Preprints
https://doi.org/10.5194/egusphere-2025-1817
https://doi.org/10.5194/egusphere-2025-1817
19 Jun 2025
 | 19 Jun 2025
Status: this preprint is open for discussion and under review for The Cryosphere (TC).

Stochastic Modelling of Thermokarst Lakes: Size Distributions and Dynamic Regimes

Constanze Reinken, Victor Brovkin, Philipp de Vrese, Ingmar Nitze, Helena Bergstedt, and Guido Grosse

Abstract. Thermokarst lakes are among the most common and dynamic landscape features in ice-rich permafrost lowland regions. They influence carbon, water and energy fluxes between atmosphere and land surface and are an important component of Arctic lowland hydrology. Despite their significant role in the climate system, thermokarst lakes are only rudimentarily or not at all represented in Earth system models (ESMs). Attempts at stand-alone modelling of their dynamics have mostly been limited to the scale of individual lakes. Because lake formation, expansion, and drainage depend on small-scale surface and subsurface heterogeneities that are difficult to measure, a deterministic modelling-approach would be a challenge at the regional or pan-Arctic scale. We therefore treat these processes as probabilistic across a landscape and create a model of thermokarst lake dynamics using stochastic approaches. With the inclusion of stochasticity and volatility, our method allows us to account for the diversity of individual lake behaviour that results from the small-scale differences in environmental conditions. We present idealized simulations and, additionally, test novel high-resolution remote sensing data products that capture annual lake areas for model initialization and the calibration of inherent or climate-induced lake dynamics. Our model is able to capture three plausible regimes by incorporating the main processes behind thermokarst lake dynamics and represents a new step towards stochastic representation of permafrost landscapes in ESMs. Furthermore, our findings emphasize the importance of continued remote sensing data retrieval and additional data products containing information on past thermokarst lake behaviour for model parameterization.

Competing interests: At least one of the (co-)authors is a member of the editorial board of The Cryosphere.

Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims made in the text, published maps, institutional affiliations, or any other geographical representation in this preprint. The responsibility to include appropriate place names lies with the authors.
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Constanze Reinken, Victor Brovkin, Philipp de Vrese, Ingmar Nitze, Helena Bergstedt, and Guido Grosse

Status: open (until 31 Jul 2025)

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Constanze Reinken, Victor Brovkin, Philipp de Vrese, Ingmar Nitze, Helena Bergstedt, and Guido Grosse

Data sets

Surface water data: Supplementary Dataset used in: Reinken et al.: Stochastic Modelling of Thermokarst Lakes: Size Distributions and Dynamic Regimes Ingmar Nitze, Todd Nicholson https://doi.org/10.5281/zenodo.15011121

Model code and software

Thermokarst Lake Model (TLM) Constanze Reinken https://github.com/cowniflow/TLM

Constanze Reinken, Victor Brovkin, Philipp de Vrese, Ingmar Nitze, Helena Bergstedt, and Guido Grosse

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Short summary
Thermokarst lakes are dynamic features of ice-rich permafrost landscapes, altering energy, water and carbon cycles, but have so far mostly been modeled on site-level scale. A deterministic modelling approach would be challenging on larger scales due to the lack of extensive high-resolution data of sub-surface conditions. We therefore develop a conceptual stochastic model of thermokarst lake dynamics that treats the involved processes as probabilistic.
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