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1. A Machine Learning Correction Model of the Winter Clear-Sky Temperature Bias over the Arctic Sea Ice in Atmospheric Reanalyses

   https://doi.org/10.1175/MWR-D-22-0130.1  

   Zampieri, Lorenzo ; Arduini, Gabriele ; Holland, Marika ; Keeley, Sarah P. E. ; Mogensen, Kristian ; Shupe, Matthew D. ; Tietsche, Steffen ( June 2023 , Monthly Weather Review)

   Atmospheric reanalyses are widely used to estimate the past atmospheric near-surface state over sea ice. They provide boundary conditions for sea ice and ocean numerical simulations and relevant information for studying polar variability and anthropogenic climate change. Previous research revealed the existence of large near-surface temperature biases (mostly warm) over the Arctic sea ice in the current generation of atmospheric reanalyses, which is linked to a poor representation of the snow over the sea ice and the stably stratified boundary layer in the forecast models used to produce the reanalyses. These errors can compromise the employment of reanalysis products in support of polar research. Here, we train a fully connected neural network that learns from remote sensing infrared temperature observations to correct the existing generation of uncoupled atmospheric reanalyses (ERA5, JRA-55) based on a set of sea ice and atmospheric predictors, which are themselves reanalysis products. The advantages of the proposed correction scheme over previous calibration attempts are the consideration of the synoptic weather and cloud state, compatibility of the predictors with the mechanism responsible for the bias, and a self-emerging seasonality and multidecadal trend consistent with the declining sea ice state in the Arctic. The correction leads on average to a 27% temperature bias reduction for ERA5 and 7% for JRA-55 if compared to independent in situ observations from the MOSAiC campaign (respectively, 32% and 10% under clear-sky conditions). These improvements can be beneficial for forced sea ice and ocean simulations, which rely on reanalyses surface fields as boundary conditions.

   This study illustrates a novel method based on machine learning for reducing the systematic surface temperature errors that characterize multiple atmospheric reanalyses in sea ice–covered regions of the Arctic under clear-sky conditions. The correction applied to the temperature field is consistent with the local weather and the sea ice and snow conditions, meaning that it responds to seasonal changes in sea ice cover as well as to its long-term decline due to global warming. The corrected reanalysis temperature can be employed to support polar research activities, and in particular to better simulate the evolution of the interacting sea ice and ocean system within numerical models.

    

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2. Increasing Winter Ocean‐to‐Ice Heat Flux in the Beaufort Gyre Region, Arctic Ocean Over 2006–2018

   https://doi.org/10.1029/2021GL096216  

   Zhong, Wenli ; Cole, Sylvia T. ; Zhang, Jinlun ; Lei, Ruibo ; Steele, Michael ( January 2022 , Geophysical Research Letters)

   Ocean‐to‐ice heat flux (OHF) is important in regulating the variability of sea ice mass balance. Using surface drifting buoy observations, we show that during winter in the Arctic Ocean's Beaufort Gyre region, OHF increased from 0.76 ± 0.05 W/m²over 2006–2012 to 1.63 ± 0.08 W/m²over 2013–2018. We find that this is a result of thinner and less‐compact sea ice that promotes enhanced winter ice growth, stronger ocean vertical convection, and subsurface heat entrainment. In contrast, Ekman upwelling declined over the study period, suggesting it had a secondary contribution to OHF changes. The enhanced ice growth creates a cooler, saltier, and deeper ocean surface mixed layer. In addition, the enhanced vertical temperature gradient near the mixed layer base in later years favors stronger entrainment of subsurface heat. OHF and its increase during 2006–2018 were not geographically uniform, with hot spots found in an upwelling region where ice was most seasonally variable.

    

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3. Spatiotemporal evolution of melt ponds on Arctic sea ice

   https://doi.org/10.1525/elementa.2021.000072  

   Webster, Melinda A. ; Holland, Marika ; Wright, Nicholas C. ; Hendricks, Stefan ; Hutter, Nils ; Itkin, Polona ; Light, Bonnie ; Linhardt, Felix ; Perovich, Donald K. ; Raphael, Ian A. ; et al ( January 2022 , Elementa: Science of the Anthropocene)

