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Chris Chickadel

Principal Oceanographer

Affiliate Assistant Professor, Civil and Environmental Engineering






B.S. Oceanography, University of Washington, 1997

M.S. Oceanography, Oregon State University, 2003

Ph.D. Oceanography, Oregon State University, 2007


Inner Shelf Dynamics

The inner shelf region begins just offshore of the surf zone, where breaking by surface gravity waves dominate, and extends inshore of the mid-shelf, where theoretical Ekman transport is fully realized. Our main goal is to provide provide improved understanding and prediction of this difficult environment. This will involve efforts to assess the influence of the different boundaries — surf zone, mid and outer shelf, air-water interface, and bed — on the flow, mixing and stratification of the inner shelf. We will also gain information and predictive understanding of remotely sensed surface processes and their connection to processes in the underlying water column.

15 Dec 2015

COHerent STructures in Rivers and Estuaries eXperiment

The experiment is a four-year collaborative project that couples state-of-the-art remote sensing and in situ measurements with advanced numerical modeling to characterize coherent structures in river and estuarine flows.

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Coherent structures are generated in rivers and estuaries when the flow interacts with bathymetric and coastline features or when density stratification causes a gradient in surface properties. These coherent structures produce surface signatures that can be detected and quantified using remote sensing techniques. A second objective of this project is to determine the extent to which these remotely sensed signatures can be used to initialize and guide predictive models.

The study site selected for Year 1 and Year 2 field operations was the Snohomish River in Everett, WA. Its annual mean flow of approximately 300 cubic meters per second is the third largest discharge into Puget Sound. The mouth of the river is defined by the city of Everett to the west (man-influenced) and Jetty Island to the east (natural). The river is dredged to a nominal depth of 5 m from the mouth at the south end of Jetty Island to approximately 12 km upstream, while the undredged depth is nominally 1-3 m. Thus the river profile is a compound channel, with the full 300 m width at Jetty Island containing the dredged channel of about 50 m width. The tidal forcing is strong, with the tidal range representing up to 2/3 of the river%u2019s mean depth. There is a bypass between the north end of Jetty Island and the mainland that connects to a mudflat area. During high tides, the river flow bifurcates between the main channel and this bypass, while at low tide very little flow occurs in the bypass. A sill extends from the north tip of Jetty Island to the southeast toward the opposite bank. The depth along this sill varies from 2 m to 5 m and terminates in a large scour hole in the middle of the channel with a depth of about 10 m.

This research is being conducted by a partnership of experts in remote sensing, numerical modeling, and estuarine dynamics from the University of Washington (Applied Physics Laboratory, Civil and Environmental Engineering, and Oceanography) and Stanford University (Environmental Fluid Mechanics Laboratory). The program is funded by a Multidisciplinary University Research Initiative (MURI) grant sponsored by the Office of Naval Research.

Tidal Flats

Under an ONR-sponsored Department Research Initiative researchers are studying thermal signatures of inter-tidal sediments. The goal is to understand how sediment properties feedback on morphology and circulation, and the extent to which such properties
can be sensed remotely.



2000-present and while at APL-UW

Optical wave gauging using deep neural networks

Buscombe, D., R.J. Carini, S.R. Harrison, C.C. Chickadel, and J.A. Warrick, "Optical wave gauging using deep neural networks," Coast. Eng., 155, doi:j.coastaleng.2019.103593, 2020.

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1 Jan 2020


• A convolutional neural network model to estimate wave height and period from images of waves.
• Trained using close-range infrared images of individual waves and visible-band orthomosaics.
• The best models achieve sub-decimeter accuracy for wave height and sub-second for wave period.
• Image regions important to model predictions can be visualized and are physically realistic.

Bias correction of airborne thermal infrared observations over forests using melting snow

Pestana, S., C.C. Chickadel, A. Harpold, T.S. Kostadinov, H. Pai, S. Tyler, C. Webster, and J.D. Lundquist, "Bias correction of airborne thermal infrared observations over forests using melting snow," Water Resour. Res., 55, 11,331-11,343, doi:10.1029/2019WR025699, 2019.

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1 Dec 2019

Uncooled thermal infrared (TIR) imagers, commonly used on aircraft and small unmanned aircraft systems (UAS, "drones"), can provide high‐resolution surface temperature maps, but their accuracy is dependent on reliable calibration sources. A novel method for correcting surface temperature observations made by uncooled TIR imagers uses observations over melting snow, which provides a constant 0°C reference temperature. This bias correction method is applied to remotely sensed surface temperature observations of forests and snow over two mountain study sites: Laret, Davos, Switzerland (27 March 2017) in the Alps, and Sagehen Creek, California, USA (21 April 2017) in the Sierra Nevada. Surface temperature retrieval errors that arise from temperature‐induced instrument bias, differences in image resolution, retrieval of mixed pixels, and variable view angles were evaluated for these forest snow scenes. Applying the melting snow‐based bias correction decreased the root‐mean‐square error by about 1°C for retrieving snow, water, and forest canopy temperatures from airborne TIR observations. The influence of mixed pixels on surface temperature retrievals over forest snow scenes was found to depend on image resolution and the spatial distribution of forest stands. Airborne observations over the forests at Sagehen showed that near the edges of TIR images, at more than 20° from nadir, the snow surface within forest gaps smaller than 10 m was obscured by the surrounding trees. These off‐nadir views, with fewer mixed pixels, could allow more accurate airborne and satellite‐based observations of canopy surface temperatures.

Satellite observations of SST-induced wind speed perturbation at the oceanic submesoscale

Gaube, P., C.C. Chickadel, R. Branch, and A. Jessup, "Satellite observations of SST-induced wind speed perturbation at the oceanic submesoscale," Geophys. Res. Lett., 46, 2690-2695, doi:10.1029/2018GL080807, 2019.

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16 Mar 2019

Sea Surface Temperature (SST) modifies the turbulent mixing, drag, and pressure gradients within the marine atmospheric boundary layer that accelerate near‐surface flow from cool to warm SST and decelerate the flow from warm to cool SST. This phenomenon is well documented on scales of 100–1,000 km (the oceanic mesoscale); however, the nature of this air–sea coupling at scales on the order of 1–10 km (the submesoscale) remains unknown. The Advanced Spaceborne Thermal Emission and Reflection Radiometer can be used to study submesoscale phenomena because the high‐resolution infrared and near‐infrared images can used to estimate both SST and wind speed. Observations of dramatic temperature and wind gradients along the Gulf Stream landward edge are used to examine the surface wind response to submesoscale fronts in SST. Our analysis indicates that SST‐induced wind speed perturbations are observed at the scales of order 1–10 km, significantly smaller than previously suggested.

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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