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Abstract The rate of technological innovation within aquatic sciences outpaces the collective ability of individual scientists within the field to make appropriate use of those technologies. The process of in situ lake sampling remains the primary choice to comprehensively understand an aquatic ecosystem at local scales; however, the impact of climate change on lakes necessitates the rapid advancement of understanding and the incorporation of lakes on both landscape and global scales. Three fields driving innovation within winter limnology that we address here are autonomous real‐time in situ monitoring, remote sensing, and modeling. The recent progress in low‐power in situ sensing and data telemetry allows continuous tracing of under‐ice processes in selected lakes as well as the development of global lake observational networks. Remote sensing offers consistent monitoring of numerous systems, allowing limnologists to ask certain questions across large scales. Models are advancing and historically come in different types (process‐based or statistical data‐driven), with the recent technological advancements and integration of machine learning and hybrid process‐based/statistical models. Lake ice modeling enhances our understanding of lake dynamics and allows for projections under future climate warming scenarios. To encourage the merging of technological innovation within limnological research of the less‐studied winter period, we have accumulated both essential details on the history and uses of contemporary sampling, remote sensing, and modeling techniques. We crafted 100 questions in the field of winter limnology that aim to facilitate the cross‐pollination of intensive and extensive modes of study to broaden knowledge of the winter period. 

Abstract Lakes play a significant role in the global carbon cycle, acting as sources and sinks of carbon dioxide (CO₂). In situ measurements of CO₂flux (FCO₂) from lakes have generally been collected during daylight, despite indications of significant diel variability. This introduces bias when scaling up to whole‐lake annual aquatic carbon budgets. We conducted an international sampling program to ascertain the extent of diel variation in FCO₂across lakes. We sampled 21 lakes over 41 campaigns and measured FCO₂at 4‐h intervals over a full diel cycle. Rates of FCO₂ranged from −3.16 to 4.39 mmol m⁻² h⁻¹. Integrated over a day, FCO₂ranged from −381.68 to 878.49 mg C m⁻²d⁻¹(mean = 76.54) across campaigns. We identified three characteristic diel patterns in FCO₂related to trophic status and show that for half of the campaigns, daily flux estimates were biased by > 50% if based on a single (daytime) measurement.