, Boulder, CO; and R. Roberts and R. Bankert | |
| JP1.21 | Using supervised learning for specific meteorological satellite applications Richard L. Bankert, NRL, Monterey, CA; and J. D. Hawkins | |
| JP1.22 | Cloud classification of satellite radiance data by Multicategory Support Vector Machines Yoonkyung Lee, Ohio State Univ., Columbus, OH; and G. Wahba and S. A. Ackerman | |
| JP1.23 | Comparison Between Bayesian Techniques and Self-Organizing Feature Map for TMI Measurement Classification: Application to Rain Rate Retrieval C. Mallet, CETP, Velizy, France; and N. Viltard and C. Klapisz | |
| JP1.24 | Future Architectures for Operational Forecasting: Two-way Interacting SensorWeb and Model/Assimilation System Mark Steiner, NASA/GSFC, Greenbelt, MD; and M. Seablom, S. Neeck, G. McConaughy, M. Clausen, M. Kalb, and R. Muller |
1 Formal Poster Viewing with Coffee Break
Joint Session 1 Artificial Intelligence (Joint between 12th Conference on Satellite Meteorology and Oceanography and Third Conference on Artificial Intelligence Applications to Environmental Science)
| 4:00 PM | J1.1 | Ozone Profile Retrieval from GOME Data using a Neural Network inverse Model Martin D. Müller, Center for Solar Energy and Hydrogen Research (ZSW), Stuttgart, Germany; and A. K. Kaifel | |
| 4:30 PM | J1.2 | Use of a neuro-variational method to improve atmosphere and ocean parameter retrieval from ocean color sensor Cedric Jamet, Univ. of Paris, Paris, France; and S. Thiria, C. Moulin, and M. Crepon |
Formal Opening of Exhibits with Reception (Cash Bar)
Sessions End for the Day
Session 3 Neural Networks
| 8:30 AM | 3.1 | Probabilistic tropical cyclogenesis prediction Christopher C. Hennon, Ohio State University, Columbus, OH | |
| 8:45 AM | 3.2 | Optimization and Performance of a Neural Network Model Forecasting Water Levels for the Corpus Christi, Texas, Estuary Philippe E. Tissot, Texas A&M University, Corpus Christi, TX; and P. R. Michaud and D. T. Cox | |
| 9:00 AM | 3.3 | NN for local meteorological forecasting Reinaldo Bomfim Silveira, Instituto Nacional de Meteorologia, Brasilia, Brazil; and S. Sugahara | |
| 9:15 AM | 3.4 | Neural Networks Estimates Atmospheric Variables in the Caribbean Basin Nazario Ramirez-Beltran, University of Puerto Rico, Mayaguez, Puerto Rico; and A. Winter, F. Chong Rengifo, A. Veneros, and N. R. Escalante | |
| 9:30 AM | 3.5 | Mixing height short range forecasting through neural network modeling applied to radon and meteorological data Antonello Pasini, CNR, Rome, Italy; and F. Ameli and M. Loré | |
| 9:45 AM | Formal poster viewing with coffee break | ||
| 3.6 | PAPER WITHDRAWN | ||
| 11:00 AM | 3.7 | Classifying El Nino and La Nina events using the Kohonen maps Zouhair Lachkar, Direction de la Meteorologie Nationale du Maroc, Casablanca, Morocco; and S. Thiria, F. Badran, J.-P. Boulanger, and C. Menkes | |
| 11:15 AM | 3.8 | An adaptive nonlinear MOS scheme for precipitation forecasts using neural networks Yuval, University of British Columbia, Vancouver, BC, Canada; and W. W. Hsieh | |
| 11:30 AM | 3.9 | A Nonlinear Statistical Model of Turbulent air-sea Fluxes Denis Bourras, JPL, Pasadena, CA; and G. Caniaux and G. Mungov | |
| 11:45 AM | 3.10 | A Combination of Empirical Orthogonal Function and Neural Network Approaches for Parameterizing Nonlinear Interactions in Wind Wave Models Vladimir M. Krasnopolsky, NOAA/NCEP/EMC, Camp Springs, MD; and H. L. Tolman and D. V. Chalikov |
Poster Session 1 All AI applications
| P1.1 | A Hidden Markov Model Approach for Lithology Identification from Logs Maria Padron, Institut National des Télécommunications, Evry, France; and S. Garcia-Salicetti, D. Barraez, B. Dorizzi, and S. Thyria | |
