Temperate lake heatwaves accelerate non-linearly as timing synchronizes across a diverse landscape

Temperate lakes are experiencing intensifying heatwaves, or prolonged periods of anomalously warm water, with potentially severe ecological consequences. Previous studies have predominantly used linear trend analyses to understand heatwave dynamics, potentially masking temporal acceleration patterns and shifts in variance. Here, we analyzed long-term, nonlinear trends in heatwave frequency, intensity, and timing across 4391 New York lakes using simulated daily surface water temperatures from an Entity-Aware Long Short-Term Memory deep learning model (validated root mean square error = 1.82°C; 1980–2020). We applied generalized additive mixed models to quantify complex temporal patterns while accounting for lake-specific effects and environmental characteristics (lake surface area, elevation, and latitude). All heatwave metrics demonstrated nonlinear and dynamic temporal trends. Heatwave frequency showed early increases in the number of events (0.05–1.32 events during the 1980s) followed by accelerated growth after 2000; other metrics exhibited more complex decadal patterns. Temporal variance increased significantly for both heatwave frequency (τ = 0.73, p