   Melt ponds on sea ice play an important role in the Arctic climate system. Their presence alters the partitioning of solar radiation: decreasing reflection, increasing absorption and transmission to the ice and ocean, and enhancing melt. The spatiotemporal properties of melt ponds thus modify ice albedo feedbacks and the mass balance of Arctic sea ice. The Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition presented a valuable opportunity to investigate the seasonal evolution of melt ponds through a rich array of atmosphere-ice-ocean measurements across spatial and temporal scales. In this study, we characterize the seasonal behavior and variability in the snow, surface scattering layer, and melt ponds from spring melt to autumn freeze-up using in situ surveys and auxiliary observations. We compare the results to satellite retrievals and output from two models: the Community Earth System Model (CESM2) and the Marginal Ice Zone Modeling and Assimilation System (MIZMAS). During the melt season, the maximum pond coverage and depth were 21% and 22 ± 13 cm, respectively, with distribution and depth corresponding to surface roughness and ice thickness. Compared to observations, both models overestimate melt pond coverage in summer, with maximum values of approximately 41% (MIZMAS) and 51% (CESM2). This overestimation has important implications for accurately simulating albedo feedbacks. During the observed freeze-up, weather events, including rain on snow, caused high-frequency variability in snow depth, while pond coverage and depth remained relatively constant until continuous freezing ensued. Both models accurately simulate the abrupt cessation of melt ponds during freeze-up, but the dates of freeze-up differ. MIZMAS accurately simulates the observed date of freeze-up, while CESM2 simulates freeze-up one-to-two weeks earlier. This work demonstrates areas that warrant future observation-model synthesis for improving the representation of sea-ice processes and properties, which can aid accurate simulations of albedo feedbacks in a warming climate. 

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4. Freshwater Input and Vertical Mixing in the Canada Basin’s Seasonal Halocline: 1975 versus 2006–12

   https://doi.org/10.1175/JPO-D-21-0116.1  

   Rosenblum, Erica ; Stroeve, Julienne ; Gille, Sarah T. ; Lique, Camille ; Fajber, Robert ; Tremblay, L. Bruno ; Galley, Ryan ; Loureiro, Thiago ; Barber, David G. ; Lukovich, Jennifer V. ( July 2022 , Journal of Physical Oceanography)

   The Arctic seasonal halocline impacts the exchange of heat, energy, and nutrients between the surface and the deeper ocean, and it is changing in response to Arctic sea ice melt over the past several decades. Here, we assess seasonal halocline formation in 1975 and 2006–12 by comparing daily, May–September, salinity profiles collected in the Canada Basin under sea ice. We evaluate differences between the two time periods using a one-dimensional (1D) bulk model to quantify differences in freshwater input and vertical mixing. The 1D metrics indicate that two separate factors contribute similarly to stronger stratification in 2006–12 relative to 1975: 1) larger surface freshwater input and 2) less vertical mixing of that freshwater. The larger freshwater input is mainly important in August–September, consistent with a longer melt season in recent years. The reduced vertical mixing is mainly important from June until mid-August, when similar levels of freshwater input in 1975 and 2006–12 are mixed over a different depth range, resulting in different stratification. These results imply that decadal changes to ice–ocean dynamics, in addition to freshwater input, significantly contribute to the stronger seasonal stratification in 2006–12 relative to 1975. These findings highlight the need for near-surface process studies to elucidate the impact of lateral processes and ice–ocean momentum exchange on vertical mixing. Moreover, the results may provide insight for improving the representation of decadal changes to Arctic upper-ocean stratification in climate models that do not capture decadal changes to vertical mixing.

    

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5. Quantifying false bottoms and under-ice meltwater layers beneath Arctic summer sea ice with fine-scale observations

   https://doi.org/10.1525/elementa.2021.000116  

   Smith, Madison M. ; von Albedyll, Luisa ; Raphael, Ian A. ; Lange, Benjamin A. ; Matero, Ilkka ; Salganik, Evgenii ; Webster, Melinda A. ; Granskog, Mats A. ; Fong, Allison ; Lei, Ruibo ; et al ( January 2022 , Elementa: Science of the Anthropocene)

   During the Arctic melt season, relatively fresh meltwater layers can accumulate under sea ice as a result of snow and ice melt, far from terrestrial freshwater inputs. Such under-ice meltwater layers, sometimes referred to as under-ice melt ponds, have been suggested to play a role in the summer sea ice mass balance both by isolating the sea ice from saltier water below, and by driving formation of ‘false bottoms’ below the sea ice. Such layers form at the interface of the fresher under-ice layer and the colder, saltier seawater below. During the Multidisciplinary drifting Observatory for the Study of the Arctic Climate (MOSAiC) expedition in the Central Arctic, we observed the presence of under-ice meltwater layers and false bottoms throughout July 2020 at primarily first-year ice locations. Here, we examine the distribution, prevalence, and drivers of under-ice ponds and the resulting false bottoms during this period. The average thickness of observed false bottoms and freshwater equivalent of under-ice meltwater layers was 0.08 m, with false bottom ice comprised of 74–87% FYI melt and 13–26% snow melt. Additionally, we explore these results using a 1D model to understand the role of dynamic influences on decoupling the ice from the seawater below. The model comparison suggests that the ice-ocean friction velocity was likely exceptionally low, with implications for air-ice-ocean momentum transfer. Overall, the prevalence of false bottoms was similar to or higher than noted during other observational campaigns, indicating that these features may in fact be common in the Arctic during the melt season. These results have implications for the broader ice-ocean system, as under-ice meltwater layers and false bottoms provide a source of ice growth during the melt season, potentially reduce fluxes between the ice and the ocean, isolate sea ice primary producers from pelagic nutrient sources, and may alter light transmission to the ocean below. 

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