ORCID

https://orcid.org/0000-0003-3364-8586

Date of Award

Summer 2025

Language

English

Embargo Period

7-30-2025

Document Type

Dissertation

Degree Name

Doctor of Philosophy (PhD)

College/School/Department

Department of Atmospheric and Environmental Sciences

Program

Atmospheric Science

First Advisor

Jeffrey Freedman

Committee Members

Jeffrey Freedman, Scott Miller, Justin Minder, David Fitzjarrald

Keywords

boundary layer meteorology, sea breeze, low-level jet, offshore wind, mesoscale coastal flows

Subject Categories

Atmospheric Sciences

Abstract

Mid-latitude coastal regions of the United States, such as the New York Bight (NYB), are playing a major role in the development of offshore wind energy. However, mesoscale dynamics of local and regional circulations in these offshore waters are poorly understood. The sea breeze, especially in the NYB, will play a key role in the development of offshore wind energy, given the favorable wind speeds and high capacity factors during periods of peak demand. With limited vertical wind profile observations available offshore, the ability to accurately forecast and understand the spatiotemporal extent of the sea breeze and often associated low-level jet (LLJ) is limited. While models can qualitatively reproduce the sea breeze circulation and LLJ, at this point, their performance in accurately depicting these features is underwhelming. The goal of this dissertation is to better understand and forecast the mechanisms behind LLJ development during sea breeze events, the relationship to atmospheric stability, and the direct impact on offshore wind energy development (including energy generation, wind farm waking, and load reduction). This dissertation addresses the limitations in understanding mesoscale wind flows such as the NYB sea breeze and associated LLJ through both an observational and numerical modeling analysis.

An observationally based methodology is developed to objectively identify sea-breeze days and their associated LLJs between 2010 and 2020, identifying an average of 32 sea breeze days annually. Most frequent during the warm season months, sea breeze events feature wind consistently backing to the south and strengthening around 1800 UTC, increasing wind speeds most during hours coinciding with high energy demand. LLJs are often associated with a sea breeze, and typically occur 150–300 m above mean sea level (AMSL)

Using Numerical Weather Prediction (NWP), specifically the Weather Research and Forecasting (WRF) modeling system on select summertime sea breeze events, all with an associated LLJ, sensitivity analyses test 18 different WRF configurations to optimize model performance in the NYB. Sea surface temperatures (SSTs) are initialized in the model using the Operational Sea Surface Temperature and Ice Analysis (OSTIA). These extensive tests reveal the importance of fine tuning the model to the study region and targeted weather conditions, as small changes to physics settings can have a significant effect on overall model performance. It was determined that the Mellor–Yamada–Janjić (MYJ) planetary boundary layer scheme, combined with the Noah land surface model and the urban parameterization turned off, is best suited to model these mesoscale summertime phenomena.

As one of the main driving factors behind LLJ intensification is the air-sea temperature difference, the relationship between the sea breeze and cold water coastal upwelling, another warm season regional phenomenon, is considered. A common problem in understanding cold water coastal upwelling is that satellite datasets have resolution limitations that make it difficult to detect localized and episodic pockets of relatively cold water along the coastlines. To isolate the influence of upwelling on the sea breeze, the input OSTIA satellite data is edited along the New Jersey coastline to perform three experiments; “GradientUpwell”, characterized by extreme cold water upwelling along coastline, “NoUpwell”, where any upwelling is removed, and “WarmAll”, where SSTs are uniformly increased based on current trends and future climate projections. Results show that cold water coastal upwelling locally increases atmospheric stability, decreasing the height and increasing the magnitude of the LLJ while also increasing the overall strength and inland propagation of the sea breeze.

Moving forward, as wind energy areas in the NYB are built out, it is not only important to understand the resource but the implications of the sea breeze and LLJ on wind energy generation. While gross capacity factors can currently be estimated, the wake effects, especially under stable conditions (such as during sea breeze events), are largely unknown. A clear understanding of stability in offshore regions is still developing, as high-resolution thermodynamic profiles are uncommon. With such an important relationship between stability and long-range (> 50 km) offshore wakes, it has become increasingly important to be able to reliably estimate stability conditions in offshore regions. At early stages in wind energy development it is necessary to rely on mesoscale models such as the WRF modeling system, to estimate both stability and wake lengths. Given that there are no observations over the NYB region that measure atmospheric stability or incorporate the impact of wind farms, to gain confidence in WRF's ability to reproduce wake effects and potential losses, the model is validated from flight data over wind farms in North Sea. As thermal stability is critical to understanding wake length, using vertical profiles taken during the flights, different metrics are evaluated to determine the best way to parameterize atmospheric stability from the WRF model. Finding show that the bulk Richardson number derived from WRF can be used as a reliable metric to classify stability and that wake lengths are well represented under stable conditions. With a better understanding of limitations and reliability in WRF's wake model, the analysis over the North sea can be translated to better predict wind farm impacts in the NYB.

License

Creative Commons Attribution 4.0 International License
This work is licensed under a Creative Commons Attribution 4.0 International License.

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