8,452 research outputs found

    Advancing coastal ocean modelling, analysis, and prediction for the US Integrated Ocean Observing System

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    Author Posting. © The Author(s), 2017. This is the author's version of the work. It is posted here by permission of Taylor & Francis for personal use, not for redistribution. The definitive version was published in Journal of Operational Oceanography 10 (2017): 115-126, doi:10.1080/1755876X.2017.1322026.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.2018-05-2

    CLIVAR Exchanges - Special Issue: WCRP Coupled Model Intercomparison Project - Phase 5 - CMIP5

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    Observational needs of sea surface temperature

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    Sea surface temperature (SST) is a fundamental physical variable for understanding, quantifying and predicting complex interactions between the ocean and the atmosphere. Such processes determine how heat from the sun is redistributed across the global oceans, directly impacting large- and small-scale weather and climate patterns. The provision of daily maps of global SST for operational systems, climate modeling and the broader scientific community is now a mature and sustained service coordinated by the Group for High Resolution Sea Surface Temperature (GHRSST) and the CEOS SST Virtual Constellation (CEOS SST-VC). Data streams are shared, indexed, processed, quality controlled, analyzed, and documented within a Regional/Global Task Sharing (R/GTS) framework, which is implemented internationally in a distributed manner. Products rely on a combination of low-Earth orbit infrared and microwave satellite imagery, geostationary orbit infrared satellite imagery, and in situ data from moored and drifting buoys, Argo floats, and a suite of independent, fully characterized and traceable in situ measurements for product validation (Fiducial Reference Measurements, FRM). Research and development continues to tackle problems such as instrument calibration, algorithm development, diurnal variability, derivation of high-quality skin and depth temperatures, and areas of specific interest such as the high latitudes and coastal areas. In this white paper, we review progress versus the challenges we set out 10 years ago in a previous paper, highlight remaining and new research and development challenges for the next 10 years (such as the need for sustained continuity of passive microwave SST using a 6.9 GHz channel), and conclude with needs to achieve an integrated global high-resolution SST observing system, with focus on satellite observations exploited in conjunction with in situ SSTs. The paper directly relates to the theme of Data Information Systems and also contributes to Ocean Observing Governance and Ocean Technology and Networks within the OceanObs2019 objectives. Applications of SST contribute to all the seven societal benefits, covering Discovery; Ecosystem Health & Biodiversity; Climate Variability & Change; Water, Food, & Energy Security; Pollution & Human Health; Hazards and Maritime Safety; and the Blue Economy

    Use of observing system simulation experiments in the United States

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    Author Posting. © American Meteorological Society, 2020. This article is posted here by permission of American Meteorological Society for personal use, not for redistribution. The definitive version was published in Bulletin of the American Meteorological Society 101(8), (2020): E1427-E1438, https://doi.org/10.1175/BAMS-D-19-0155.1.The NOAA Science Advisory Board appointed a task force to prepare a white paper on the use of observing system simulation experiments (OSSEs). Considering the importance and timeliness of this topic and based on this white paper, here we briefly review the use of OSSEs in the United States, discuss their values and limitations, and develop five recommendations for moving forward: national coordination of relevant research efforts, acceleration of OSSE development for Earth system models, consideration of the potential impact on OSSEs of deficiencies in the current data assimilation and prediction system, innovative and new applications of OSSEs, and extension of OSSEs to societal impacts. OSSEs can be complemented by calculations of forecast sensitivity to observations, which simultaneously evaluate the impact of different observation types in a forecast model system

    Challenges of a Sustained Climate Observing System

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    Observations of planet Earth and especially all climate system components and forcings are increasingly needed for planning and informed decision making related to climate services in the broadest sense. Although significant progress has been made, much more remains to be done before a fully functional and dependable climate observing system exists. Observations are needed on spatial scales from local to global, and all time scales, especially to understand and document changes in extreme events. Climate change caused by human activities adds a new dimension and a vital imperative: to acquire climate observations of sufficient quality and coverage, and analyze them into products for multiple purposes to inform decisions for mitigation, adaptation, assessing vulnerability and impacts, possible geoengineering, and predicting climate variability and change and their consequences. A major challenge is to adequately deal with the continually changing observing system, especially from satellites and other remote sensing platforms such as in the ocean, in order to provide a continuous climate record. Even with new computational tools, challenges remain to provide adequate analysis, processing, meta-data, archival, access, and management of the resulting data and the data products. As volumes of data continue to grow, so do the challenges of distilling information to allow us to understand what is happening and why, and what the implications are for the future. The case is compelling that prompt coordinated international actions are essential to provide for information-based actions and decisions related to climate variability and change

    PICES Press, Vol. 5, No. 2, July 1997

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    WG 10 Fukuoka Workshop Pacific salmon:climate-linked long-term stock fluctuations The state of the eastern North Pacific in the second half of 1996 The state of the western North Pacific in the second half of 1996 The status of the Bering Sea in the second half of 1996 Yutaka Nagata Eulogy A brief look at mechanisms for support of oceanographic research in the United States Research interests and the funding system for the new Ministry of Maritime Affairs and Fisheries of the Republic of Korea PICES and electronic communication Japan Meteorological Agency: oceanographic activitie

    Designing the climate observing system of the future

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    © The Author(s), 2018. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Earth's Future 6 (2018): 80–102, doi:10.1002/2017EF000627.Climate observations are needed to address a large range of important societal issues including sea level rise, droughts, floods, extreme heat events, food security, and freshwater availability in the coming decades. Past, targeted investments in specific climate questions have resulted in tremendous improvements in issues important to human health, security, and infrastructure. However, the current climate observing system was not planned in a comprehensive, focused manner required to adequately address the full range of climate needs. A potential approach to planning the observing system of the future is presented in this article. First, this article proposes that priority be given to the most critical needs as identified within the World Climate Research Program as Grand Challenges. These currently include seven important topics: melting ice and global consequences; clouds, circulation and climate sensitivity; carbon feedbacks in the climate system; understanding and predicting weather and climate extremes; water for the food baskets of the world; regional sea-level change and coastal impacts; and near-term climate prediction. For each Grand Challenge, observations are needed for long-term monitoring, process studies and forecasting capabilities. Second, objective evaluations of proposed observing systems, including satellites, ground-based and in situ observations as well as potentially new, unidentified observational approaches, can quantify the ability to address these climate priorities. And third, investments in effective climate observations will be economically important as they will offer a magnified return on investment that justifies a far greater development of observations to serve society's needs

    TERSSE: Definition of the Total Earth Resources System for the Shuttle Era. Volume 7: User Models: A System Assessment

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    User models defined as any explicit process or procedure used to transform information extracted from remotely sensed data into a form useful as a resource management information input are discussed. The role of the user models as information, technological, and operations interfaces between the TERSSE and the resource managers is emphasized. It is recommended that guidelines and management strategies be developed for a systems approach to user model development

    Advanced study of coastal zone oceanographic requirements for ERTS E and F

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    Earth Resources Technology Satellites E and F orbits and remote sensor instruments for coastal oceanographic data collectio
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