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Tyler Sutterley

Research Scientist/Engineer - Senior





Department Affiliation

Polar Science Center


B.S. Mechanical Engineering, University of California, San Diego, 2008

M.S. Earth System Science, University of California, Irvine, 2012

Ph.D. Earth System Science, University of California, Irvine, 2016


2000-present and while at APL-UW

Automated dynamic mascot generation for GRACE and GRACE-FO harmonic processing

Mohajerani, Y., D. Shean, A. Arendt, and T.C. Sutterley, "Automated dynamic mascot generation for GRACE and GRACE-FO harmonic processing," Remote Sens., 13, doi:10.3390/rs13163134, 2021.

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7 Aug 2021

Commonly used mass-concentration (mascon) solutions estimated from Level-1B Gravity Recovery and Climate Experiment (GRACE) and GRACE Follow-On data, provided by processing centers such as the Jet Propulsion Laboratory (JPL) or the Goddard Space Flight Center (GSFC), do not give users control over the placement of mascons or inversion assumptions, such as regularization. While a few studies have focused on regional or global mascon optimization from spherical harmonics data, a global optimization based on the geometry of geophysical signal as a standardized product with user-defined points has not been addressed. Finding the optimal configuration with enough coverage to account for far-field leakage is not a trivial task and is often approached in an ad-hoc manner, if at all. Here, we present an automated approach to defining non-uniform, global mascon solutions that focus on a region of interest specified by the user, while maintaining few global degrees of freedom to minimize noise and leakage. We showcase our approach in High Mountain Asia (HMA) and Alaska, and compare the results with global uniform mascon solutions from range-rate data. We show that the custom mascon solutions can lead to improved regional trends due to a more careful sampling of geophysically distinct regions. In addition, the custom mascon solutions exhibit different seasonal variation compared to the regularized solutions. Our open-source pipeline will allow the community to quickly and efficiently develop optimized global mascon solutions for an arbitrary point or polygon anywhere on the surface of the Earth.

Comparisons of satellite and airborne altimetry with ground-based data from the interior of the Antarctic ice sheet

Brunt, K.M., B.E. Smith, T.C. Sutterly, N.T. Kurtz, and T.A. Neumann, "Comparisons of satellite and airborne altimetry with ground-based data from the interior of the Antarctic ice sheet," Geophys. Res. Lett., 48, doi:10.1029/2020GL090572, 2021.

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28 Jan 2021

A series of traverses has been conducted for validation of the National Aeronautics and Space Administration Ice, Cloud, and land Elevation Satellite 2 (ICESat‐2) on the flat interior of the Antarctic ice sheet. Global Navigation Satellite System data collected on three separate 88S Traverses intersect 20% of the ICESat‐2 reference ground tracks and have precisions of better than ±7 cm and biases of less than ~4 cm. Data from these traverses were used to assess heights from ICESat‐2, CryoSat‐2, and Airborne Topographic Mapper (ATM). ICESat‐2 heights have better than ±3.3 cm bias and better than ±7.2 cm precision. ATM heights have better than 9.3 cm bias and better than ±9.6 cm precision. CryoSat‐2 heights have –38.9 cm of bias and ±47.3 cm precision. These best case results are from the flat ice‐sheet interior but provide a characterization of the quality of satellite and airborne altimetry.

Greenland ice sheet elevation change: Direct observation of process and attribution at Summit

Hawley, R.L., T.A. Neumann, C.M. Stevens, K.M. Brunt, and T.C. Sutterley, "Greenland ice sheet elevation change: Direct observation of process and attribution at Summit," Geophys. Res. Lett., 47, doi:10.1029/2020GL088864, 2020.

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28 Nov 2020

Greenland Ice Sheet surface elevation is changing as mass loss accelerates. In understanding elevation change, the magnitudes of physical processes involved are important for interpretation of altimetry and assessing changes in these processes. The four key processes are surface mass balance (SMB), firn densification, ice dynamics, and isostatic adjustment. We quantified these processes at Summit, Greenland, where monthly Global Navigation Satellite System (GNSS) snowmobile traverses measured elevation change from 2008 to 2018. We find an elevation increase of 0.019 m a-1. The sum of the effects of the four processes reproduces the measured elevation time series, in linear trend and in intra-annual variability. The short-term variability in elevation is primarily explained by the variability in SMB. Since SMB has not changed significantly over the last century, and the other processes change over longer time scales, the elevation change likely has been ongoing for at least the last 100 years.

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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