How the growth of ice depends on the fluid dynamics underneath

TL;DR

This study combines experiments, simulations, and theory to understand how water density anomalies and turbulence influence ice growth, revealing four flow regimes and providing a predictive model for ice thickness and growth rate.

Contribution

It introduces a comprehensive model that accounts for water density anomalies and turbulence, accurately predicting ice growth dynamics under various conditions.

Findings

Identified four distinct flow regimes with increasing thermal driving.

Developed a theoretical model capturing average ice thickness and growth rate.

Demonstrated thermal driving's impact on icing duration, from days to hours.

Abstract

Convective flows coupled with solidification or melting in water bodies play a major role in shaping geophysical landscapes. Particularly in relation to the global climate warming scenario, it is essential to be able to accurately quantify how water-body environments dynamically interplay with ice formation or melting process. Previous studies have revealed the complex nature of the icing process, but have often ignored one of the most remarkable particularity of water, its density anomaly, and the induced stratification layers interacting and coupling in a complex way in presence of turbulence and phase change. By combining experiments, numerical simulations, and theoretical modeling, we investigate solidification of freshwater, properly considering phase transition, water density anomaly, and real physical properties of ice and water phases, which we show to be essential for correctly predicting the different qualitative and quantitative behaviors. We identify, with increasing thermal driving, four distinct flow-dynamics regimes, where different levels of coupling among ice front, stably and unstably stratified water layers occur. Despite the complex interaction between the ice front and fluid motions, remarkably, the average ice thickness and growth rate can be well captured with the theoretical model. It is revealed that the thermal driving has major effects on the temporal evolution of the global icing process, which can vary from a few days to a few hours in the current parameter regime. Our model can be applied to general situations where the icing dynamics occurs under different thermal and geometrical conditions (e.g. cooling conditions or water layer depth).