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2014 AMS Annual Meeting

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18th Conference on Integrated Observing and Assimilation Systems for Atmosphere, Oceans, and Land Surface (IOAS-AOLS) Student Awards

18th Conference on Integrated Observing and Assimilation Systems for Atmosphere, Oceans, and Land Surface (IOAS-AOLS) Call for Papers

Partial travel support (of up to $550 each) and two prizes (of $200 each) will be awarded in recognition of outstanding abstracts and oral presentations at the IOAS-AOLS conference.

To be eligible for apply for an award, each student applicant must meet the following conditions:

  1. Full-time undergraduate or graduate student enrolled at a University,
  2. Lead author, personally presenting the work,
  3. Submission of an abstract to a session in which IOAS-AOLS is the lead conference, and submission of an extended abstract.

The student needs to indicate whether they wish to be considered for travel support and/or the best student paper prize. For those who are requesting partial travel support, in addition to the above conditions, the IOAS-AOLS co-chairs will review the abstract to determine how their work meets one or more of the following focus areas:

  1. Atmospheric observations, in situ and remote, including from satellites: Advantages and shortcomings compared with other observing systems, and their influences on global and regional numerical weather prediction
  2. Assimilation of observations (ocean, atmosphere, and land surface) into models: assimilation methods; minimization techniques; forward model and their adjoints; incorporation of constraints; error statistics
  3. Experiments involving observations, real or hypothetical: data impact tests (sensitivity of forecasts to a particular source of observations); observing system simulation experiments (OSSEs)
  4. Application of the above technologies and concepts for extreme weather events
  5. Ocean observations: What do ocean observations tell us about the ocean environment and how do they contribute to its prediction?
  6. Field experiments: observational results from past field experiments; potential relevance of the field observations to operational prediction.
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