Symposium on the Role of Statistical Methods in Weather and Climate Prediction
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The theme for the 2013 AMS Annual Meeting is “Taking Predictions to the Next Level: Expanding Beyond Today's Weather, Water, and Climate Forecasting and Projections”. Over the past 60 years the meteorological community has made tremendous strides in making prediction a fundamental part of its scientific and operational/service heritage through the development and application of complex numerical models involving the atmosphere, ocean, land and cryosphere components of the Earth System. This theme will serve as a catalyst for the 2013 AMS annual meeting by focusing the attention of the research and operational communities, including those who are involved in accelerating the transition of research results into operations. Furthermore, the increasing use of predictions by decision makers throughout federal, state, and local emergency management government agencies and by private/commercial sectors will serve as an important component for this annual meeting along with the extension of predictive capabilities into a broader domain, including public health, food security, air and water quality, alternative energy and responses to climate trends.
Following this theme, this symposium is soliciting papers on the role of statistical and probabilistic methods in the prediction systems for weather, climate, and user variables (e.g., hydrologic prediction). In addition to papers focused on methodologies and advances in capabilities, some talks on user “best practices” are also solicited. A number of invited talks will provide overviews of the state-of-the-art of research and best practices and some specific discussions will focus on advances in these areas. A poster session will be included to allow greater participation in the symposium. The symposium is also planning to convene joint sessions with the Hydrology, Climate Variability and Change, Artificial Intelligence,, and Planned and Inadvertent Weather Modification committees, so presentations that concern the crossover of statistical and probabilistic methods with these topic areas are also invited.
For additional information please contact the program chairpersons, Barbara Brown (email@example.com), Dan Collins (firstname.lastname@example.org), Bob Glahn (email@example.com), and Scott Sellars (firstname.lastname@example.org).