Publication details for Professor Richard HobbsBuffett, G. G., Hurich, C. A., Vsemirnova, E. A., Hobbs, R. W., Sallarès, V., Carbonell, R., Klaeschen, D. & Biescas, B. (2010). Stochastic Heterogeneity Mapping around a Mediterranean salt lens. Ocean Science 6(1): 423-429.
- Publication type: Journal Article
- ISSN/ISBN: 1812-0784, 1812-0792
- DOI: 10.5194/os-6-423-2010
- Further publication details on publisher web site
- Durham Research Online (DRO) - may include full text
Author(s) from Durham
We present the first application of Stochastic Heterogeneity Mapping based on the band-limited von Kármán function to a seismic reflection stack of a Mediterranean water eddy (meddy), a large salt lens of Mediterranean water. This process extracts two stochastic parameters directly from the reflectivity field of the seismic data: the Hurst number, which ranges from 0 to 1, and the correlation length (scale length). Lower Hurst numbers represent a richer range of high wavenumbers and correspond to a broader range of heterogeneity in reflection events. The Hurst number estimate for the top of the meddy (0.39) compares well with recent theoretical work, which required values between 0.25 and 0.5 to model internal wave surfaces in open ocean conditions based on simulating a Garrett-Munk spectrum (GM76) slope of −2. The scale lengths obtained do not fit as well to seismic reflection events as those used in other studies to model internal waves. We suggest two explanations for this discrepancy: (1) due to the fact that the stochastic parameters are derived from the reflectivity field rather than the impedance field the estimated scale lengths may be underestimated, as has been reported; and (2) because the meddy seismic image is a two-dimensional slice of a complex and dynamic three-dimensional object, the derived scale lengths are biased to the direction of flow. Nonetheless, varying stochastic parameters, which correspond to different spectral slopes in the Garrett-Munk spectrum (horizontal wavenumber spectrum), can provide an estimate of different internal wave scales from seismic data alone. We hence introduce Stochastic Heterogeneity Mapping as a novel tool in physical oceanography.