Sea Ice Nonlinearities Act to Rectify and Filter Oceanic and Atmospheric Forcing

Aug 8, 2025·
Richaud, B.
,
Dowd, M.
Christoph Renkl
Christoph Renkl
,
Oliver, E.C.J.
· 3 min read
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Abstract
Offshore wind farms may induce changes in the upper ocean and near-surface atmosphere through coupled ocean-atmosphere feedbacks. Yet, the role of air-sea interactions mediated by offshore wind farms remains poorly understood. Using fully coupled ocean-atmosphere-wave model simulations for seasonally stratified conditions along the US East Coast, we show that simulated cumulative reductions in wind stress due to large-scale wind farm clusters lead to sea surface warming of 0.3° to 0.4°C and a shallower mixed layer. This warming drives upward heat fluxes, destabilizing the atmospheric boundary layer and enhancing wind stress, which partially offsets wake-induced wind deficits. These wake-ocean interactions influence near-surface meteorology and air-sea fluxes, suggesting that a coupled modeling approach may be necessary for assessing potential oceanographic impacts of offshore wind developments. However, ocean coupling exerts limited influence on winds at turbine-relevant heights or within downstream wakes, resulting in minimal impact on long-term energy. These findings suggest that models without ocean coupling may be adequate for wind energy applications.
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Journal of Climate, 28(17), 4573–4588
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publication: “Journal of Climate 38(17), 4573–4588. https://doi.org/10.1175/JCLI-D-24-0485.1" publication_short: "”

abstract: The nonlinearities controlling sea ice thermodynamics integrate forcing from the ocean and atmosphere in surprising ways, rendering it difficult to understand the processes affecting sea ice response to climate change. In this study, a simple ice thickness model is forced by realistic stochastic atmospheric and oceanic heat fluxes. Ensemble experiments show that the nonlinearities in the system rectify the added zero-mean noise on weather time scales leading to a change in the mean sea ice state. Most notably, there is a thinning in summer when sea ice is already at its minimum. The sea ice system integrates high-frequency forcing to influence longer time scales, thus changing not only the mean state but also the interannual-to-decadal variability of sea ice. Adding a trend to the forcing variables yields estimates of the dominant drivers of the current and future ice loss in the Arctic, with a prevalent role of ice–ocean heat flux over surface heat fluxes. This study reveals sea ice as a fundamental climate component, absorbing the energy into its mean state and transforming weather fluctuations with time scales of days to weeks into internal variability on time scales of months to decades. Significance Statement Understanding how sea ice responds to changes in the Arctic climate is crucial to predict its future. Using a simple model, ice thickness is shown to react in unexpected ways to small changes in atmospheric and oceanic conditions. Sea ice absorbs parts of those changes to modify its average thickness and transforms short-term weather fluctuations (lasting days to weeks) into longer-term changes in ice thickness (lasting months to decades). When it comes to Arctic warming, trends in the atmosphere and ocean have different impacts on the ice melt. The ocean plays a bigger role in determining when a seasonally ice-free Arctic will occur. This study emphasizes that sea ice is a key part of the climate system.

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Christoph Renkl
Authors
Christoph Renkl
Regional Weather and
Climate Modeling Group

I am a climate scientist with background in atmospheric science and physical oceanography. My research focuses on interactions of the atmosphere, ocean, and cryosphere within climate as an integrated system. The overarching goal of my research is to better understand the role of air-sea-ice interactions and their teleconnections in weather and climate variability across a range of spatial and temporal scales. I am particularly interested in combining coupled numerical models and observations using a variety of statistical tools to improve our understanding of the climate system, including questions of predictability, longterm trends, and extreme events.

Currently, I am a Deputy Professor in Meteorology at the University of Bonn where I am leading the research group Regional Weather and Climate Modeling.