23rd Conference Probability and Statistics in the Atmospheric Sciences
Authors & Presenters
Please review our Presenter Guidelines.
Please note that abstract fees are only refundable if your abstract is rejected for presentation and Any abstracts withdrawn after acceptance must still be paid in full.
- Check/Change Abstract Title and Author Listing Deadline: 2 November 2015
- Oral Presentation Upload Deadline (before meeting): 4 January 2016
- Supplementary Information Upload Deadline 11 February 2015
Sponsors and Organizers
The 23rd Conference Probability and Statistics in the Atmospheric Sciences is organized by the AMS Committee on Probability and Statistics and is sponsored by the American Meteorological Society.
Call for Papers
The theme for the 2016 AMS Annual Meeting, “Earth System Science in Service to Society”, weaves the many parts of AMS into a common core. Emphasizing the academic and research strength of AMS, the theme also connects that research to the benefits that society gains from our science. AMS merges the physical, chemical, and biological study of the Earth with human-centered “domains of action”: (1) Observing, (2) Analysis and research leading to understanding, (3) Modeling and prediction, and (4) Social sciences – how people deal with Earth. “Service to Society” explicitly evokes the integrated and complementary government and commercial enterprise that the AMS has done so much to foster over the last decade. The 2016 meeting integrates AMS’ proud, nearly 100-year history of making a positive difference in the lives of our citizens by continually communicating the advances of its science research to the public and policy makers.
Papers are solicited on all aspects of the application of probability and statistics to the atmospheric sciences, including but not limited to:
• Best practices for statistical inference in the atmospheric sciences
• Dealing with nonstationarity, and other topics in climate analysis and prediction
• Ensemble forecasting and predictability
• Extreme-value analysis, prediction, and evaluation
• Forecast evaluation/verification
• Machine learning methods in the atmospheric sciences
• Probabilistic methods in weather and climate services
• Spatial statistics and time series
• Statistical downscaling
• Statistical postprocessing of ensemble and traditional dynamical forecasts
• Statistical weather forecasting
• Weather derivatives and risk management
We plan for the topic on statistical inference to occupy a full day, with several invited papers and a panel discussion in addition to contributed papers.
For additional information please contact the program chair, Dan Wilks.