1,096
Views
19
CrossRef citations to date
0
Altmetric
Thematic cl.: Towards regional climate system modeling for the Baltic Sea, North Sea, Mediterranean Sea and Arctic Ocean

Application of 3-D ensemble variational data assimilation to a Baltic Sea reanalysis 1989–2013

&
Article: 24220 | Received 28 Feb 2014, Accepted 02 Feb 2016, Published online: 11 Mar 2016

References

  • Alenius P. , Nekrasov A. , Myrberg K . Variability of the baroclinic Rossby radius in the Gulf of Finland. Cont. Shelf. Res. 2003; 23(6): 563–573.
  • Arheimer B., Dahné J., Lindström G., Strömqvist J. Water and nutrient simulations using the HYPE model for Sweden vs. the Baltic Sea basin – influence of input data quality and scale. Hydrol. Res. 2012; 43: 315–329. DOI: http://dx.doi.org/10.2166/nh.2012.010.
  • Axell L.B. Wind-driven internal waves and Langmuir circulations in a numerical ocean model of the southern Baltic Sea. J. Geophys. Res. 2002; 107(C11): 3204,. DOI: http://dx.doi.org/10.1029/2001JC000922.
  • Axell L . BSRA-15: A Baltic Sea Reanalysis 1990–2004. 2013; Norrköping, Sweden: Swedish Meteorological and Hydrological Institute. Reports Oceanography, 45.
  • Buehner M . Ensemble-derived stationary and flow-dependent background-error covariances: evaluation in a quasi-operational NWP setting. Q. J. R. Meteor. Soc. 2005; 131: 1013–1043.
  • Buehner M. , Houtekamer P. , Charette C. , Mitchell H. , He B . Intercomparison of variational data assimilation and the ensemble Kalman filter for global deterministic NWP. Part I: description and single-observation experiments. Mon. Wea. Rev. 2010a; 138: 1550–1566.
  • Buehner M. , Houtekamer P. , Charette C. , Mitchell H. , He B . Intercomparison of variational data assimilation and the ensemble Kalman filter for global deterministic NWP. Part II: one-month experiments with real observations. Mon. Wea. Rev. 2010b; 138: 1567–1586.
  • Compo G. P., Whitaker J. S., Sardeshmukh P. D., Matsui N., Allan R. J., co-authors. The twentieth century reanalysis project. Q. J. R. Meteor. Soc. 2011; 137: 1–28. DOI: http://dx.doi.org/10.1002/qj.776.
  • Counillon F. , Bertino L . Ensemble optimal interpolation: multivariate properties in the Gulf of Mexico. Tellus A. 2009; 61: 296–308.
  • Courtier P. , Andersson E. , Heckley W. , Pailleux J. , Vasiljevic D. , co-authors . The ECMWF implementation of three-dimensional variational assimilation (3DVAR). I:Formulation. Q. J. R. Meteor. Soc. 1998; 124: 1783–1807.
  • Dahlgren P., Kållberg P., Landelius T., Undén P. EURO4M Project – Report, D 2.9 Comparison of the Regional Reanalyses Products with Newly Developed and Existing State-of-the Art Systems. 2014. Technical Report. Online at: http://www.euro4m.eu/Deliverables.html.
  • Daley R . Cambridge Atmospheric and Space Sciences Series. Atmospheric Data Analysis. 1991; Cambridge University Press. Chap. 3.
  • Dee D. P. , Uppala S. M. , Simmons A.J. , Berrisford P. , Poli P. , co-authors . The ERA-Interim reanalysis: configuration and performance of the data assimilation system. Q. J. R. Meteorol. Soc. 2011; 137: 553–597.
  • Ebita A. , Kobayashi S. , Ota Y. , Moriya M. , Kumabe R. , co-authors . The Japanese 55-year Reanalysis ‘JRA-55’: an interim report. SOLA. 2011; 7: 149–152.
  • Evensen G . Sequential data assimilation with a nonlinear quasi-geostrophic model using Monte Carlo methods to forecast error statistics. J. Geophys. Res. 1994; 99: 143–162.
  • Evensen G . The ensemble Kalman filter: theoretical formulation and practical implementation. Ocean Dyn. 2003; 53: 343–367.
