Modelling sea‐breeze climatologies and interactions on coasts in the southern North Sea: implications for offshore wind energy

Abstract

Current understanding of the behaviour of sea breezes in the offshore environment is limited but rapidly requires improvement due, not least, to the expansion of the offshore wind energy industry. Here we report on contrasting characteristics of three sea-breeze types on five coastlines around the southern North Sea from an 11 year model-simulated climatology. We present and test an identification method which distinguishes sea-breeze types which can, in principle, be adapted for other coastlines around the world. The coherence of the composite results for each type demonstrates that the method is very effective in resolving and distinguishing characteristics and features. Some features, such as jets and calm zones, are shown to influence offshore wind farm development areas, including the sites of the proposed wind farms up to 200 km offshore. A large variability in sea-breeze frequency between neighbouring coastlines of up to a factor of 3 is revealed. Additionally, there is a strong association between sea-breeze type on one coastline and that which may form coincidentally on another nearby. This association can be as high as 86% between, for example, the North Norfolk and East Norfolk coasts. We show, through associations between sea-breeze events on coastlines with contrasting orientations, that each coastline can be important for influencing the wind climate of another. Furthermore, we highlight that each sea-breeze type needs separate consideration in wind power resource assessment and that future larger turbines will be more sensitive to sea-breeze impacts.

Influence of the North Atlantic Subtropical High on wet and dry sea-breeze events in North Carolina, United States

“…The majority of SB dry parallel flow events (10 of 16) can be defined as backdoor (Adams, 1997) because they occurred during days when the synoptic-scale flow was from the northwest. The fact that most of the SB dry parallel flow events in this study are classified as backdoor agrees well with the hypothesis that backdoor SB are weaker and less conducive to precipitation than their corkscrew counterparts (Steele et al, 2014).…”

“…The majority of those SB wet parallel flow events (10 of 12) occurred during days when the flow was from the southwest and can be defined as corkscrew sea breeze events (Adams, 1997). The fact that most of the SB wet parallel flow events in this study are classified as corkscrew corroborates theoretical and modeling studies that indicate that corkscrew SB are stronger and likely conducive to precipitation (Steele et al, 2014). In contrast, among the 47 SB dry events, 30 (64%) occurred under offshore synoptic flow, 16 (34%) under parallel flow and 1 (2%) under onshore flow.…”

“…Gillian et al, (2004) shows that the SB can propagate farther inland during parallel synoptic scale flow than during onshore flows. Synoptic-scale parallel flow SBs can be divided into two types, corkscrew and backdoor SBs (e.g., Adams, 1997;Miller et al, 2003;Steele et al, 2014). During a corkscrew SB in the northern hemisphere the flow is parallel to the coast with the land to the left of the flow.…”

“…The SB has been shown to be influenced by the shape of the coastline (Gilliam et al, 2004;Steele et al, 2014), interactions with topography (Zhu and Atkinson, 2004;Azorin-Molina, Tijm, Ebert, Vicente-Serrano and Estrela, 2015;Naor, Potcher, Shafir and Alpert, 2017) and interactions with ocean currents such as the Gulf Stream (Jacobs, Lackman and Raman, 2005). Previous studies of SB fronts in NC have focused on numerical and observational case studies of the effects of geophysical variables on SB evolution (Ray, 1995;Koch and Ray, 1997;Gilliam et al, 2004).…”

The application of high-resolution atmospheric modelling to weather and climate variability in vineyard regions

“…Potential cold bias of model predictions has previously been recognized (Steele et al, 2014;Hu et al, 2010), and needs to be allowed for when interpreting analysis of spatial patterns across the region. This cold bias will be the subject of further research so that appropriate adjustments can be made.…”