| 19 Jan 2026
LI-CCR: Dataset of daily lake ice evolution (2002–2024) across global cold climate regions based on gap-filled MODIS observations
Abstract. Lake ice is an essential component of the terrestrial cryosphere and plays an important role in the socioeconomic and ecological systems of cold regions. However, existing lake ice datasets generally suffer from poor temporal continuity, limited spatial coverage, and a lack of observations for small and medium-sized lakes. Consequently, the global spatial patterns and long-term trends of lake ice have remained insufficiently understood. In this study, using MODIS observations, we developed global datasets of daily lake ice coverage (LIC), annual lake ice-cover status, annual lake ice phenology (LIP), and the probability of complete ice-cover occurrence (PCIO), including 32,800 lakes across global cold climate regions from 2002 through 2024. Validation against multiple remote sensing datasets demonstrated high accuracy and confirmed that our Lake Ice – Cold Climate Regions dataset (LI-CCR) effectively captures the spatiotemporal evolution of the lake ice zone. Quality assessments were conducted for both LIC and LIP, and the information was included as an integral component of the LI-CCR. The results show that most cold regions lakes in the Northern (Southern) Hemisphere freeze before November (May) and melt from May (November) onward, with an average ice cover duration of about 200 days. Presently 89 % of the lakes experience completely frozen annually, and the number of intermittent or even ice-free lakes is increasing under the warming climate. The LI-CCR dataset provides comprehensive records of lake ice evolution in cold climate regions and offers valuable information for studies on lake–climate interactions, cryosphere changes, and ecosystem responses. This LI-CCR dataset v2 is freely available from the Zenodo platform at https://doi.org/10.5281/zenodo.17687698 (Jiang et al., 2025b).
General comments:
The manuscript presents a global dataset, LI-CCR, of daily lake ice coverage (LIC), annual ice status, lake ice phenology (LIP), and the probability of complete ice-cover occurrence (PCIO) for 32,800 lakes across cold-climate regions from 2002 to 2024. Given that lake ice is recognized as an Essential Climate Variable (ECV), this long-term, high-frequency dataset improves the representation of small and medium-sized lakes. The manuscript is generally well organized and clearly written. I only have a few minor comments related to the discussion of uncertainties and the potential future applications of the dataset.
Specific comments:
1. The validation section could further illustrate how lake size influences the performance and uncertainty of different observation methods. For example, methods such as passive remote sensing may show larger uncertainties for small lakes, as noted in the Introduction.
2. The discussion could mention potential biases related to wind speed, which may influence ice formation and/or breakup processes and remote-sensing detection during transitional periods.
3. It would be helpful to further expand the discussion on potential future applications of this dataset, such as its use in climate studies, lake modeling, and lake-atmosphere interaction research.
Technical corrections:
-Line 26: The link of dataset might contain an extra space that should be removed.
-Line 83: It might be helpful to specify the area range of the 32,800 lakes (e.g., >2 km2).
-Line 310: "PICO" should be corrected to "PCIO".
-Eq. (3): "Nremove" should be corrected to "Nremoved".
-Fig. 6 caption: A ":" is missing after “Figure 6”.