Oceanographic feature models
The oceanographic feature model is a numerical ocean modeling concept initially brought up by the oceanography research group at Harvard University. Oceanographic feature models are defined as mathematical representations of typical synoptic features of circulation in an oceanic region. Examples of features in the world ocean include western and eastern boundary currents, eddies, jets and fronts, gyres, recirculation regions, upwelling regions, retroflections, bifurcations, coastal currents, shelf flows, shelf-slope fronts, anomalous pools, freshwater plumes, sub-mesoscale mushroom vortices or dipoles, etc. Parameterized mathematical representation of the three-dimensional descriptions of the mass (temperature, salinity, density) and momentum (zonal, meredional and vertical velocity) within a feature is dubbed a "feature model." The typical extent of the features in the horizontal and vertical is obtained from previous observations.
History and development
The idea and development of oceanic feature models originated from the Harvard Oceanography Group (Robinson et al., 1988; Spall and Robinson, 1990) for Gulf Stream meander and ring (GSMR) studies. The application of feature models for synoptic ocean prediction in the GSMR region was first described by Robinson et al. (1989) and then by Glenn and Robinson (1995). Subsequently, these feature models were used for initialization of primitive equation models for the GSMR region in a multiscale circulation model synthesis framework with a Validation-Calibration-Verification methodology developed by Gangopadhyay et al. (1997), Robinson and Gangopadhyay (1997), and Gangopadhyay and Robinson (1997).
One approach to regional modeling in the world oceans is to use such knowledge-based feature models for initialization of a numerical model for use in prediction and for process studies. This approach is distinctly different from the basin-scale approach that requires models to develop the inertia fields in a so-called "spin-up" period, which could require multiple (3-10) years of numerical integration prior to resolving synoptic mesoscale fields. This feature-oriented regional modeling system (FORMS) approach has been used for regional simulations and operational forecasting since the late 1990s. It originated and was very successful in weather prediction when available data were insufficient for a complete initialization of features (e.g., Bennett, 1992). In the ocean, specific examples include the studies by Robinson et al. (1989), Hurlburt et al. (1990), Fox et al. (1992), Glenn and Robinson (1995), Cummings et al. (1997), Gangopadhyay et al. (1997), Lermusiaux (1999), Robinson and Glenn (1999), and Robinson et al. (2001).
Gangopadhyay and Robinson (2002) have generalized the feature-oriented approach for strategic application to any regional ocean. Typical feature model expressions to guide any further development are provided by Gangopadhyay and Robinson (2002). A feature-oriented regional modeling system (FORMS) for the Gulf of Maine and Georges Bank region has been developed for real-time applications for medium-range (7-10 days), process studies and mesoscale to sub-mesoscale forecasting (Gangopadhyay et al., 2003; Warn-Varnas et al., 2005; Brown et al., 2007a,b). This system has been applied in many real-time simulations, including the IOOS efforts of the Mid-Atlantic Regional Association Coastal Ocean Observation System (MARACOOS) (Schofield et al., 2010; Schmidt and Gangopadhyay, 2012; Gangopadhyay et al., 2012), for the Brazil Current system (Calado et al., 2006, 2008, 2010), for the California Current system (Kim et al., 2007; Gangopadhyay et al., 2011), and for the Trinidad-North Brazil Current region (Schmidt et al., 2011).
The development of feature models allows for targeted process studies such as of coastal plumes (Gangopadhyay et al., 2005), upwelling events in Arabian Sea (Shaji and Gangopadhyay, 2007), phytoplankton growth in the wake of an island (Hasegawa et al., 2008), meander-eddy-upwelling interactions (Calado et al., 2010), and the relative roles of topography and shear for generating eddies in the Brazil Current formation region (Soutelino et al., 2013).
Methodology
The feature models are developed from synoptic data for specific features of circulation in a particular region. A multiscale Objective Analysis technique (Carter and Robinson, 1987; Lozano et al., 1995) is then used to meld the synoptic feature models with large-scale background climatology. The resulting three-dimensional field is then used to initialize any numerical model for simulations for analysis of processes or for operational predictions over days to weeks. Ocean prediction is an initial value problem and the feature-oriented approach provides a capability of deriving a best-possible guess of the initial three-dimensional state of the ocean at any given time by synthesizing different kinds of satellite and in-situ data (as available), the regional climatology, and prior knowledge of the dominant features of regional circulation.
The FORMS methodology is generally implemented in four distinct steps:
- identify circulation and water mass features by analyzing regional processes and dynamics;
- develop feature models for prevalent features from synoptic data sets from previous or current observations;
- select and/or develop a regional climatology which could serve as a background flow field; and
- carry out a multiscale objective analysis using climatology and feature models, to provide for a three-dimensional ocean estimate at a particular time of interest.
