50 years of lake ice research from active microwave remote sensing: Progress and prospects

Abstract

Lake ice is an important feature of the physical landscape at northern latitudes. Not only does the presence of lake ice help modulate weather and climate but it also plays an important role in travel between northern communities. Furthermore, the thickness of ice cover can impact overwintering fish habitat and access to fresh water during winter months. Lake ice cover and lake ice thickness are two notable climate proxies identified by the Global Climate Observing System (GCOS) as Essential Climate Variables (ECVs). Changes in ice thickness can impact lakes freezing to bed which in turn affect permafrost thaw while longer periods of open water can impact heat transfer to the atmosphere. With recent climate warming in the Northern Hemisphere, there are general trends towards thinner ice and an increase in the length of the open water season. However, the paucity of in-situ observations in many countries has led to remote sensing playing an ever-increasing role for lake ice monitoring. This paper reviews progress in lake ice research conducted using active microwave remote sensing over the last 50 years and highlights areas where future developments are needed. Analysis of the literature found that the diversity of study areas where this work is taking place has increased, incorporating more lake sites from the mid-latitudes in North America, Europe, and Asia. Additionally, clear connections can be made between the launch of synthetic aperture radar (SAR) satellites and patterns in the use of certain radar frequencies in scientific studies. This review also discusses evolving theories concerning the scattering mechanisms associated with lake ice as well as the current state of lake ice cover and ice thickness retrieval methods. The paper concludes with a suite of recommendations for future research, highlighting work that is needed on: 1) advancing our understanding of the response of active microwave signals to lake ice properties; 2) applying machine learning algorithms to lake ice classification; 3) further exploring the retrieval of ice thickness from imaging SAR and radar altimetry data; and 4) other considerations such as data availability and the topic of snow on lake ice.