Lagrangian validation of numerical drifter trajectories using drifting buoys: Application to the Agulhas system
The skill of numerical Lagrangian drifter trajectories in three numerical models is assessed by comparing these numerically obtained paths to the trajectories of drifting buoys in the real ocean. The skill assessment is performed using the two-sample Kolmogorov–Smirnov statistical test. To demonstra...
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Published in: | Ocean modelling (Oxford) Vol. 29; no. 4; pp. 269 - 276 |
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2009
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Abstract | The skill of numerical Lagrangian drifter trajectories in three numerical models is assessed by comparing these numerically obtained paths to the trajectories of drifting buoys in the real ocean. The skill assessment is performed using the two-sample Kolmogorov–Smirnov statistical test. To demonstrate the assessment procedure, it is applied to three different models of the Agulhas region. The test can either be performed using crossing positions of one-dimensional sections in order to test model performance in specific locations, or using the total two-dimensional data set of trajectories. The test yields four quantities: a binary decision of model skill, a confidence level which can be used as a measure of goodness-of-fit of the model, a test statistic which can be used to determine the sensitivity of the confidence level, and cumulative distribution functions that aid in the qualitative analysis. The ordering of models by their confidence levels is the same as the ordering based on the qualitative analysis, which suggests that the method is suited for model validation. Only one of the three models, a 1/10° two-way nested regional ocean model, might have skill in the Agulhas region. The other two models, a 1/2° global model and a 1/8° assimilative model, might have skill only on some sections in the region. |
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AbstractList | The skill of numerical Lagrangian drifter trajectories in three numerical models is assessed by comparing these numerically obtained paths to the trajectories of drifting buoys in the real ocean. The skill assessment is performed using the two-sample Kolmogorov–Smirnov statistical test. To demonstrate the assessment procedure, it is applied to three different models of the Agulhas region. The test can either be performed using crossing positions of one-dimensional sections in order to test model performance in specific locations, or using the total two-dimensional data set of trajectories. The test yields four quantities: a binary decision of model skill, a confidence level which can be used as a measure of goodness-of-fit of the model, a test statistic which can be used to determine the sensitivity of the confidence level, and cumulative distribution functions that aid in the qualitative analysis. The ordering of models by their confidence levels is the same as the ordering based on the qualitative analysis, which suggests that the method is suited for model validation. Only one of the three models, a 1/10° two-way nested regional ocean model, might have skill in the Agulhas region. The other two models, a 1/2° global model and a 1/8° assimilative model, might have skill only on some sections in the region. The skill of numerical Lagrangian drifter trajectories in three numerical models is assessed by comparing these numerically obtained paths to the trajectories of drifting buoys in the real ocean. The skill assessment is performed using the two-sample Kolmogorov-Smirnov statistical test. To demonstrate the assessment procedure, it is applied to three different models of the Agulhas region. The test can either be performed using crossing positions of one-dimensional sections in order to test model performance in specific locations, or using the total two-dimensional data set of trajectories. The test yields four quantities: a binary decision of model skill, a confidence level which can be used as a measure of goodness-of-fit of the model, a test statistic which can be used to determine the sensitivity of the confidence level, and cumulative distribution functions that aid in the qualitative analysis. The ordering of models by their confidence levels is the same as the ordering based on the qualitative analysis, which suggests that the method is suited for model validation. Only one of the three models, a 1/10@uo two-way nested regional ocean model, might have skill in the Agulhas region. The other two models, a 1/2@uo global model and a 1/8@uo assimilative model, might have skill only on some sections in the region. The skill of numerical Lagrangian drifter trajectories in three numerical models is assessed by comparing these numerically obtained paths to the trajectories of drifting buoys in the real ocean. The skill assessment is performed using the two-sample Kolmogorov-Smirnov statistical test. To demonstrate the assessment procedure, it is applied to three different models of the Agulhas region. The test can either be performed using crossing positions of one-dimensional sections in order to test model performance in specific locations, or using the total two-dimensional data set of trajectories. The test yields four quantities: a binary decision of model skill, a confidence level which can be used as a measure of goodness-of-fit of the model, a test statistic which can be used to determine the sensitivity of the confidence level, and cumulative distribution functions that aid in the qualitative analysis. The ordering of models by their confidence levels is the same as the ordering based on the qualitative analysis, which suggests that the method is suited for model validation. Only one of the three models, a 1/10 super(o) two-way nested regional ocean model, might have skill in the Agulhas region. The other two models, a 1/2 super(o) global model and a 1/8 super(o) assimilative model, might have skill only on some sections in the region. |
Author | de Ruijter, W.P.M. van Leeuwen, P.J. Barron, C.N. van Sebille, E. Biastoch, A. |
Author_xml | – sequence: 1 givenname: E. surname: van Sebille fullname: van Sebille, E. email: E.vanSebille@uu.nl organization: Institute for Marine and Atmospheric Research Utrecht, Utrecht University, The Netherlands – sequence: 2 givenname: P.J. surname: van Leeuwen fullname: van Leeuwen, P.J. organization: Institute for Marine and Atmospheric Research Utrecht, Utrecht University, The Netherlands – sequence: 3 givenname: A. surname: Biastoch fullname: Biastoch, A. organization: Leibniz Institute of Marine Sciences, Kiel, Germany – sequence: 4 givenname: C.N. surname: Barron fullname: Barron, C.N. organization: Naval Research Laboratory, Stennis Space Center, Mississippi, USA – sequence: 5 givenname: W.P.M. surname: de Ruijter fullname: de Ruijter, W.P.M. organization: Institute for Marine and Atmospheric Research Utrecht, Utrecht University, The Netherlands |
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SubjectTerms | Drifting buoys Kolmogorov–Smirnov statistics Marine Model validation Numerical Lagrangian drifters |
Title | Lagrangian validation of numerical drifter trajectories using drifting buoys: Application to the Agulhas system |
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