| P1.2 | Classifying TOA Ocean Color signals by using a Kohonen map methodology Sylvie Thiria, University of Paris, Paris, France; and A. Niang, F. Badran, C. Moulin, and M. Crepon | |
| P1.3 | Determination of error in ARPS model surface temperature forecasts using statistical methods Andrew A. Taylor, Univ. of Oklahoma, Norman, OK; and L. M. Leslie and K. K. Droegemeier | |
| P1.4 | Nonlinear Approach to Winter North Atlantic SLP Variability with the Help of Autoassociative Neural Network Ladislav Metelka, Czech Hydrometeorological Institute, Hradec Kralove, Czech Republic | |
| P1.5 | Statistical Downscaling Technique using Artificial Neural Networks for localized precipitation forecasts over São Paulo region María Cleofé Valverde Ramírez, INPE, São José dos Campos - São Paulo, Brazil; and H. de Campos Velho and N. J. Ferreira | |
| P1.6 | The Radar Echo Classifier: A Fuzzy Logic Algorithm for the WSR-88D Cathy Kessinger, NCAR, Boulder, CO; and S. Ellis and J. Van Andel | |
| P1.7 | Genetic Algorithms in Geophysical Fluid Dynamics (Formerly Paper number 1.1) Sue Ellen Haupt, Utah State University, Logan, UT | |
| P1.8 | Neural Networks for spatial interpolation of meteorological data Juan P. Rigol, University of Edinburgh, Edinburgh, Scotland, United Kingdom |
Lunch Break
Session 4 All aspects of artificial intelligence applications to environmental sciences
| 2:15 PM | 4.0a | Multiagent Systems for Environmental Perception Francesco Amigoni, Politecnico di Milano, Milano, Italy; and M. Somalvico | |
| 2:45 PM | 4.1 | Pricing a financial instrument to guarantee the accuracy of a weather forecast Harvey Stern, Bureau of Meteorology, Melbourne, Victoria, Australia; and S. Dawkins | |
| 4.2 | PAPER WITHDRAWN | ||
| 2:59 PM | 4.3 | Fuzzy image processing applied to time series analysis R. Andrew Weekley, NCAR, Boulder, CO; and R. K. Goodrich and L. B. Cornman | |
| 3:14 PM | 4.4 | Fuzzy Case-Based Prediction of Cloud Ceiling and Visibility Bjarne K. Hansen, Dalhousie University, Halifax, NS, Canada; and D. Riordan | |
| 3:29 PM | Coffee Break in exhibit hall (exhibits open 1:30–6:30 p.m. | ||
| 3:59 PM | 4.5 | Simplified nonlinear principal component analysis Beiwei Lu, University of British Columbia, Vancouver, BC, Canada; and W. W. Hsieh | |
| 4:14 PM | 4.6 | Development of an Events-Oriented Verification System Using data mining and Image Processing Algorithms Michael E. Baldwin, CIMMS/Univ. of Oklahoma, Norman, OK; and S. Lakshmivarahan | |
| 4:29 PM | 4.7 | Application of knowledge discovery from databases to remote weather assessment Michael Hadjimichael, NRL, Monterey, CA; and R. L. Bankert, A. P. Kuciauskas, K. L. Richardson, and G. N. Vogel | |
| 4:44 PM | 4.8 | Adaptive Data Fusion of Meteorological Forecast Modules Shel Gerding, NCAR, Boulder, CO; and B. Myers | |
| 4:59 PM | 4.9 | A Fuzzy Logic System for Automated Short Term Aviation Weather Forecasts Tom Hicks, Harris Corporation, Melbourne, FL; and T. Crawford and M. Wilson |
Conference Ends
Special Address. Conrad C. Lautenbacher, NOAA, Washington, DC
Coffee Break in the Ballroom Foyer, 2nd Level, Promenade
Presidential Forum: Administration Priorities in Climate Change Research and Technology
Lunch Break
Simpsons Symposium—A Tribute to Robert and Joanne Simpson
Reception (Cash Bar)
AMS Annual Awards Banquet
Simpsons Symposium—A Tribute to Robert and Joanne Simpson
Formal Poster Viewing with Coffee Break
Conference Ends
Closing Reception in Exhibit Hall (Cash Bar)
Simpsons Banquet
Closing Event at the Long Beach Aquarium on the Pacific