Generation of analysis and consistent error fields using the Data Interpolating Variational Analysis (DIVA)

Ocean Modelling

Volumn 52-53, Issue , 2012, Pages 90-101

  Troupin, C ^a   Barth, A ^a,b   Sirjacobs, D ^a   Ouberdous, M ^a   Brankart, J M ^c   Brasseur, P ^c   Rixen, M ^d   Alvera Azcarate A ^a   Belounis, M ^a   Capet, A ^a   Lenartz, F ^a   Toussaint, M E ^a   Beckers, J M ^a,b  

^a UNIVERSITY OF LIÈGE   (Belgium)

^b FRS FNRS ^*  (Belgium)

^c UNIV GRENOBLE ALPES   (France)

^d NATO UNDERSEA RESEARCH CENTRE   (Italy)

Author keywords

Inverse method; Mediterranean sea; Optimal interpolation; Spatial interpolation; Variational analysis

Indexed keywords

INVERSE METHODS; MEDITERRANEAN SEA; OPTIMAL INTERPOLATION; SPATIAL INTERPOLATION; VARIATIONAL ANALYSIS;

COASTAL ZONES; COST FUNCTIONS; INTERPOLATION; INVERSE PROBLEMS; OPTIMIZATION; SALINITY MEASUREMENT;

FINITE ELEMENT METHOD;

COASTAL ZONE; COVARIANCE ANALYSIS; ERROR ANALYSIS; FINITE ELEMENT METHOD; INTERPOLATION; INVERSE ANALYSIS; OPTIMIZATION; SMOOTHING; SPATIAL ANALYSIS; VARIANCE ANALYSIS;

MEDITERRANEAN SEA;

EID: 84862270968     PISSN: 14635003     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.ocemod.2012.05.002     Document Type: Article

References (48)

