Hughes, P. J. (2014). The Influence of Small-Scale Sea Surface Temperature Gradients on Surface Vector Winds and Subsequent Impacts on Oceanic Ekman Pumping . Tallahassee, FL: Florida State University.
Glazer, R. H. (2014). The Influence of Mesoscale Sea Surface Temperature Gradients on Tropical Cyclones . Master's thesis, Florida State University, Tallahassee, FL.
Armstrong, E. M., Bourassa, M. A., Cram, T., Elya, J. L., Greguska, F. R., III, Huang, T., et al. (2018). An information technology foundation for fostering interdisciplinary oceanographic research and analysis. In American Geophysical Union (Vol. Fall Meeting).
Abstract: Before complex analysis of oceanographic or any earth science data can occur, it must be placed in the proper domain of computing and software resources. In the past this was nearly always the scientist's personal computer or institutional computer servers. The problem with this approach is that it is necessary to bring the data products directly to these compute resources leading to large data transfers and storage requirements especially for high volume satellite or model datasets. In this presentation we will present a new technological solution under development and implementation at the NASA Jet Propulsion Laboratory for conducting oceanographic and related research based on satellite data and other sources. Fundamentally, our approach for satellite resources is to tile (partition) the data inputs into cloud-optimized and computation friendly databases that allow distributed computing resources to perform on demand and server-side computation and data analytics. This technology, known as NEXUS, has already been implemented in several existing NASA data portals to support oceanographic, sea-level, and gravity data time series analysis with capabilities to output time-average maps, correlation maps, Hovmöller plots, climatological averages and more. A further extension of this technology will integrate ocean in situ observations, event-based data discovery (e.g., natural disasters), data quality screening and additional capabilities. This particular activity is an open source project known as the Apache Science Data Analytics Platform (SDAP) (https://sdap.apache.org), and colloquially as OceanWorks, and is funded by the NASA AIST program. It harmonizes data, tools and computational resources for the researcher allowing them to focus on research results and hypothesis testing, and not be concerned with security, data preparation and management. We will present a few oceanographic and interdisciplinary use cases demonstrating the capabilities for characterizing regional sea-level rise, sea surface temperature anomalies, and ocean hurricane responses.
Morey, S. L., Wienders, N., Dukhovskoy, D. S., & Bourassa, M. A. (2018). Impact of Stokes Drift on Measurements of Surface Currents from Drifters and HF Radar. In American Geophysical Union (Vol. Fall Meeting).
Abstract: Concurrent measurements by surface drifters of different configurations and HF radar reveal substantial differences in estimates of the near-surface seawater velocity. On average, speeds of small ultra-thin (5 cm) drifters are significantly greater than co-located drifters with a traditional shallow drogue design, while velocity measurements from the drogued drifters closely match HF radar velocity estimates. Analysis of directional wave spectra measurements from a nearby buoy reveals that Stokes drift accounts for much of the difference between the velocity measurements from the drogued drifters and the ultra-thin drifters, except during times of wave breaking. Under wave breaking conditions, the difference between the ultra-thin drifter velocity and the drogued drifter velocity is much less than the computed Stokes drift. The results suggest that surface currents measured by more common approaches or simulated in models may underrepresent the velocity at the very surface of the ocean that is important for determining momentum and enthalpy fluxes between the ocean and atmosphere and for estimating transport of material at the ocean surface. However, simply adding an estimate of Stokes drift may also not be an appropriate method for estimating the true surface velocity from models or measurements from drogued drifters or HF radar under all sea conditions.
Gentemann, C. L., Clayson, C. A., Brown, S., Lee, T., Parfitt, R., Farrar, J. T., et al. (2020). FluxSat: Measuring the Ocean-Atmosphere Turbulent Exchange of Heat and Moisture from Space. Remote Sensing , 12 (11), 1796.
Abstract: Recent results using wind and sea surface temperature data from satellites and high-resolution coupled models suggest that mesoscale ocean-atmosphere interactions affect the locations and evolution of storms and seasonal precipitation over continental regions such as the western US and Europe. The processes responsible for this coupling are difficult to verify due to the paucity of accurate air-sea turbulent heat and moisture flux data. These fluxes are currently derived by combining satellite measurements that are not coincident and have differing and relatively low spatial resolutions, introducing sampling errors that are largest in regions with high spatial and temporal variability. Observational errors related to sensor design also contribute to increased uncertainty. Leveraging recent advances in sensor technology, we here describe a satellite mission concept, FluxSat, that aims to simultaneously measure all variables necessary for accurate estimation of ocean-atmosphere turbulent heat and moisture fluxes and capture the effect of oceanic mesoscale forcing. Sensor design is expected to reduce observational errors of the latent and sensible heat fluxes by almost 50%. FluxSat will improve the accuracy of the fluxes at spatial scales critical to understanding the coupled ocean-atmosphere boundary layer system, providing measurements needed to improve weather forecasts and climate model simulations.
