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2013 AMS Annual Meeting

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Third Symposium on Advances in Modeling and Analysis Using Python

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.

The application of object-oriented programming and other advances in computer science to the atmospheric and oceanic sciences has in turn led to advances in modeling and analysis tools and methods. This symposium focuses on applications of the open-source language Python and seeks to disseminate advances using Python in the atmospheric and oceanic sciences, as well as grow the earth sciences Python community. Papers describing Python work in applications, methodologies, and package development in all areas of meteorology, climatology, oceanography, and space sciences are welcome, including (but not limited to):  modeling, time series analysis, air quality, satellite data processing, in-situ data analysis, Python as a software integration platform, visualization, gridding, model intercomparison, and very large (petabyte) dataset manipulation and access.  Following the overall annual meeting theme, the Symposium is  also soliciting papers on advances in using Python to create, analyze, disseminate, and manage climate and weather projections and predictions.

For additional information please contact the program chairperson, Johnny Lin, Physics Department, North Park University (jlin@northpark.edu).

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