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Numerical International Polar Year

THEMES: NOAA activities for the second half of the IPY period NOAA contributions to the IPY legacy MOTIVATION:

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Numerical International Polar Year

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  1. THEMES: • NOAA activities for the second half of the IPY period • NOAA contributions to the IPY legacy • MOTIVATION: • Historically, each IPY has been characterized by exploring new directions of Arctic studies and employing new technologies. We propose that an advanced numerical modelling component during IPY 2007-2008 would be a major accomplishment for enhancing Arctic studies in the modern world. • Model development and improvement represent the highest levels of integration and synthesis. IPY will be a benchmark for Arctic studies so it would be very timely to revaluate existing models and their results in order to improve and revalidate them. Numerical International Polar Year Andrey Proshutinsky and AOMIP group, Woods Hole Oceanographic Institution NOAA Arctic Science Priorities Workshop, February 2-3 2005, Silver Spring, MD

  2. Model development and improvement represent the highest levelsof integration and synthesis Ocean Physics Sea Ice Physics RASN IARC ice NCAR IOS RASM AWI NPS NYU UW Improved models, diagnostics and predictions of Arctic system variability LLA LLN

  3. THE CONCEPT IPYs serve as benchmarks of Arctic climate states and, in principal, differences between these states reflect Arctic climate change. Unfortunately, the temporal resolution of IPYs does not resolve natural climate cycling and much more information is needed for robust conclusions. • In order to fill the temporal and spatial informational gaps and answer major questions related to the Arctic climate change, we propose employing methods of numerical modeling, namely: a set of Arctic numerical models (atmospheric, sea ice, oceanic, terrestrial, coupled and uncoupled, regional and global) developed and run by experts of the international community specifically to satisfy IPY goals and objectives.

  4. Proposed Activity:Support investigations of Arctic Ocean climate using numerical models At the IPY planning stage, model results can be used to assist in designing the observational network. During IPY, operational models will diagnose and predict atmospheric, oceanic and sea ice conditions to assist field activities and to optimally correct observational schemes. After the IPY field phase, modelling will be used for Arctic atmosphere, sea ice, ocean and terrestrial data reconstruction for the period of existing observations, for near future predictions, and to resolve major questions of the Arctic climate change processes with better accuracy. Arctic environmental data collected during IPYs will be used for model calibration and validation and a reconstruction of forcing parameters. Through the interface between regional Arctic modelling and global climate modelling, we will better determine the interactive interdependencies between Arctic processes and global climate variability. Employing a set of different Arctic models and internationally coordinating the numerical experiments will guarantee the highest quality results and effective solutions for coordinating IPY 2007-2008 observations.

  5. The Mechanics • There will be a steering committee to effectively manage and coordinate the project. This committee will consist of project investigators, colleagues from other disciplines, experts from other IPY activities, and stakeholders. This committee will provide overall project guidance, formulate numerical experiment strategy, and develop international collaboration. • List of core investigators includes (but is not limited to): • Arctic Ocean Model Intercomparison Project (AOMIP) team • Arctic Regional Climate Model Intercomparison Project (ARCMIP) team • Sea Ice Model Intercomparison Project (SIMIP) team

  6. Project Investigators A. Proshutinsky Woods Hole Oceanographic Institution, USA R. Gerdes Alfred Wegener Institute, Germany S. Hakkinen Goddard Space Flight Center, USA D. Holland New-York University, USA G. Holloway Institute of Ocean Science, Canada M. Johnson Institute of Marine Science, UAF, USA H. Goose Louvain-la-Neuve, Belgium M. Karcher, C. Koeberle Alfred Wegener Institute, Germany F. Kauker Alfred Wegener Institute, Germany W. Maslowski Naval Postgraduate School, USA M. Steele, J. Zhang University of Washington, USA J. Wang, W. Hibler International Arctic Research Center, UAF, USA N. Yakovlev, Russian Academy of Science, Moscow E. Golubeva, G. Platov Russian Academy of Science, Novosibirsk

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