Reconstructing ice phenology of a lake with complex surface cover: a case study of Lake Ulansu during 1941–2023

Abstract

Lake ice phenology plays a critical role in determining the hydrological and biogeochemical dynamics of catchments and regional climates. Lakes with complex shorelines and abundant aquatic vegetation are challenging for retrieving lake ice phenology via remote sensing data, primarily because of mixed pixels containing plants, land, and ice. To address this challenge, a new double-threshold moving t-test (DMTT) algorithm, which uses Scanning Multichannel Microwave Radiometer (SMMR) and Special Sensor Microwave/Imager–Special Sensor Microwave Imager/Sounder (SSM/I–SSMIS) sensor-derived brightness temperature data at a 3.125 km resolution and long-term ERA5 data, was applied to capture the ice phenology of Lake Ulansu from 1979 to 2023. Compared with the previous moving ttest algorithm, the new DMTT algorithm employs air temperature time series to assist in determining abrupt change points and uses two distinct thresholds to calculate the freeze-up start (FUS) and break-up end (BUE) dates. This method effectively improved the detection of ice information for mixed pixels. Furthermore, we extended Lake Ulansu’s ice phenology back to 1941 via a random forest (RF) model. The reconstructed ice phenology from 1941 to 2023 indicated that Lake Ulansu had average FUS and BUE dates of 15 ± 5 November and 25 ± 6 March, respectively, with an average ice cover duration (ICD) of 130 ± 8 d. Over the last 4 decades, the ICD has shortened by an average of 22 d. Air temperature was the primary impact factor, accounting for 56.5 % and 67.3 % of the variations in the FUS and BUE dates, respectively. We reconstructed, for the first time, the longest ice phenology over a large shallow lake with complex surface cover. We argue that DMTT can be effectively applied to retrieve ice phenology for other similar lakes, which has not been fully explored worldwide.