A novel algorithm for detecting lake-breeze fronts at Lake Victoria using station observations

Lake Victoria (LV), the world’s largest tropical lake, significantly influences East Africa’s regional climate through diurnally varying lake–land-breeze circulations. In particular, lake-breeze fronts (LBFs) often trigger cloudiness, deep moist convection, and heavy precipitation, leading to weather-related hazards. To systematically study LBFs over LV, we developed an observation-based lake-breeze detection algorithm (OLBDA), which objectively identifies LBF passages using 15-min data from 45 automatic weather stations across Uganda’s extended coastal region over 6 years (2017–22). Focusing on daytime (0900–1900 LT) during dry months (December–February and June–August), the algorithm applies thresholds based on the lowest (highest) 30% of temperature drops (dewpoint and wind speed increases), enabling detection of subtle meteorological changes associated with LBF passage. Validation against visible satellite imagery shows strong performance with high accuracy (ACC = 0.76), detection rate [probability of detection (POD) > 0.7], and low false alarms [probability of false alarm (POFA) = 0.2]. Application of the OLBDA revealed that LBFs predominantly occur from early afternoon to evening, peaking at 1300 LT near the coast and shifting inland with distance. LBFs were observed on 48% of days, with December–February and January having the highest seasonal and monthly frequencies, respectively. LBF propagation speed varied in relation to the background wind in different hinterland sectors of LV, with the fastest movement westward at 8 m s⁻¹ and the slowest northward at 5.8 m s⁻¹. LBFs penetrate up to ∼130 km inland. The OLBDA offers a robust framework for analyzing LBFs, providing valuable insights for disaster preparedness and climate mitigation in the Lake Victoria basin.