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    Climatological SST and MLD Predictions from a Global Layered Ocean Model with an Embedded Mixed Layer

    Source: Journal of Atmospheric and Oceanic Technology:;2003:;volume( 020 ):;issue: 011::page 1616
    Author:
    Kara, A. Birol
    ,
    Wallcraft, Alan J.
    ,
    Hurlburt, Harley E.
    DOI: 10.1175/1520-0426(2003)020<1616:CSAMPF>2.0.CO;2
    Publisher: American Meteorological Society
    Abstract: The Naval Research Laboratory (NRL) Layered Ocean Model (NLOM) with an embedded mixed layer submodel is used to predict the climatological monthly mean sea surface temperature (SST) and surface ocean mixed layer depth (MLD) over the global ocean. The thermodynamic model simulations presented in this paper are performed using six dynamical layers plus the embedded mixed layer at 1/2° resolution in latitude and 0.703125° in longitude, globally spanning from 72°S to 65°N. These model simulations use climatological wind and thermal forcing and include no assimilation of SST or MLD data. To measure the effectiveness of the NLOM mixed layer, the annual mean and seasonal cycle of SST and MLD obtained from the model simulations are compared to those from different climatological datasets at each grid point over the global ocean. Analysis of the global error maps shows that the embedded mixed layer in NLOM gives accurate SST with atmospheric forcing even with no SST relaxation/assimilation. In this case the model gives a global root-mean-square (rms) difference of 0.37°C for the annual mean and 0.59°C over the seasonal cycle over the global ocean. The mean global correlation coefficient (R) is 0.91 for the seasonal cycle of the SST. NLOM predicts SST with an annual mean error of <0.5°C in most of the North Atlantic and North Pacific Oceans. For the MLD the model gave a global rms difference of 34 m for the annual mean and 63 m over the seasonal cycle over the global ocean in comparison to the NRL MLD climatology (NMLD). The mean global R value is 0.62 for the seasonal cycle of the MLD. Additional model?data comparisons use climatological monthly mean SST time series from 18 National Oceanic Data Center (NODC) buoys and 11 ocean weather station (OWS) hydrographic locations in the North Pacific Ocean. The median rms difference between the NLOM SSTs and SSTs at these 29 locations is 0.49°C for the seasonal cycle. Deepening and shallowing of the MLD at the all OWS locations in the northeast Pacific are captured by the model with an rms difference of <20 m and an R value of >0.85 for the seasonal cycle. Using several statistical measures and climatologies of SST and MLD we have demonstrated that NLOM with an embedded mixed layer is able to simulate with substantial skill the climatological SST and MLD when using accurate and computationally efficient surface heat flux and solar radiation attenuation parameterizations over the global ocean. Further, this was accomplished using a model with only seven layers in the vertical, including the embedded mixed layer. Success of climatological predictions from the NLOM with an embedded mixed layer is a prerequisite for simulations using interannual atmospheric forcing with high temporal resolution. NLOM gives accurate upper-ocean quantities with atmospheric forcing even with no SST relaxation or assimilation, a strong indication that the model is a good candidate for assimilation of SST data. Finally, the techniques and datasets used here can be applied to evaluation of other ocean models in predicting the SST and MLD.
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      Climatological SST and MLD Predictions from a Global Layered Ocean Model with an Embedded Mixed Layer

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    http://yetl.yabesh.ir/yetl1/handle/yetl/4158334
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    contributor authorKara, A. Birol
    contributor authorWallcraft, Alan J.
    contributor authorHurlburt, Harley E.
    date accessioned2017-06-09T14:34:21Z
    date available2017-06-09T14:34:21Z
    date copyright2003/11/01
    date issued2003
    identifier issn0739-0572
    identifier otherams-2194.pdf
    identifier urihttp://onlinelibrary.yabesh.ir/handle/yetl/4158334
    description abstractThe Naval Research Laboratory (NRL) Layered Ocean Model (NLOM) with an embedded mixed layer submodel is used to predict the climatological monthly mean sea surface temperature (SST) and surface ocean mixed layer depth (MLD) over the global ocean. The thermodynamic model simulations presented in this paper are performed using six dynamical layers plus the embedded mixed layer at 1/2° resolution in latitude and 0.703125° in longitude, globally spanning from 72°S to 65°N. These model simulations use climatological wind and thermal forcing and include no assimilation of SST or MLD data. To measure the effectiveness of the NLOM mixed layer, the annual mean and seasonal cycle of SST and MLD obtained from the model simulations are compared to those from different climatological datasets at each grid point over the global ocean. Analysis of the global error maps shows that the embedded mixed layer in NLOM gives accurate SST with atmospheric forcing even with no SST relaxation/assimilation. In this case the model gives a global root-mean-square (rms) difference of 0.37°C for the annual mean and 0.59°C over the seasonal cycle over the global ocean. The mean global correlation coefficient (R) is 0.91 for the seasonal cycle of the SST. NLOM predicts SST with an annual mean error of <0.5°C in most of the North Atlantic and North Pacific Oceans. For the MLD the model gave a global rms difference of 34 m for the annual mean and 63 m over the seasonal cycle over the global ocean in comparison to the NRL MLD climatology (NMLD). The mean global R value is 0.62 for the seasonal cycle of the MLD. Additional model?data comparisons use climatological monthly mean SST time series from 18 National Oceanic Data Center (NODC) buoys and 11 ocean weather station (OWS) hydrographic locations in the North Pacific Ocean. The median rms difference between the NLOM SSTs and SSTs at these 29 locations is 0.49°C for the seasonal cycle. Deepening and shallowing of the MLD at the all OWS locations in the northeast Pacific are captured by the model with an rms difference of <20 m and an R value of >0.85 for the seasonal cycle. Using several statistical measures and climatologies of SST and MLD we have demonstrated that NLOM with an embedded mixed layer is able to simulate with substantial skill the climatological SST and MLD when using accurate and computationally efficient surface heat flux and solar radiation attenuation parameterizations over the global ocean. Further, this was accomplished using a model with only seven layers in the vertical, including the embedded mixed layer. Success of climatological predictions from the NLOM with an embedded mixed layer is a prerequisite for simulations using interannual atmospheric forcing with high temporal resolution. NLOM gives accurate upper-ocean quantities with atmospheric forcing even with no SST relaxation or assimilation, a strong indication that the model is a good candidate for assimilation of SST data. Finally, the techniques and datasets used here can be applied to evaluation of other ocean models in predicting the SST and MLD.
    publisherAmerican Meteorological Society
    titleClimatological SST and MLD Predictions from a Global Layered Ocean Model with an Embedded Mixed Layer
    typeJournal Paper
    journal volume20
    journal issue11
    journal titleJournal of Atmospheric and Oceanic Technology
    identifier doi10.1175/1520-0426(2003)020<1616:CSAMPF>2.0.CO;2
    journal fristpage1616
    journal lastpage1632
    treeJournal of Atmospheric and Oceanic Technology:;2003:;volume( 020 ):;issue: 011
    contenttypeFulltext
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    DSpace software copyright © 2002-2015  DuraSpace
    نرم افزار کتابخانه دیجیتال "دی اسپیس" فارسی شده توسط یابش برای کتابخانه های ایرانی | تماس با یابش
    yabeshDSpacePersian