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Robert M. Graham, Lana Cohen, Nicole Ritzhaupt, Benjamin Segger, Rune G. Graversen, Annette Rinke, Von P. Walden, Mats A. Granskog, and Stephen R. Hudson


This study evaluates the performance of six atmospheric reanalyses (ERA-Interim, ERA5, JRA-55, CFSv2, MERRA-2, and ASRv2) over Arctic sea ice from winter to early summer. The reanalyses are evaluated using observations from the Norwegian Young Sea Ice campaign (N-ICE2015), a 5-month ice drift in pack ice north of Svalbard. N-ICE2015 observations include surface meteorology, vertical profiles from radiosondes, as well as radiative and turbulent heat fluxes. The reanalyses simulate surface analysis variables well throughout the campaign, but have difficulties with most forecast variables. Wintertime (January–March) correlation coefficients between the reanalyses and observations are above 0.90 for the surface pressure, 2-m temperature, total column water vapor, and downward longwave flux. However, all reanalyses have a positive wintertime 2-m temperature bias, ranging from 1° to 4°C, and negative (i.e., upward) net longwave bias of 3–19 W m−2. These biases are associated with poorly represented surface inversions and are largest during cold-stable periods. Notably, the recent ERA5 and ASRv2 datasets have some of the largest temperature and net longwave biases, respectively. During spring (April–May), reanalyses fail to simulate observed persistent cloud layers. Therefore they overestimate the net shortwave flux (5–79 W m−2) and underestimate the net longwave flux (8–38 W m−2). Promisingly, ERA5 provides the best estimates of downward radiative fluxes in spring and summer, suggesting improved forecasting of Arctic cloud cover. All reanalyses exhibit large negative (upward) residual heat flux biases during winter, and positive (downward) biases during summer. Turbulent heat fluxes over sea ice are simulated poorly in all seasons.

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A. K. Pavlov, A. Meyer, A. Rösel, L. Cohen, J. King, P. Itkin, J. Negrel, S. Gerland, S. R. Hudson, P. A. Dodd, L. de Steur, S. Mathisen, N. Cobbing, and M. A. Granskog


Effective science communication is essential to share knowledge and recruit the next generation of researchers. Science communication to the general public can, however, be hampered by limited resources and a lack of incentives in the academic environment. Various social media platforms have recently emerged, providing free and simple science communication tools to reach the public and young people especially, an audience often missed by more conventional outreach initiatives. While individual researchers and large institutions are present on social media, smaller research groups are underrepresented. As a small group of oceanographers, sea ice scientists, and atmospheric scientists at the Norwegian Polar Institute, we share our experience establishing, developing, and maintaining a successful Arctic science communication initiative (@oceanseaicenpi) on Instagram, Twitter, and Facebook. The initiative is run entirely by a team of researchers with limited time and financial resources. It has built a broad audience of more than 7,000 followers, half of which is associated with the team’s Instagram account. To our knowledge, @oceanseaicenpi is one of the most successful Earth sciences Instagram accounts managed by researchers. The initiative has boosted the alternative metric scores of our publications and helped participating researchers become better writers and communicators. We hope to inspire and help other research groups by providing some guidelines on how to develop and conduct effective science communication via social media.

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