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Abstract In 2023, the first Polar Postdoc Leadership Workshop convened to discuss present and future polar science issues and to develop leadership skills. The workshop discussions fostered a collective commitment to inclusive leadership within the polar science community among all participants. Here, we outline challenges encountered by underrepresented groups in polar sciences, while also noting that progress has been made to improve inclusivity in the field. Further, we highlight the inclusive leadership principles identified by workshop participants to bring to the polar community as we transition into leadership roles. Finally, insights and practical knowledge we gained from the workshop are shared, aiming to inform the community of our commitment to inclusive leadership and encourage the polar community to join us in pursuing action toward our shared vision for a more welcoming polar science future. 

Abstract Understanding the variability of the Atlantic Meridional Overturning Circulation is essential for better predictions of our changing climate. Here we present an updated time series (August 2014 to June 2020) from the Overturning in the Subpolar North Atlantic Program. The 6-year time series allows us to observe the seasonality of the subpolar overturning and meridional heat and freshwater transports. The overturning peaks in late spring and reaches a minimum in early winter, with a peak-to-trough range of 9.0 Sv. The overturning seasonal timing can be explained by winter transformation and the export of dense water, modulated by a seasonally varying Ekman transport. Furthermore, over 55% of the total meridional freshwater transport variability can be explained by its seasonality, largely owing to overturning dynamics. Our results provide the first observational analysis of seasonality in the subpolar North Atlantic overturning and highlight its important contribution to the total overturning variability observed to date. 

Sea surface salinity (SSS) anomalies and near-surface thermohaline stratification are key parameters to improve our understanding of sea ice retreat and formation in polar regions. Since 2010, the remote sensing salinity missions ESA Soil Moisture Ocean Salinity (SMOS) and NASA Soil Moisture Active Passive (SMAP) offer unprecedented SSS observations globally (SSSSMOS and SSSSMAP, respectively). In this study, we compare these observations with in situ salinity observations (SSSin‐situ) made during the NASA salinity field campaign Salinity and Stratification at Sea Ice Edge (SASSIE) during the fall of 2022. The SASSIE SSSin‐situ were collected by nine different platforms: Castaway and Underway conductivity–temperature–depth (CTD), Wave Gliders, Thermosalinograph, Snake salinity, Surface Wave Instrument Float with Tracking (SWIFT) drifters, Upper Temperature of the Polar Oceans (UpTempO) buoys, Jet Surface Salinity Profiler (Jet-SSP), and Autonomous Lagrangian Thermometric Observer (ALTO) and Air-Launched Autonomous Micro Observer (ALAMO) profilers. Because satellite SSS retrievals are impacted by land and sea ice contaminations, cold temperatures, and surface roughness, mean differences, root-mean-square difference (RMSD), and standard deviation (STD) between satellite SSS and SSSin‐situ are examined as a function of distance from the coast and sea ice edge, sea surface temperature (SST), and wind speed. We find that SSSSMOS and SSSSMAP are well correlated (0.66 and 0.78, respectively) with similar RMSD when compared with SSSin‐situ. Close to the coast (0–150 km), SSSSMAP compares better with SSSin‐situ with RMSD (<2 g kg−1) lower than that from SSSSMOS. Near the sea ice edge (0–150 km), SSSSMOS compares better with SSSin‐situ with RMSD (<2.5 g kg−1) lower than that from SSSSMAP. In cold water (SST < 1.5°C) and low wind speed conditions (<7 m s−1), both SSSSMOS and SSSSMAP are consistent with each other. The RMSD between SSSSMAP and SSSin‐situ decreases considerably (<1 g kg−1) when SST > 1.5°C, while the RMSD between SSSSMOS and SSSin‐situ shows less dependence on SST. 

There are many challenges associated with obtaining high-fidelity sea ice concentration (SIC) information, and products that rely solely on passive microwave measurements often struggle to represent conditions at low concentration, especially within the marginal ice zone and during periods of active melt. Here, we present a newly gridded SIC product for the Alaskan Arctic, generated with data from the National Weather Service Alaska Sea Ice Program (hereafter referred to as ASIP), that synthesizes a variety of satellite SIC and in situ observations from 2007–present. These SIC fields have been primarily used for operational purposes and have not yet been gridded or independently validated. In this study, we first grid the ASIP product into 0.05° resolution in both latitude and longitude (hereafter referred to as gridded ASIP, or grASIP). We then perform extensive intercomparison with an international database of ship-based in situ SIC observations, supplemented with observations from saildrones. Additionally, an intercomparison between three ice products is performed: (i) grASIP, (ii) a high-resolution passive microwave product (AMSR2), and (iii) a product available from the National Snow and Ice Data Center (MASIE) that originates from the US National Ice Center (USNIC) operational IMS product. This intercomparison demonstrates that all products perform similarly when compared to in situ observations generally, but grASIP outperforms the other products during periods of active melt and in low-SIC regions. Furthermore, we show that the similarity in performance among products is partly due to the deficiencies in the in situ observations' geographical distribution, as most in situ observations are far from the ice edge in locations where all products agree. We find that the grASIP ice edge is generally farther south than both the AMSR2 and MASIE ice edges by an average of approximately 50 km in winter and 175 km in summer for grASIP vs. AMSR2 and 10 km in winter and 40 km in summer for grASIP vs. MASIE. 

The National Weather Service Alaska Sea Ice Program (ASIP) produces manually-drawn, high-resolution sea ice maps for the Pacific Arctic. This is done by leveraging all available imagery and observations of sea ice conditions in the preceding 24 hours, prioritized by data quality and latency. These ice maps are published three times per week from 2007 to June 30, 2014, and then daily from July 1, 2014 to the present. The data follow World Meteorological Organization standard for ice charts, meaning the shapefiles are published in SIGRID-3 vector archive format and published charts are in standard color code. Within these shapefiles, the source data are expressed as a series of polygons, each with an ice concentration range. Here, we compute the average ice concentration within each polygon, as well as the range. These data are then projected onto a 0.05 degree grid in latitude and longitude. Ultimately, this results in gridded maps of sea ice concentration for each day of available data.