  • Evensen G . Data assimilation: the ensemble Kalman Filter. 2009. Springer-Verlag, Heidelberg, Germany.
  • Fisher M. , Courtier P . Estimating the covariance matrices of analysis and forecast error in variational data assimilation. ECMWF Tech. Memo .
  • Fu W. , She J. , Dobrynin M . A 20-year reanalysis experiment in the Baltic Sea using three-dimensional variational (3DVAR) method. Ocean Sci. 2012; 8: 827–844.
  • Funkquist L. , Kleine E . Report Oceanography, 37. HIROMB: An Introduction to HIROMB, an Operational Baroclinic Model for the Baltic Sea. 2007; Norrköping, Sweden: Swedish Meteorological and Hydrological Institute.
  • Gibson J. , Kållberg P. , Uppala S. , Hernandez A. , Nomura A. , co-authors . ERA Description. Re-Analysis (ERA) Project Report Series 1, ECMWF. 1997. European Centre for Medium-Range Weather Forecasts, Reading, Great Britain.
  • Gustafsson N . Discussion on ‘4D-Var or EnKF’. Tellus A. 2007; 59: 774–777.
  • Gustafsson N. , Berre L. , Hornquist S. , Huang X.-Y. , Lindskog M. , co-authors . Three-dimensional variational data assimilation for a limited area model. Part I: general formulation and the background error constraint. Tellus A. 2001; 53: 425–446.
  • Gustafsson N, Bojarova J. Four-dimensional ensemble variational (4D-En-Var) data assimilation for the HIgh Resolution Limited Area Model (HIRLAM). Nonlin. Process. Geophys. 2014; 21: 1–18. DOI: http://dx.doi.org/10.5194/npg-21-1-2014.
  • Gustafsson N., Bojarova J., Vignes O. A hybrid variational ensemble data assimilation for the HIgh Resolution Limited Area Model (HIRLAM). Nonlin. Process. Geophys. 2014; 21: 303–323. DOI: http://dx.doi.org/10.5194/npg-21-303-2014.
  • Hamill T. , Snyder C . A hybrid ensemble Kalman filter-3D variational analysis scheme. Mon. Wea. Rev. 2000; 135: 222–227.
  • Hamill T. , Snyder C. , Morss R . Analysis-error statistics of a quasigeostrophic model using three-dimensional variational assimilation. Mon. Wea. Rev. 2002; 130: 2777–2790.
  • Houtekamer P. , Mitchell H . A sequential ensemble Kalman filter for atmospheric data assimilation. Mon. Wea. Rev. 2001; 129: 123–137.
  • Kalnay E. , Kanamitsu M. , Kistler R. , Collins W. , Deaven D. , co-authors . The NCEP/NCAR 40-year reanalysis project. Bull. Amer. Meteor. Soc. 1996; 77: 437–471.
  • Leppäranta M. , Myrberg K . Physical Oceanography of the Baltic Sea. 2009. Springer-Verlag, Heidelberg, Germany.
  • Lisaeter K. A. , Rosanov J. , Evensen G . Assimilation of ice concentration in a coupled ice–ocean model, using the Ensemble Kalman filter. Ocean Dyn. 2003; 53: 368–388.
  • Liu C. , Xiao Q . An ensemble-based four-dimensional variational data assimilation scheme. Part III: Antarctic applications with advanced research WRF using real data. Mon. Wea. Rev. 2013; 141: 2721–2739.
  • Liu C. , Xiao Q. , Wang B . An ensemble-based four-dimensional variational data assimilation scheme. Part I: technical formulation and preliminary test. Mon. Wea. Rev. 2008; 136: 3363–3373.
  • Liu C. , Xiao Q. , Wang B . An ensemble-based four-dimensional variational data assimilation scheme. Part II: observing system simulation experiments with Advanced Research WRF (ARW). Mon. Wea. Rev. 2009; 137: 1687–1702.
  • Liu Y. , Meier M. , Axell L . Reanalyzing temperature and salinity on decadal time scales using the ensemble optimal interpolation data assimilation method and a 3D ocean circulation model of the Baltic Sea. J. Geophys. Res. 2013; 118: 5536–5554.
