Multi-sensor satellite analysis reveals latitudinal and morphometric controls on ice phenology across 31 000 lakes on the Alaska North Slope

Thermokarst lakes are critical components of Arctic carbon cycling, yet their ice phenology remains poorly characterized at regional scales. We present the first comprehensive analysis of ice-on and ice-off timing across 30 774 lakes on the Alaska North Slope using Sentinel-1 synthetic aperture radar (SAR) classified by a Random Forest (RF) model trained using labels derived from Sentinel-2 optical imagery and ERA5 temperature data for the period 2019–2023. Our RF classifier achieved 94 % accuracy for ice state detection, enabling phenology retrieval for 97 % of lake-years. Results revealed a mean ice-free period of 114 d (standard deviation = 25 d), with ice-off occurring at day-of-year 159 (8 June) and ice-on at day-of-year 273 (30 September). Spatial analysis demonstrated strong latitudinal control on ice phenology, with ice-free duration decreasing by 23 d per degree northward. Lake morphology (area, circularity, convexity, and shoreline development index) showed modest but significant effects on ice timing after controlling for latitude effects, with shoreline development index and convexity each contributing ∼ 3 d variation across typical lake ranges. Comparison of the RF model and simplistic accumulated degree-day (ADD) model-detected ice phenology yielded a convincing match, where the offsets in ice phenology between the models fell within twice the per-detection observation gap for approximately 80 % of the lakes. Furthermore, these offsets exhibited the same strong latitudinal control and negligible effects of lake morphology. These lake-specific phenology dates provide timing and duration constraints for future methane studies using high-resolution sensors and provide baseline phenology data essential for understanding how continued Arctic warming will affect thermokarst lake dynamics and associated carbon cycle feedbacks.