References
- Bennett, A. F., 1992. Inverse Methods in Physical Oceanography. Cambridge University Press, Cambridge, 346 pp.
- Brown, W. S., A. Gangopadhyay, F. L. Bub, Z. Yu, G. Strout, and A. R. Robinson, 2007. An operational circulation modeling system for the Gulf of Maine/Georges Bank region, part 1: The basic elements. IEEE J. Oceanic Eng. 32(4), 807-822.
- Brown, W. S., A. Gangopadhyay, and Z. Yu, 2007. An operational circulation modeling system for the Gulf of Maine/Georges Bank region, part 2: Applications. IEEE J. Oceanic Eng. 32(4), 823-838.
- Calado, L., A. Gangopadhyay, and I. C. A. da Silveira, 2006. A parametric model for the Brazil Current meanders and eddies off southeastern Brazil. Geophys. Res. Lett. 33, L12602, doi:10.1029/2006GL026092.
- Calado, L, A. Gangopadhyay and I.C. daSilveira, 2008. Feature-oriented regional modeling and simulations (FORMS) for the western South Atlantic, southeastern Brazil Region. Ocean Model. 25, 48-64.
- Calado, L., I. C. da Silveira, A. Gangopadhyay, and B. Castro, 2010. Eddy-induced upwelling off the coast of Cape São Tome (22S). Cont. Shelf Res. 30(10-11), 1181-1188. doi:10.1016/j.csr.2010.03.007.
- Carter, E. F., and A. R. Robinson, 1987. Analysis models for the estimation of oceanic fields. J. Atmos. Ocean. Tech. 4(1), 49–74.
- Cummings, J. A., C. Szczechowski, and M. R. Carnes, 1997. Global and regional ocean thermal analysis systems. Marine Technol. Soc. J. 31, 63-75.
- Fox, D. N., M. R. Carnes, and J. L. Mitchell, 1992. Characterizing major frontal systems: A nowcast/forecast system for Northwest Atlantic. Oceanography 5(1), 49-53.
- Gangopadhyay, A., A. R. Robinson, and H. G. Arango, 1997. Circulation and dynamics of the western North Atlantic, I: Multiscale feature models. J. Atmos. Ocean. Tech. 14(6), 1314-1332.
- Gangopadhyay, A., and A. R. Robinson, 1997. Circulation and dynamics of the western North Atlantic, III: Forecasting the meanders and rings. J. Atmos. Ocean. Tech. 14 (6), 1352-1365.
- Gangopadhyay, A., and A. R. Robinson, 2002. Feature oriented regional modeling of oceanic fronts. Dynam. Atmos. Oceans 36(1-3), 201-232.
- Gangopadhyay, A., A. R. Robinson, P. J. Haley, W. J. Leslie, C. J. Lozano, J. J. Bisagni, and Z. Yu, 2003. feature oriented regional modeling and simulation (FORMS) in the Gulf of Maine and Georges Bank. Cont. Shelf Res. 23(3-4), 317-353.
- Gangopadhyay, A., C. Y. Shen, G. O. Marmorino, R. P. Mied and G. Lindemann, 2005. An extended velocity projection method for estimating the subsurface current and density structure for coastal plume regions: An application to the Chesapeake Bay outflow plume. Cont. Shelf Res. 25(2005), 1309-1319.
- Gangopadhyay, A., P. F. J. Lermusiaux, L. K. Rosenfeld, A. R. Robinson, L. Calado, H. S. Kim, W. G. Leslie, and P. J. Haley, Jr., 2011. California Current System: A multiscale overview and the development of a feature-oriented regional modeling system (FORMS). Dyn. Atmos. Oceans 52(1-2), 131-169. doi: 10.1016/j.dynatmoce.2011.04.003.
- Gangopadhyay, A., A. Schmidt, L. Agel, O. Schofield, and J. Clark, 2012. Multiscale forecasting in the western North Atlantic: An application to OSSE in November 2009 and sensitivity to glider data assimilation. Cont. Shelf Res. http://dx.doi.org/10.1016/j.csr.2012.09.013.
- Glenn, S. M., and A. R. Robinson, 1995. Validation of an operational Gulf Stream forecasting model. In: Qualitative Skill Assessment for Coastal Models, AGU Estuarine/Coastal Series, vol. 47, American Geophysical Union, 469-499.
- Hasegawa, D., M. Lewis and A. Gangopadhyay, 2009. How islands cause phytoplankton to bloom in their wakes. Geophys. Res. Lett. 36, L20605, doi:10.1029/2009GL039743, 2009.