1. Handbook of Mathematical Functions with Formulas, Graphs, and Mathematical Tables 1964, Dover, New York. M. Abramowitz, I.A. Stegun (Eds.).
2. Barnes S.L. A technique for maximizing details in numerical weather map analysis. J. Appl. Meteorol. 1964, 3:396-409. http://dx.doi.org/10.1175/1520-0450(1964)003<0396:ATFMDI>2.0.CO;2.
3. Barth A., Alvera-Azcárate A., Troupin C., Ouberdous M., Beckers J.M. A web interface for griding arbitrarily distributed in situ data based on data-interpolating variational analysis (DIVA). Adv. Geophys. 2010, 28:29-37. http://dx.doi.org/10.5194/adgeo-28-29-2010.
4. Bennett A. Inverse methods in physical oceanography. Cambridge Monogr. Mech. Appl. Math. 1992, ISBN 0-521-38568-7.
5. Berx B., Hughes S. Climatology of surface and near-bed temperature and salinity on the north-west European continental shelf for 1971-2000. Cont. Shelf Res. 2009, 29:2286-2292. http://dx.doi.org/10.1016/j.csr.2009.09.006.
6. Boyer, T.P., Antonov, J.I., Baranova, O.K., Garcia, H.E., Johnson, D.R., Locarnini, R.A., Mishonov, A.V., O'Brien, T.D., Seidov, D., Smolyar, I.V., Zweng, M.M., 2009. World Ocean Database 2009, Chapter 1: Introduction. Technical Report, National Oceanographic Data Center, Ocean Climate Laboratory, Washington, D.C. pp. 216.
7. Brankart J.M., Brasseur P. Optimal analysis of in situ data in the Western Mediterranean using statistics and cross-validation. J. Atmos. Ocean. Tech. 1996, 13:477-491. http://dx.doi.org/10.1175/1520-0426(1996)013<0477:OAOISD>2.0.CO;2.
8. Brankart J.M., Brasseur P. The general circulation in the Mediterranean Sea: a climatological approach. J. Mar. Syst. 1998, 18:41-70. http://dx.doi.org/10.1016/S0924-7963(98)00005-0.
9. Brankart J.M., Ubelmann C., Testut C.E., Cosme E., Brasseur P., Verron J. Efficient parameterization of the observation error covariance matrix for square root or ensemble Kalman filters: application to ocean altimetry. Mon. Weather Rev. 2009, 137:1908-1927. http://dx.doi.org/10.1175/2008MWR2693.1.
10. Brasseur, P., 1994. Reconstruction de champs d'observations océanographiques par le Modéle variationnel inverse: Méthodologie et Applications, Ph.D. Thesis, University of Liége.
11. Brasseur P., Beckers J.M., Brankart J.M., Schoenauen R. Seasonal temperature and salinity fields in the Mediterranean Sea: climatological analyses of a historical data set. Deep-Sea Res. I 1996, 43:159-192. http://dx.doi.org/10.1016/0967-0637(96)00012-X.
12. Brasseur P., Haus J. Application of a 3-D variational inverse model to the analysis of ecohydrodynamic data in the Northern Bering and Southern Chukchi Seas. J. Mar. Syst. 1991, 1:383-401. http://dx.doi.org/10.1016/0924-7963(91)90006-G.
13. Brasseur P.P. A variational inverse method for the reconstruction of general circulation fields in the northern Bering Sea. J. Geophys. Res. 1991, 96:4891-4907. http://dx.doi.org/10.1029/90JC02387.
14. Bretherton F., Davis R., Fandry C. A technique for objective analysis and design of oceanic experiments applied to mode-73. Deep-Sea Res. 1976, 23:559-582. http://dx.doi.org/10.1016/0011-7471(76)90001-2.
15. Chilés J.P., Delfiner P. Geostatistics: Modeling Spatial Uncertainty 1999, Wiley-Interscience, ISBN 0-471-08315-1. first ed.
16. Cleveland W.S., Devlin S.J. Locally weighted regression: an approach to regression analysis by local fitting. J. Am. Stat. Assoc. 1988, 83:596-610. http://dx.doi.org/10.2307/2289282.
17. Craven P., Wahba G. Smoothing noisy data with spline functions. Numer. Math. 1979, 31:377-403. http://dx.doi.org/10.1007/BF01404567.
18. Delhomme J. Kriging in the hydrosciences. Adv. Water Resour. 1978, 1:251-266. http://dx.doi.org/10.1016/0309-1708(78)90039-8.
19. Franke R. Thin plate splines with tension. Comput. Aided Geom. D. 1985, 2:87-95. http://dx.doi.org/10.1016/0167-8396(85)90011-1.
20. Gandin, L.S., 1965. Objective analysis of meteorological fields, Israel Program for Scientific Translations, Jerusalem.
21. Gascard J., Richez C. Water masses and circulation in the Western Alboran sea and in the straits of Gibraltar. Prog. Oceanogr. 1985, 15:157-216. http://dx.doi.org/10.1016/0079-6611(85)90031-X.
22. Golub G.H., Heath M., Wahba G. Generalized cross-validation as a method for choosing a good ridge parameter. Technometrics 1979, 21:215-223. http://www.jstor.org/stable/1268518.
23. Gomis D., Ruiz S., Pedder M. Diagnostic analysis of the 3D ageostrophic circulation from a multivariate spatial interpolation of CTD and ADCP data. Deep-Sea Res. 2001, 48:269-295. http://dx.doi.org/10.1016/S0967-0637(00)00060-1.
24. Hartman L., Hössjer O. Fast kriging of large data sets with Gaussian Markov random fields. Comput. Stat. Data Anal. 2008, 52:2331-2349. http://dx.doi.org/10.1016/j.csda.2007.09.018.
