Empirical wind-driven models of sea surface height and their use for reconstructing sea surface height fields from incomplete data

Alexey Kaplan (LDEO of Columbia University, United States)

Event: 2014 Ocean Surface Topography Science Team Meeting

Session: Science Results from Satellite Altimetry: Regional and basin-scale processes and sea level rise

Presentation type: Type Poster

Vector autoregressive modeling is used for the construction of empirical linear models for sea surface heights with wind forcing. Dynamical linearized model for tropical ocean (Cane and Patton, 1984) will be used for comparison. Performance of several wind stress data sets (from QuikSCAT-FSU, CCMP, and atmospheric reanalyses) as a forcing for sea surface height simulations is evaluated. Assimilation of sea surface height data from altimetry and tide gauges into linear wind-forced model is performed using reduced space optimal smoother (Kaplan et al., 1997) with the addition of smaller scale variability with locally estimated covariance (Karspeck et al., 2012) and locally-forced dynamics. Assimilated fields are compared with published reconstructions of sea surface height fields.


Cane, M. A. and R. J. Patton, 1984: A Numerical-Model for Low-Frequency Equatorial Dynamics. J. Phys, Oceanogr., 14, 1853-1863.

Kaplan, A., Y. Kushnir, M. Cane, and M. Blumenthal, 1997: Reduced space optimal analysis for historical datasets: 136 years of Atlantic sea surface temperatures, J. Geophys. Res., 102, 27835-27860.

Karspeck, A.R., A.Kaplan, and S.R.Sain, 2012: Bayesian modelling and ensemble reconstruction of mid-scale spatial variability in North Atlantic sea-surface temperatures for 1850-2008. Q.J.R. Meteorol. Soc., 138, 234-248. doi: 10.1002/qj.900. Suppl. Materials: http://rainbow.ldeo.columbia.edu/~alexeyk/KKS2011supp/

Alexey Kaplan
LDEO of Columbia University
United States