Publication Date:
2022-05-26
Description:
Author Posting. © American Meteorological Society, 2019. This article is posted here by permission of American Meteorological Society for personal use, not for redistribution. The definitive version was published in Journal of Atmospheric and Oceanic Technology 36(9), (2019): 1789-1812, doi:10.1175/JTECH-D-18-0223.1.
Description:
Temporal vertical eddy viscosity coefficient (VEVC) in an Ekman layer model is estimated using an adjoint method. Twin experiments are carried out to investigate the influences of several factors on inversion results, and the conclusions of twin experiments are 1) the adjoint method is a capable method to estimate different kinds of temporal distributions of VEVCs; 2) the gradient descent algorithm is better than CONMIN and L-BFGS for the present problem, although the posterior two algorithms perform better on convergence efficiency; 3) inversion results are sensitive to initial guesses; 4) the model is applicable to different wind conditions; 5) the inversion result with thick boundary layer depth (BLD) is slightly better than thin BLD; 6) inversion results are more sensitive to observations in upper layers than those in lower layers; 7) inversion results are still acceptable when data noise exists, indicating the method can sustain noise to a certain degree; 8) a regularization method is proved to be useful to improve the results for present problem; and 9) the present method can tolerate the existence of balance errors due to the imperfection of governing equations. The methodology is further validated in practical experiments where Ekman currents are derived from Bermuda Testbed Mooring data and assimilated. Modeled Ekman currents coincide well with observed ones, especially for upper layers. The results demonstrate that the assumptions of depth dependence and time dependence are equally important for VEVCs. The feasibility of the typical Ekman model, the imperfection of Ekman balance equations, and the deficiencies of the present method are discussed. This method provides a potential way to realize the time variations of VEVCs in ocean models.
Description:
The authors thank the seven reviewers for the constructive suggestions which have greatly improved the manuscript. Financial support is provided by the National Key Research and Development Plan of China (Grants 2017YFA0604100 and 2017YFC1404000), the National Natural Science Foundation of China (Grants 41876086 and 41806012), Scientific Research Fund of the Second Institute of Oceanography, MNR (Grant JG1819), and the Fundamental Research Funds for the Central Universities of China. Jicai thanks the support of China Scholarship Council for the visiting research in WHOI, and he also thanks the host of WHOI. BTM data are provided by Ocean Physics Laboratory, University of California, Santa Barbara (http://opl.ucsb.edu).
Description:
2020-03-10
Keywords:
Data assimilation
;
Parameterization
Repository Name:
Woods Hole Open Access Server
Type:
Article
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