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Elizabeth Thompson

Affiliated Research Meterologist

Email

elizabeth.thompson@noaa.gov

Phone

303-497-6930

Research Interests

Coupled air-sea interaction processes, Atmospheric and oceanic boundary layers, Precipitation and clouds, Radar and satellite meteorology, Synoptic and mesoscale meteorology, Physical oceanography

Biosketch

Elizabeth Thompson is a Research Meteorologist at the NOAA Physical Sciences Lab in Boulder, CO. She continues to collaborate with APL-UW scientists since her time at APL-UW.

Education

B.S. Meterology, Valparaiso University, 2010

M.S. Atmospheric Science, Colorado State University, 2012

Ph.D. Atmospheric Science, Colorado State University, 2016

Publications

2000-present and while at APL-UW

Evaluation of the RainFARM statistical downscaling technique applied to IMERG over global oceans using Passive Aquatic Listener in situ rain measurements

Bytheway, J.L., E.J. Thompson, J. Yang, and H. Chenc, "Evaluation of the RainFARM statistical downscaling technique applied to IMERG over global oceans using Passive Aquatic Listener in situ rain measurements," J. Hydrometeorol., 24, 2351-2367, doi:10.1175/JHM-D-23-0090.1, 2023.

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1 Dec 2023

High-resolution oceanic precipitation estimates are needed to increase our understanding of and ability to monitor ocean–atmosphere coupled processes. Satellite multisensor precipitation products such as IMERG provide global precipitation estimates at relatively high resolution (0.1°, 30 min), but the resolution at which IMERG precipitation estimates are considered reliable is coarser than the nominal resolution of the product itself. In this study, we examine the ability of the Rainfall Autoregressive Model (RainFARM) statistical downscaling technique to produce ensembles of precipitation fields at relatively high spatial and temporal resolution when applied to spatially and temporally coarsened precipitation fields from IMERG. The downscaled precipitation ensembles are evaluated against in situ oceanic rain-rate observations collected by passive aquatic listeners (PALs) in 11 different ocean domains. We also evaluate IMERG coarsened to the same resolution as the downscaled fields to determine whether the process of coarsening then downscaling improves precipitation estimates more than averaging IMERG to coarser resolution only. Evaluations were performed on individual months, seasons, by ENSO phase, and based on precipitation characteristics. Results were inconsistent, with downscaling improving precipitation estimates in some domains and time periods and producing worse performance in others. While the results imply that the performance of the downscaled precipitation estimates is related to precipitation characteristics, it is still unclear what characteristics or combinations thereof lead to the most improvement or consistent improvement when applying RainFARM to IMERG.

Saturation of ocean surface wave slopes observed during hurricanes

Davis, J.R., J. Thomson, I.A. Houghton, J.D. Doyle, W.A. Komaromi, C.W. Fairall, E.J. Thompson, and J.R. Moskaitis, "Saturation of ocean surface wave slopes observed during hurricanes," Geophys. Res. Lett., 50, doi:10.1029/2023GL104139, 2023.

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28 Aug 2023

Drifting buoy observations of ocean surface waves in hurricanes are combined with modeled surface wind speeds. The observations include targeted aerial deployments into Hurricane Ian (2022) and opportunistic measurements from the Sofar Ocean Spotter global network in Hurricane Fiona (2022). Analysis focuses on the slope of the waves, as quantified by the spectral mean square slope. At low-to-moderate wind speeds (<15 ms-1), slopes increase linearly with wind speed. At higher winds (>15 ms-1), slopes continue to increase, but at a reduced rate. At extreme winds (>30 ms-1), slopes asymptote. The mean square slopes are directly related to the wave spectral shapes, which over the resolved frequency range (0.03–0.5 Hz) are characterized by an equilibrium tail (f-4) at moderate winds and a saturation tail (f-5) at higher winds. The asymptotic behavior of wave slope as a function of wind speed could contribute to the reduction of surface drag at high wind speeds.

Small-scale spatial variations of air-sea heat, moisture, and buoyancy fluxes in the tropical trade winds

Iyer, S., K. Drushka, E.J. Thompson, and J. Thomson, "Small-scale spatial variations of air-sea heat, moisture, and buoyancy fluxes in the tropical trade winds," J. Geophys. Res., 127, doi:10.1029/2022JC018972, 2022.

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1 Oct 2022

Observations from two autonomous Wave Gliders and six Lagrangian Surface Wave Instrument Float with Tracking drifters in the northwestern tropical Atlantic during the January–February 2020 NOAA Atlantic Tradewind Ocean-atmosphere Mesoscale Interaction Campaign (ATOMIC) are used to evaluate the spatial variability of bulk air-sea heat, moisture, and buoyancy fluxes. Sea surface temperature (SST) gradients up to 0.7°C across 10–100 km frequently persisted for several days. SST gradients were a leading cause of systematic spatial air-sea sensible heat flux gradients, as variations over 5 Wm-2 across under 20 km were observed. Wind speed gradients played no significant role and air temperature adjustments to SST gradients sometimes acted to reduce spatial flux gradients. Wind speed, air temperature, and air humidity caused high-frequency spatial and temporal flux variations on both sides of SST gradients. A synthesis of observations demonstrated that fluxes were usually enhanced on the warm SST side of gradients compared to the cold SST side, with variations up to 10 Wm-2 in sensible heat and upward buoyancy fluxes and 50 Wm-2 in latent heat flux. Persistent SST gradients and high-frequency air temperature variations each contributed up to 5 Wm-2 variability in sensible heat flux. Latent heat flux was instead mostly driven by air humidity variability. Atmospheric gradients may result from convective structures or high-frequency turbulent fluctuations. Comparisons with 0.05°-resolution daily satellite SST observations demonstrate that remote sensing observations or lower-resolution models may not capture the small-scale spatial ocean variability present in the Atlantic trade wind region.

More Publications

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
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