25. *. J. Clim. 2000, 13:2987-3002. http://dx.doi.org/10.1175/1520-0442(2000)013<2987:RSOIOH>2.0.CO;2.
26. Legler D.M., Navon I.M., O'Brien J.J. Objective analysis of pseudostress over the indian ocean using a direct-minimization approach. Mon. Weather Rev. 1989, 117:709-720. http://dx.doi.org/10.1175/1520-0493(1989)117<0709:OAOPOT>2.0.CO;2.
27. Locarnini, R.A., Mishonov, A.V., Antonov, J.I., Boyer, T.P., Garcia, H.E., 2006. World Ocean Atlas 2005, Volume 1: Temperature, Technical Report, US Government Printing Office, Washington, DC, p. 182.
28. Locarnini, R.A., Mishonov, A.V., Antonov, J.I., Boyer, T.P., Garcia, H.E., Baranova, O.K., Zweng, M.M., Johnson, D.R., 2010. World Ocean Atlas 2009. Volume 1: Temperature. In: S. Levitus, (Ed.), NOAA Atlas NESDIS 68, US Government Printing Office, Washington, DC, p. 184.
29. Logan, D.L., 2012. A first course in the Finite element method. Global Engineering. Fifth ed. ISBN 978-0-495-66825-1.
30. McIntosh P.C. Oceanographic data interpolation: objective analysis and splines. J. Geophys. Res. 1990, 95:13529-13541. http://dx.doi.org/10.1029/JC095iC08p13529.
31. Millot C. Circulation in the Western Mediterranean sea. J. Mar. Syst. 1999, 20:423-442. http://dx.doi.org/10.1016/S0924-7963(98)00078-5.
32. Ooyama K.V. Scale-controlled objective analysis. Mon. Weather Rev. 1987, 115:2479-2506. http://dx.doi.org/10.1175/1520-0493(1987)115<2479:SCOA>2.0.CO;2.
33. Ridgway K.R., Dunn J.R., Wilkin J.L. Ocean interpolation by four-dimensional weighted least squares - application to the waters around Australasia. J. Atmos. Ocean. Tech. 2002, 19:1357-1375. http://dx.doi.org/10.1175/1520-0426(2002)019<1357:OIBFDW>2.0.CO;2.
34. Rixen M., Beckers J.M., Brankart J.M., Brasseur P. A numerically efficient data analysis method with error map generation. Ocean Model. 2000, 2:45-60. http://dx.doi.org/10.1016/S1463-5003(00)00009-3.
35. Rixen, M., Beckers, J.M., Levitus, S., Antonov, J., Boyer, T., Maillard, C., Fichaut, M., Balopoulos, E., Iona, S., Dooley, H., Garcia, M.J., Manca, B., Giorgetti, A., Manzella, G., Mikhailov, N., Pinardi, N., Zavatarelli, M., the Medar Consortium, 2005a. The Western Mediterranean Deep Water: a proxy for global climate change. Geophys. Res. Lett. 32, L12608. doi:10.1029/2005GL022702.
36. Rixen, M., Beckers, J.M., Maillard, C., the MEDAR Group, 2005b. A hydrographic and bio-chemical climatology of the Mediterranean and the Black Sea: a technical note on the use of coastal data. B. Geofis. Teor. Appl. 46, 319-327.
37. Schweikert D.G. An interpolation curve using a spline in tension. J. Math. Phys. 1966, 45:312-317.
38. Shen S., Smith T., Ropelewski C., Livezey R. An optimal regional averaging method with error estimates and a test using tropical pacific SST data. J. Clim. 1998, 11:2340-2350. http://dx.doi.org/10.1175/1520-0442(1998)011<2340:AORAMW>2.0.CO;2.
39. Steele M., Morley R., Ermold W. PHC: A global ocean hydrography with a high-quality Arctic ocean. J. Clim. 2001, 14:2079-2087. http://dx.doi.org/10.1175/1520-0442(2001)014<2079:PAGOHW>2.0.CO;2.
40. von Storch H., Zwiers F. Statistical Analysis in Climate Research 1999, Cambdridge University Press, Cambridge.
41. Tandeo P., Ailliot P., Autret E. Linear Gaussian state-space model with irregular sampling: application to sea surface temperature. Stoch. Env. Res. Risk. A. 2011, 25:793-804. http://dx.doi.org/10.1007/s00477-010-0442-8.
42. Teague W.J., Carron M.J., Hogan P.J. A comparison between the generalized digital environmental model and Levitus climatologies. J. Geophys. Res. 1990, 95:7167-7183. http://dx.doi.org/10.1029/JC095iC05p07167.
43. Troupin, C., Beckers, J.M., Ouberdous, M., Sirjacobs, D., 2010a. Diva User's Guide. GeoHydrodynamics and Environment Research. http://modb.oce.ulg.ac.be/projects/1/diva.
44. Troupin C., Machi{dotless}́n F., Ouberdous M., Sirjacobs D., Barth A., Beckers J.M. High-resolution climatology of the north-east atlantic using data-interpolating variational analysis (Diva). J. Geophys. Res. 2010, 115:C08005. http://dx.doi.org/10.1029/2009JC005512.
45. Tyberghein L., Verbruggen H., Klaas P., Troupin C., Mineur F., De Clerck O. ORACLE: a global environmental dataset for marine species distribution modeling. Global Ecol. Biogeogr. 2012, 21:272-281. http://dx.doi.org/10.1111/j.1466-8238.2011.00656.x.
46. Wahba G. Smoothing noisy data with spline functions. Numer. Math. 1975, 24:383-393. http://dx.doi.org/10.1007/BF01437407.
47. Wahba G., Wendelberger J. Some new mathematical methods for variational objective analysis using splines and cross validation. Mon. Weather Rev. 1980, 108:1122-1143. http://dx.doi.org/10.1175/1520-0493(1980)108<1122:SNMMFV>2.0.CO;2.
48. Zhang H., Wang Y. Kriging and cross-validation for massive spatial data. Environmetrics 2010, 21:290-304. http://dx.doi.org/10.1002/env.1023.