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  • 1
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    PANGAEA
    In:  Supplement to: Jia, Yinglai; Chang, Ping; Szunyogh, Istvan; Saravanan, Ramalingam; Bacmeister, Julio T (2019): A Modeling Strategy for the Investigation of the Effect of Mesoscale SST Variability on Atmospheric Dynamics. Geophysical Research Letters, 46(7), 3982-3989, https://doi.org/10.1029/2019GL081960
    Publication Date: 2023-01-13
    Description: An efficient modeling strategy is proposed for the investigation of the effect of SST mesoscale variability on atmospheric dynamics. Two ensembles of numerical simulations are generated with a high-resolution atmospheric global circulation model coupled to a slab ocean model. This dataset contains data from the control and filtered ensembles which ran using the CESM at about 25km horizontal resolution over the globe. CAM5_SOM simulations are used to study the effect of mesoscale SST variability on atmospheric circulations. This dataset contains 25km model simulations from control and filtered ensemble run.
    Keywords: File content; File format; File name; File size; Uniform resource locator/link to file
    Type: Dataset
    Format: text/tab-separated-values, 20 data points
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  • 2
    Publication Date: 2023-06-27
    Keywords: AGE; PC; Piston corer; Sea surface temperature, annual mean; Sub-surface temperature; V12; V12-107; Vema
    Type: Dataset
    Format: text/tab-separated-values, 151 data points
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  • 3
    Publication Date: 2013-09-19
    Description: Cloud computing has become a popular topic for exploration in both academic and industrial research in recent years. In this paper, network behavior is analyzed to assess and compare the costs and risks associated with traditional local servers versus those associated with cloud computing to determine the appropriate deployment strategy. An analytic framework of a deployment strategy that involves two mathematical models and the analytical hierarchy process is proposed to analyze the costs and service level agreements of services involving using traditional local servers and platform as service platforms in the cloud. Two websites are used as test sites to analyze the costs and risks of deploying services in Google App Engine (GAE) (1) the website of Information and Finance of Management (IFM) at the National Chiao Tung University (NCTU) and (2) the NCTU website. If the examined websites were deployed in GAE, NCTU would save over 83.34% of the costs associated with using a traditional local server with low risk. Therefore, both the IFM and NCTU websites can be served appropriately in the cloud. Based on this strategy, a suggestion is proposed for managers and professionals.
    Print ISSN: 1024-123X
    Electronic ISSN: 1563-5147
    Topics: Mathematics , Technology
    Published by Hindawi
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