  • Lorenc A . The potential of the ensemble Kalman filter for NWP – a comparison with 4D-Var. Q. J. R. Meteorol. Soc. 2003; 129: 3183–3203.
  • Luhamaa A. , Kimmel K. , Männik A. , R[otilde][otilde]m R . High resolution re-analysis for the Baltic Sea region during 1965–2005 period. Clim. Dyn. 2011; 36: 727–738.
  • Madec G. , The NEMO Team . NEMO Ocean Engine. Note du Pole de modelisation. 2008. 27. Institut Pierre-Simon Laplace (IPSL), France. ISSN No. 1288-1619.
  • Nerger L. , Hiller W. , Schrter J . A comparison of error subspace Kalman filters. Tellus A. 2005; 57: 715–735.
  • Oke P., Allen J., Miller R., Egbert G., Kosro P. Assimilation of surface velocity data into a primitive equation coastal ocean model. J. Geophys. Res. 2002; 107: 3122. DOI: http://dx.doi.org/10.1029/2000JC000511.
  • Oke P. , Schiller A. , Griffin D. , Brassington G . Ensemble data assimilation for an eddy-resolving ocean model of the Australian region. Q. J. R. Meteorol. Soc. 2005; 131: 3301–3311.
  • Omstedt A. , Axell L.-B . Modeling the seasonal, interannual, and long-term variations of salinity and temperature in the Baltic proper. Tellus A. 1998; 50: 637–652.
  • Onogi K. , Tsutsui J. , Koide H. , Sakamoto M. , Kobayashi S. , co-authors . The JRA-25 Reanalysis. J. Meteor. Soc. Japan. 2007; 85: 369–432.
  • Osinski R. , Rak D. , Walczowski W. , Piechura J . Baroclinic Rossby radius of deformation in the southern Baltic Sea. Oceanologia. 2010; 52(3): 417–429.
  • Parrish D. , Derber J . The National Meteorological Center's spectral statistical interpolation analysis system. Mon. Wea. Rev. 1992; 120: 1747–1763.
  • Pham D. , Verron J. , Roubaud M . A singular evolutive extended Kalman filter for data assimilation. J. Mar. Syst. 1998; 16: 323–340.
  • Umlauf L. , Burchard H. , Hutter K . Extending the k - w turbulence model towards oceanic applications. Oc. Mod. 2003; 5: 195–218.
  • Uppala S. M., Kållberg P. W., Simmons A.J., Andrae U., Da Costa Bechtold V., co-authors. The ERA-40 re-analysis. Q. J. R. Meteorol. Soc. 2005; 131: 2961–3012. DOI: http://dx.doi.org/10.1256/qj.04.176.
  • Wang K. , Leppäranta M. , Gästgivars M. , Vainio J. , Wang C . The drift and spreading of the Runner 4 oil spill and the ice conditions in the Gulf of Finland, winter 2006. Estonian J. Earth Sci. 2008; 57(3): 181–191.
  • Wang X. , Bishop C . A comparison of breeding and ensemble transform Kalman filter ensemble forecast schemes. J. Atmos. Sci. 2003; 60: 1140–1158.
  • Wang X. , Lei T . GSI-based four-dimensional ensemble-variational (4DEnsVar) data assimilation: formulation and single-resolution experiments with real data for NCEP global forecast system. Mon. Wea. Rev. 2014; 142: 3303–3325.
  • Wilcox D . Turbulence Modeling for CFD. 1998; Inc: DCW Industries. 2nd ed.
  • Wilhelmsson T . Licentiate Thesis. Parallellization of the HIROMB Ocean Model. 2002. Royal Institute of Technology, Department of Numerical and Computer Science, Stockholm, Sweden.
  • Xie J. , Zhu J . Ensemble optimal interpolation schemes for assimilating Argo profiles into a hybrid coordinate ocean model. Ocean Model. 2010; 33: 283–298.
  • Zhang H. , Xue J. , Zhuang S. , Zhu G. , Zhu Z . GRAPeS 3D-Var data assimilation system ideal experiments. Acta Meteor. Sin. 2004; 62: 31–41.