Text

theses

ETD graduate

The Mid Atlantic Bight (MAB) is a unique environment that supports diverse ecosystems, contains complex oceanographic features, and is located near dense centers of human population. A key component of the MAB shelf that affects its ecosystems and coastal communities is the Cold Pool. This cold-water mass develops below the seasonal thermocline from remnant winter water and remains present in the mid to outer shelf throughout the summer. The Cold Pool is the source for coastal upwelling, which is focused upon in this thesis as a unique oceanographic feature of the MAB that has implications for stakeholder groups like fisheries and offshore wind. Upwelling is important to coastal regions around the world and is linked with hypoxic bottom conditions and influences atmospheric circulation in the MAB. Coastal Upwelling was previously defined by Glenn et al. (2004) as a difference between onshore and offshore sea surface temperature (SST) of at least 2°C. Using this definition, we can describe coastal upwelling events, both in size and duration from satellite SST fields.

This study involved the use of newly available high resolution GOES-16 SST for the observation of coastal upwelling in the MAB. Locally focused cloud-correcting methods, referred to as the Spike Filter (SF), were developed for GOES SST in order to retain upwelling pixels. The Spike Filter (SF) method, greatly increased SST coverage of the coastal zone of the MAB by retaining more SST measurements than the aggressive cloud correcting algorithm (Quality Filter) provided by NOAA. DINEOF (Alvera-Azcárate et al. 2009) was then used to statistically gap-fill missing data to complete the GOES SST fields. GOES SF DINEOF SST approximately doubled the number of detected upwelling days compared to MUR SST. The longest upwelling event detected in GOES SF DINEOF persisted for over 17 days which is longer than the maximum outlier previously observed using 9 years of AVHRR measurements (Glenn et al. 2004). These observations suggest that MAB upwelling may be occurring more persistently, rather than as a series of short episodic events, and they can be more readily observed with continuous GOES SST data. Clear detection of the timing and duration of upwelling events is important as it provides estimates for ecological and physical responses in the MAB. GOES SST is valuable for the detection of upwelling in the MAB and should be adapted for application in ocean and atmospheric modeling.

GOES SF DINEOF SST was then used as part of an atmospheric analysis to test the sensitivity of the Rutgers Weather Research and Forecasting Model (RU-WRF) to different ocean surface boundary conditions. Three SST products, varying in resolution and their ability to capture upwelling, were chosen for this analysis. This analysis demonstrated that there is a difference in RU-WRF forecasted wind speeds at a location in the NJ offshore wind energy using different SSTs during a week-long upwelling event. Forecasted wind speeds at turbine hub height varied in both the timing of wind speed changes and the total magnitude, which equate to differences in the potential wind power production for an offshore wind turbine. The accuracy of forecasted winds in this area affect the ability of the wind farm to correctly match electricity supply to grid demand. This analysis makes the case for further investigations over a longer time period that can be validated with newly available data such as the Atlantic shores LIDAR buoy to determine what SST provides the most accurate ocean conditions and wind forecasts.

ETD_11388

M.S.

Includes bibliographical references

doi:10.7282/t3-grcm-z596

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