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Controlling Atmospheric Forcing Parameters of Global Ocean Models: Sequential Assimilation of Sea Surface Mercator-ocean Reanalysis Data : Volume 5, Issue 4 (16/10/2009)

By Skandrani, C.

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Book Id: WPLBN0004020396
Format Type: PDF Article :
File Size: Pages 17
Reproduction Date: 2015

Title: Controlling Atmospheric Forcing Parameters of Global Ocean Models: Sequential Assimilation of Sea Surface Mercator-ocean Reanalysis Data : Volume 5, Issue 4 (16/10/2009)  
Author: Skandrani, C.
Volume: Vol. 5, Issue 4
Language: English
Subject: Science, Ocean, Science
Collections: Periodicals: Journal and Magazine Collection, Copernicus GmbH
Historic
Publication Date:
2009
Publisher: Copernicus Gmbh, Göttingen, Germany
Member Page: Copernicus Publications

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Brankart, J., Ferry, N., Verron, J., Brasseur, P., Skandrani, C., & Barnier, B. (2009). Controlling Atmospheric Forcing Parameters of Global Ocean Models: Sequential Assimilation of Sea Surface Mercator-ocean Reanalysis Data : Volume 5, Issue 4 (16/10/2009). Retrieved from http://worldlibrary.net/


Description
Description: Laboratoire des Ecoulements Géophysiques et Industriels (LEGI/CNRS), Grenoble, France. In the context of stand alone ocean models, the atmospheric forcing is generally computed using atmospheric parameters that are derived from atmospheric reanalysis data and/or satellite products. With such a forcing, the sea surface temperature that is simulated by the ocean model is usually significantly less accurate than the synoptic maps that can be obtained from the satellite observations. This not only penalizes the realism of the ocean long-term simulations, but also the accuracy of the reanalyses or the usefulness of the short-term operational forecasts (which are key GODAE and MERSEA objectives). In order to improve the situation, partly resulting from inaccuracies in the atmospheric forcing parameters, the purpose of this paper is to investigate a way of further adjusting the state of the atmosphere (within appropriate error bars), so that an explicit ocean model can produce a sea surface temperature that better fits the available observations. This is done by performing idealized assimilation experiments in which Mercator-Ocean reanalysis data are considered as a reference simulation describing the true state of the ocean. Synthetic observation datasets for sea surface temperature and salinity are extracted from the reanalysis to be assimilated in a low resolution global ocean model. The results of these experiments show that it is possible to compute piecewise constant parameter corrections, with predefined amplitude limitations, so that long-term free model simulations become much closer to the reanalysis data, with misfit variance typically divided by a factor 3. These results are obtained by applying a Monte Carlo method to simulate the joint parameter/state prior probability distribution. A truncated Gaussian assumption is used to avoid the most extreme and non-physical parameter corrections. The general lesson of our experiments is indeed that a careful specification of the prior information on the parameters and on their associated uncertainties is a key element in the computation of realistic parameter estimates, especially if the system is affected by other potential sources of model errors.

Summary
Controlling atmospheric forcing parameters of global ocean models: sequential assimilation of sea surface Mercator-Ocean reanalysis data

