Baltes Rebecca

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Baltes
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Rebecca
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  • Article
    Autonomous and Lagrangian ocean observations for Atlantic tropical cyclone studies and forecasts
    (Oceanography Society, 2017-06) Goni, Gustavo J. ; Todd, Robert E. ; Jayne, Steven R. ; Halliwell, George R. ; Glenn, Scott ; Dong, Jili ; Curry, Ruth G. ; Domingues, Ricardo ; Bringas, Francis ; Centurioni, Luca R. ; DiMarco, Steven F. ; Miles, Travis ; Morell, Julio M. ; Pomales, Luis ; Kim, Hyun-Sook ; Robbins, Pelle E. ; Gawarkiewicz, Glen G. ; Wilkin, John L. ; Heiderich, Joleen ; Baltes, Rebecca ; Cione, Joseph J. ; Seroka, Greg ; Knee, Kelly ; Sanabia, Elizabeth
    The tropical Atlantic basin is one of seven global regions where tropical cyclones (TCs) commonly originate, intensify, and affect highly populated coastal areas. Under appropriate atmospheric conditions, TC intensification can be linked to upper-ocean properties. Errors in Atlantic TC intensification forecasts have not been significantly reduced during the last 25 years. The combined use of in situ and satellite observations, particularly of temperature and salinity ahead of TCs, has the potential to improve the representation of the ocean, more accurately initialize hurricane intensity forecast models, and identify areas where TCs may intensify. However, a sustained in situ ocean observing system in the tropical North Atlantic Ocean and Caribbean Sea dedicated to measuring subsurface temperature, salinity, and density fields in support of TC intensity studies and forecasts has yet to be designed and implemented. Autonomous and Lagrangian platforms and sensors offer cost-effective opportunities to accomplish this objective. Here, we highlight recent efforts to use autonomous platforms and sensors, including surface drifters, profiling floats, underwater gliders, and dropsondes, to better understand air-sea processes during high-wind events, particularly those geared toward improving hurricane intensity forecasts. Real-time data availability is key for assimilation into numerical weather forecast models.
  • Article
    Introduction to special section on The U.S. IOOS Coastal and Ocean Modeling Testbed
    (John Wiley & Sons, 2013-12-11) Luettich, Richard A. ; Wright, L. Donelson ; Signell, Richard P. ; Friedrichs, Carl T. ; Friedrichs, Marjorie A. M. ; Harding, John ; Fennel, Katja ; Howlett, Eoin ; Graves, Sara J. ; Smith, Elizabeth ; Crane, Gary ; Baltes, Rebecca
    Strong and strategic collaborations among experts from academia, federal operational centers, and industry have been forged to create a U.S. IOOS Coastal and Ocean Modeling Testbed (COMT). The COMT mission is to accelerate the transition of scientific and technical advances from the coastal and ocean modeling research community to improved operational ocean products and services. This is achieved via the evaluation of existing technology or the development of new technology depending on the status of technology within the research community. The initial phase of the COMT has addressed three coastal and ocean prediction challenges of great societal importance: estuarine hypoxia, shelf hypoxia, and coastal inundation. A fourth effort concentrated on providing and refining the cyberinfrastructure and cyber tools to support the modeling work and to advance interoperability and community access to the COMT archive. This paper presents an overview of the initiation of the COMT, the findings of each team and a discussion of the role of the COMT in research to operations and its interface with the coastal and ocean modeling community in general. Detailed technical results are presented in the accompanying series of 16 technical papers in this special issue.
  • Preprint
    Advancing coastal ocean modelling, analysis, and prediction for the US Integrated Ocean Observing System
    ( 2017-04-19) Wilkin, John L. ; Rosenfeld, Leslie K. ; Allen, Arthur ; Baltes, Rebecca ; Baptista, Antonio ; He, Ruoying ; Hogan, Patrick ; Kurapov, Alexander ; Mehra, Avichal ; Quintrell, Josie ; Schwab, David ; Signell, Richard P. ; Smith, Jane
    This paper outlines strategies that would advance coastal ocean modeling, analysis and prediction as a complement to the observing and data management activities of the coastal components of the U.S. Integrated Ocean Observing System (IOOS®) and the Global Ocean Observing System (GOOS). The views presented are the consensus of a group of U.S. based researchers with a cross-section of coastal oceanography and ocean modeling expertise and community representation drawn from Regional and U.S. Federal partners in IOOS. Priorities for research and development are suggested that would enhance the value of IOOS observations through model-based synthesis, deliver better model-based information products, and assist the design, evaluation and operation of the observing system itself. The proposed priorities are: model coupling, data assimilation, nearshore processes, cyberinfrastructure and model skill assessment, modeling for observing system design, evaluation and operation, ensemble prediction, and fast predictors. Approaches are suggested to accomplish substantial progress in a 3-8 year timeframe. In addition, the group proposes steps to promote collaboration between research and operations groups in Regional Associations, U.S. Federal Agencies, and the international ocean research community in general that would foster coordination on scientific and technical issues, and strengthen federal-academic partnerships benefiting IOOS stakeholders and end users.