Preprints
https://doi.org/10.5194/egusphere-2025-4848
https://doi.org/10.5194/egusphere-2025-4848
14 Nov 2025
 | 14 Nov 2025
Status: this preprint is open for discussion and under review for Geoscientific Model Development (GMD).

Identifying sea breezes from atmospheric model output (sea_breeze v1.1)

Andrew Brown, Claire Vincent, and Ewan Short

Abstract. The sea breeze is a mesoscale atmospheric circulation that has implications for human activity and wind energy availability in coastal areas. Sea breezes have been studied in many regions throughout the world, with analyses usually identifying them at individual coastal sites based on local characteristics. Therefore, there is currently a lack of robust and generalizable identification methods, resulting in difficulties analyzing sea breeze characteristics over large regions. Here, software is developed that applies three, physically-based diagnostics for sea breeze identification to atmospheric model datasets. The diagnostics are tested across the coastline of Australia over a 6-month period. These diagnostics identify sea breezes based on either a front or circulation, with additional filtering applied to each diagnostic to reduce mis-classifications. The diagnostics are tested on four different model datasets, ranging from 2.2 km to around 25 km horizontal grid spacing, to explore the impact of spatial resolution on sea breeze identification methods. Based on a range of individual cases, as well as statistics of sea breeze occurrences, we suggest that a method based on moisture frontogenesis may potentially be suitable for sea breeze identification from model data. However, results for individual sea breeze cases indicate that there are difficulties associated with separating the sea breeze from other coastal fronts and circulations. These results have applications for quantifying the effect of sea breezes on human activities, such as for coastal wind energy and the modulation of the urban heat island.

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Andrew Brown, Claire Vincent, and Ewan Short

Status: open (until 09 Jan 2026)

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Andrew Brown, Claire Vincent, and Ewan Short

Model code and software

sea_breeze: v1.1 Andrew Brown et al. https://doi.org/10.5281/zenodo.17220916

andrewbrown31/sea_breeze_analysis: v1.0 Andrew Brown https://doi.org/10.5281/zenodo.17230239

Andrew Brown, Claire Vincent, and Ewan Short

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Short summary
We developed software to identify sea breezes from weather model output, using three different methods, and applied these to four models for a 6-month period over Australia. We tested each method using case studies and statistics of sea breeze occurrences, finding that a method that identifies atmospheric moisture fronts performs well. Some potential errors are demonstrated due to detection of other frontal systems, but this method could be useful for robustly analyzing sea breezes from models.
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