Excerpt
Balmaseda, M., Alves, J., Arribas, A., Awaji, T. D. B., Ferry, N., Fujii, Y., Lee, T., Rienecker, M. T. R., and Stammer, D.: Ocean Initialisation for Seasonal Forecasts, Proceeding of final GODAE Symposiumi, Nice, France, 373–394, 2008.; Béal, D., Brasseur, P., Brankart, J.-M., Ourmiéres, Y., and Verron, J.: Controllability of mixing errors in a coupled physical biogeochemical model of the North Atlantic: a nonlinear study using anamorphosis, Ocean Sci. Discuss., 6, 1289–1332, 2009.; Berliand, M. and Berliand, T.: Determining the net long-wave radiation of the earth with consideration of the effect of cloudiness, Isv. Akad. Nauk. SSSR Ser. Geophys, 1952.; Blanke, B. and Delecluse, P.: Variability of the {T}ropical {A}tlantic {O}cean simulated by a general circulation model with two different mixed-layer physics, J. Phys. Oceanogr., 23, 1363–1388, 1993.; Brankart, J.-M., Testut, C.-E., Brasseur, P., and Verron, J.: Implementation of a multivariate data assimilation scheme for isopycnic coordinate ocean models: {A}pplication to a 1993–96 hindcast of the {N}orth {A}tlantic {O}cean circulation, J. Geophys. Res., 108(19), 1–20, 2003.; Brodeau, L., Barnier, B., Penduff, T., Treguier, A., and Gulev, S.: An ERA-40 based atmospheric forcing for global ocean circulation models, Ocean Modell., in press, 2009.; Castruccio, F., Verron, J., Gourdeau, L., Brankart, J., and Brasseur, P.: Joint altimetric and in-situ data assimilation using the GRACE mean dynamic topography: a 1993-1998 hindcast experiment in the Tropical Pacific Ocean, Ocean Dynam., 58, 43–63, 2008.; Fukumori, I.: An partitioned {K}alman Filter and Smoother, Mon. Weather Rev., 130, 1370–1383, 2002.; GODAE: The Procceddings of the Global Data Assimilation Experiment ({GODAE}), Final Symposium, Nice, France, 2008.; Goosse, H., Campin, J., Deleersnijder, E., Fichefet, T., Mathieu, P., Morales Maqueda, M., and Tartinville, B.: Description of the CLIO model version 3.0., Tech. rep., Institut d'Astronomie et de Géophysique G. Lema\^ itre, {U}niversité catholique de Louvain, Belgique, 1999.; Large, W. and Pond, S.: Sensible and latent heat flux measurements over the ocean, J. Phys. Oceanogr., 12, 464–482, 1982.; Large, W. and Yeager, S.: The global climatology of an interannually varying air-sea flux data set, Clim. Dynam., 33(2), 341–364, 2008.; Lauvernet, C., Brankart, J.-M., Castruccio, F., Broquet, G., Brasseur, P., and Verron, J.: A truncated {G}aussian filter for data assimilation with inequality constraints: application to the hydrostatic stability condition in ocean models, Ocean Modell., 27, 1–17, 2009.; Madec, G., Delecluse, P., Imbard, M., and Levy, C.: \em{OPA8.1 Ocean General Circulation Model reference manual.} Notes du pôle de modélisation, Tech. rep., Institut Pierre-Simon Laplace (IPSL), 91 pp., 1998.; Menkes, C., Boulanger, J., Busalacchi, A., Vialard, J., Delecluse, P., McPhaden, M., E., H., and Grima, N.: Impact of TAO vs. ERS wind stresses onto simulations of the tropical P}acific {O}cean during the 1993–1998 period by the {OPA OGCM, in: Climate Impact of Scale Interaction for the Tropical Ocean-Atmosphere System, vol. 13 of \em Euroclivar Workshop Report\/, 1998.; Mourre, B., Ballabrera-Poy, J., Garcia-Ladona, E., and Font, J.: Surface salinity response to changes in the model parameters and forcings in a climatological simulation of the eastern {N}orth-{A}tlantic {O}cean, Ocean Modell., 23, 21–32, 2008.; Ourmières, Y., Brankart, J.-M., Berline, L., Brasseur, P., and Verron, J.: Incremental {A}nalysis {U}pdate implementation into a sequential ocean data assimilation system., J. Atmos. Ocean. Tech., 23(12), 1729–1744, 2006.; Pham, D. T., Verron, J., and Roubaud, M. C.: Singular evolutive extended Kalman filter with EOF initialization for data assimilation in oceanography, J. Mar. Syst., 16, 323–340, 1998.; Reynolds, R. W., Rayner, N. A., Smith, T. M., Stokes, D. C., and Wang, W.:

 

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