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Arctic ecosystems are affected by accelerated warming as well as the intensification of the hydrologic cycle, yet understanding of the impacts of compound climate extremes (e.g., simultaneous extreme heat and rainfall) remains limited, despite their high potential to alter ecosystems. Here, we show that the aquatic ecosystems in historically arid West Greenland have undergone an ecological transformation after a series of atmospheric rivers that simultaneously produced record heat and rainfall hit the region in autumn 2022. We analyzed a unique, long-term lake dataset and found that compound climate extremes pushed Arctic lakes across a tipping point. As terrestrial–aquatic linkages were strengthened, lakes synchronously transformed from “blue” lakes with high transparency and low pelagic primary production to “brown” in less than a year, owing to a large influx of dissolved organic material and metals, with iron concentrations increasing by more than two orders of magnitude. The browning of lake waters reduced light penetration by 50% across lakes. The resulting light limitation altered plankton distributions and community structure, including a major reduction in prokaryotic diversity and an increase in algal groups capable of metabolizing organic carbon sources. As a result, lakes shifted from being summer carbon sinks to sources, with a >350% increase in carbon dioxide flux from lakes to the atmosphere. The remarkably rapid, coherent transformation of these Arctic ecosystems underscores the synergistic and unpredictable impacts of compound extreme events and the importance of their seasonal timing, especially in regions with negative moisture balance. 

Satellites have provided high-resolution ( < 100 m) water color (i.e., remote sensing reflectance) and thermal emission imagery of aquatic environments since the early 1980s; however, global operational water quality products based on these data are not readily available (e.g., temperature, chlorophyll- a , turbidity, and suspended particle matter). Currently, because of the postprocessing required, only users with expressive experience can exploit these data, limiting their utility. Here, we provide paths (recipes) for the nonspecialist to access and derive water quality products, along with examples of applications, from sensors on board Landsat-5, Landsat-7, Landsat-8, Landsat-9, Sentinel-2A, and Sentinel-2B. We emphasize that the only assured metric for success in product derivation and the assigning of uncertainties to them is via validation with in situ data. We hope that this contribution will motivate nonspecialists to use publicly available high-resolution satellite data to study new processes and monitor a variety of novel environments that have received little attention to date. 

Aquaculture of the eastern oyster, Crassostrea virginica , is an expanding industry in the US, particularly in the Gulf of Maine. High resolution ocean color satellites launched in the last decade potentially provide aquaculture-relevant water-quality parameters at farm scales. However, these parameters, such as temperature, suspended particulate matter (SPM), and Chlorophyll a (Chl a), need to be derived by interested users. Water quality parameters are derived first by applying an atmospheric correction and then estimating the target parameter with a specific algorithm. Here, we use five atmospheric correction schemes and two algorithms to derive SPM and Chl a from the Sentinel 2A&B satellites’ multispectral instrument data. The best estimates of SPM and Chl a are determined by comparison with in situ observations from buoys. Together with SST from Landsat-8, we estimated an Oyster Suitability Index (OSI) along the transects in five estuaries in the Gulf of Maine as well as applied a novel particulate organic matter algorithm, a function of Chl a and SPM in low turbidity estuaries. We then apply the optimal approaches to derive water quality parameters to study five different estuaries in Maine and find that existing high-yield oyster aquaculture farms are found in areas with elevated OSI values. Additionally, we suggest new areas, currently under-exploited, where oyster aquaculture is likely to succeed, showcasing the utility of the approach.