- Hulburt, H. E., D. N. Fox, and E. J. Metzger, 1990. Statistical inference of weakly correlated subthermocline fields from satellite altimeter data. J. Geophys. Res. 95, 11,375-11,409.
- Kim, H-S., A. Gangopadhyay, L. K. Rosenfeld, and F. L. Bub, 2007. A high-resolution regional climatology for the central California. Cont. Shelf Res. doi:10.1016/j.csr.2007.05.011.
- Lermusiaux, P. F. J., 1999. Data assimilation via error subspace statistical estimation, part II: Middle Atlantic Bight shelfbreak front simulations and ESSE validation. Mon. Wea. Rev. 1278, 1408-1432.
- Lozano, C. J., A. Robinson, H. G. Arango, A. Gangopadhyay, Q. Sloan, P. J. Haley, L. Anderson, and W. Leslie, 1996. An interdisciplinary ocean prediction system: assimilation strategies and structured data models. In: Modern Approaches to Data Assimilation in Ocean Modeling, (Ed. P. Malanotte-Rizzoli), Elsevier Sciences, pp. 413-452.
- Robinson, A. R., M. A. Spall, and N. Pinardi, 1988. GS simulations and the dynamics of ring and meander processes. J. Phys. Oceanogr. 18, 1811–1853.
- Robinson, A. R., S. M. Glenn, M. A. Spall, L. J. Walstad, G. M. Gardner, and W. G. Leslie, 1989. Forecasting meanders and rings. EOS Oceanogr. Rep. 70(45), 1464-1473.
- Robinson, A. R., and A. Gangopadhyay, 1997. Circulation and dynamics of the western North Atlantic, II: Dynamics of meanders and rings. J. Atmos. Oceanic Tech. 14(6), 1333-1351.
- Robinson, A.R., Glenn, S.M., 1999. Adaptive sampling for ocean forecasting. Naval Res. Rev. 51 (2), 28–38.
- Robinson, Allan R., Brian J. Rothschild, W. G. Leslie, J. J. Bisagni, M. F. Borges, W. S. Brown, D. Cai, P. Fortier, A. Gangopadhyay, P. J. Haley, Jr., H. S. Kim, L. Lanerolle, P. F. J. Lermusiaux, C. J. Lozano, M. G. Miller, G. Strout and M. A. Sundermeyer, 2001. The development and demonstration of an Advanced Fisheries Management Information System (AFMIS). Amer. Met. Soc., 186-190.
- Schmidt, A. C. K., and A. Gangopadhyay, 2012. An operational circulation ocean prediction system for the Northwest Atlantic: Hindcasting during July-September of 2006. Cont. Shelf Res., http://dx.doi.org/10.1016/j.csr.2012.08.017
- Schmidt, A. C. K., A. Gangopadhyay, and P. Brickley, 2012. An operational modeling implementation for the Trinidad-Venezuela region using feature models. MTS/IEEE Proceedings. http:/dx.doi.org/10.1109/OCEANS.2012.6404973.
- Schofield, O., S. M. Glenn, J. Orcutt, M. Arrott, M. Meisinger, A. Gangopadhyay, W. Brown, R. Signell, M. Moline, Y. Chao, S. Chien, D. Thompson, A. Balasuriya, P. Lermusiaux and M. Oliver, 2010. Automated sensor networks to advance ocean science. EOS 91(39), 28 Sept, 2010.
- Shaji, C., and A. Gangopadhyay, 2007. Synoptic modeling of the West India Coastal Current system using an upwelling feature model. J. Atmos. Oceanic Tech. 24(5), 877-893.
- Soutelino, R, I. Silveira, A. Gangopadhyay and J. Miranda, 2011. Is the Brazil Current eddy dominated north of 20S? Geophys. Res. Lett. 38, L03607, doi:10.1029/2010GL046276, 2011.
- Soutelino, R. G., A. Gangopadhyay, and I. C. A. da Silveira, 2013. The roles of topography and vertical shear on the eddy formation near the site of origin of the Brazil Current. Cont. Shelf Res. 70, 46-60. http://dx.doi.org/10.1016/j.csr.2013.10.001.
- Spall, M. A., and A. R. Robinson, 1990. Regional primitive equation studies of the GS meander and ring formation region. J. Phys. Oceanogr. 20, 985–1016.
- Warn-Varnas, A., A. Gangopadhyay, J. Hawkins and A. Robinson, 2005: Wilkinson Basin Area Water Masses: A revisit with EOFs, Cont. Shelf Res, 25, 277-296.