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Interpolating through time and space  with empirical orthogonal functions
Poster Title: Interpolating through time and space with empirical orthogonal functions
Submitted on 10 Oct 2014
Author(s): M Jordan Stanway, Yanwu Zhang, James G Bellingham
Affiliations: Monterey Bay Aquarium Research Institute
This poster was presented at ASLO Ocean Sciences Meeting
Poster Views: 1,753
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Poster Information
Abstract: Interpolation is necessary when working with many types of real-world data -- for example, it is required to overcome limited spatial and temporal resolution and data gaps. Interpolation through both space and time together can be particularly difficult. We present a novel approach using singular value decomposition to decouple the spatial and temporal components, interpolate them independently, and reconstruct the original field on an as-needed basis. The empirical orthogonal functions (EOFs) describe the spatial variability, and their expansion coefficients (ECs) capture the temporal variability. This decomposition simplifies the problem. Since the leading EOF modes capture the majority of the spatial information, the original variable can often be reconstructed using fewer EOFs than original timesteps. Additionally, the interpolants over the EOFs and ECs can be pre-computed, and building the interpolant is often more costly than evaluating it at the desired coordinates. We demonstrate the new method in three example applications using surface current data in Monterey Bay: upsampling the current fields, calculating the path of a surface drifter, and tying in with forecast data generated by a compact ocean model.Summary: see abstract (it is quite short)References: Björnsson, H. and Venegas, S.A. (1997). A manual for EOF and SVD analyses of climate data. CCGCR Report No. 97-1

Paduan, J.D., and Cook, M.S. 1997. Mapping surface currents in Monterey Bay with CODAR-type HF radar. Oceanography 10(2):49–52

Frolov, S., Paduan, J.D., Cook, M.S., and Bellingham, J. 2012. Improved statistical prediction of surface currents based on historic HF-Radar observations. Ocean Dynamics 62(7):1111-1122
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