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Ralph Foster

Principal Physicist





Research Interests

Boudary Layer Turbulence, Remote Sensing


Dr. Foster's primary research interest is the dynamics of atmospheric planetary boundary layer (PBL) turbulence with an emphasis on improving PBL parameterization in global and mesoscale models. Of particular interest is the role of coherent structures on fluxes in the PBL and their effect on air-sea fluxes. Previous work has been primarily on theoretical models and numerical simulations of coherent structures and their effects.

The majority of his current research involves analysis of satellite remote sensing data products, especially scatterometer surface wind data and synthetic aperture radar (SAR) imagery of the ocean surface. The current scatterometers provide nearly global daily retrievals of the surface wind vectors over the world's oceans on 25 km footprints. Often clear signatures of atmospheric PBL eddies and organized flow are imaged by SAR as a result of the wind stress acting on the sea surface. He is currently working towards a better understanding of the air-sea momentum transfer and how it manifests in SAR imagery. A long-term goal is to integrate theoretical analyses, numerical simulation, observational and remote sensing studies in order to improve understanding of coherent structures and to incorporate their non-local effects in operational PBL parameterizations.


B.S. Physics, University of California - Berkeley, 1983

Ph.D. Atmospheric Sciences, University of Washington - Seattle, 1996


2000-present and while at APL-UW

Classification of the global Sentinel-1 SAR vignettes for ocean surface process studies

Wang, C., and 8 others including R.C. Foster, "Classification of the global Sentinel-1 SAR vignettes for ocean surface process studies," Remote Sens. Environ., 234, doi:10.1016/j.rse.2019.111457, 2019.

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1 Dec 2019


• First deep learning model to classify ten geophysical phenomena from S-1 WV SAR data.
• Model performance is evaluated using an independent eye-selected dataset.
• Classified rain cells and sea ice are compared with other satellite measurements.
• The global S-1 SAR data show great potential for sea surface processes studies.

The contribution of extratropical waves to the MJO wind field

Adames, A.F., J. Patoux, and R.C. Foster, "The contribution of extratropical waves to the MJO wind field," J. Atmos. Sci., 71, 155-176, doi:10.1175/JAS-D-13-084.1, 2014.

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1 Jan 2014

A method for capturing the different dynamical components of the Madden–Julian oscillation (MJO) is presented. The tropical wind field is partitioned into three components using free-space Green's functions: 1) a nondivergent component, 2) an irrotational component, and 3) a background or environmental flow that is interpreted as the influence on the tropical flow due to vorticity and divergence elements outside of the tropical region. The analyses performed in this study show that this background flow is partly determined by a train of extratropical waves. Space–time power spectra for each flow component are calculated. The strongest signal in the nondivergent wind spectrum corresponds to equatorial Rossby, mixed Rossby–gravity, and easterly waves. The strongest signal in the irrotational winds corresponds to Kelvin and inertia–gravity modes. The strongest signal in the power spectrum of the background flow corresponds to the wave band of extratropical Rossby waves. Furthermore, a coherence analysis reveals that the background flow has the highest coherence with geopotential height variations in the latitude bands from 30° to 45° in both the Northern and Southern Hemispheres.

The flow partitions are further studied through a composite analysis based on the Wheeler–Hendon MJO index. Anomalies in the background flow are strongest in the western and central Pacific, possess an equivalent barotropic structure, and show an eastward propagation. By contrast, the irrotational and nondivergent winds possess a first-mode baroclinic structure. An oscillation in the zonally averaged background flow with the MJO phases is observed but contributes little to tropical angular momentum when compared to the nondivergent flow.

Cross-validation of scatterometer measurements via sea-level pressure retrieval

Patoux, J., and R.C. Foster, "Cross-validation of scatterometer measurements via sea-level pressure retrieval," IEEE Trans. Geosci. Remote Sens., 50, 2507-2517, doi:10.1109/TGRS.2011.2172620, 2012

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1 Jul 2012

A combined analysis of ocean surface wind vector measurements by the European Advanced Scatterometer (ASCAT) and the National Aeronautics and Space Administration QuikSCAT (QS) scatterometer using buoy measurements, numerical weather prediction model analyses, and spectral decomposition reveals significant statistical differences between the two data sets. While QS wind speeds agree better with buoy wind speeds than ASCAT above 15 m s-1, ASCAT wind directions agree better with buoy directions overall than QS. In contrast, it is shown that sea-level pressure (SLP) fields derived from ASCAT and QS measurements compare better with each other than the winds in a statistical sense, even though ASCAT bulk pressure gradients (BPGs) are slightly weaker than buoy pressure gradients and have slightly lower spectral energy than QS. Weaker BPGs in ASCAT are consistent with the low bias in ASCAT wind speeds. Thus, it is proposed that scatterometer-derived SLP fields can be used as a filter to improve the wind directions. This improves the QS wind directions but has less effect on the more accurate ASCAT wind directions. The unfiltered ASCAT wind vector statistics compare well with the statistics of the direction-filtered QS winds. It is suggested that this methodology might provide a basis for minimizing the discrepancies between various satellite wind measurement data sets in view of producing a long-term record of satellite-derived SLP fields and ocean surface wind vectors.

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Acoustics Air-Sea Interaction & Remote Sensing Center for Environmental & Information Systems Center for Industrial & Medical Ultrasound Electronic & Photonic Systems Ocean Engineering Ocean Physics Polar Science Center