Jennifer King

Leads in Arctic pack ice enable early phytoplankton blooms below snow-covered sea ice

The Arctic icescape is rapidly transforming from a thicker multiyear ice cover to a thinner and largely seasonal first-year ice cover with significant consequences for Arctic primary production. One critical challenge is to understand how productivity will change within the next decades. Recent studies have reported extensive phytoplankton blooms beneath ponded sea ice during summer, indicating that satellite-based Arctic annual primary production estimates may be significantly underestimated. Here we present a unique time-series of a phytoplankton spring bloom observed beneath snow-covered Arctic pack ice. The bloom, dominated by the haptophyte algae Phaeocystis pouchetii, caused near depletion of the surface nitrate inventory and a decline in dissolved inorganic carbon by 16 ± 6 g C m−2. Ocean circulation characteristics in the area indicated that the bloom developed in situ despite the snow-covered sea ice. Leads in the dynamic ice cover provided added sunlight necessary to initiate and sustain the bloom. Phytoplankton blooms beneath snow-covered ice might become more common and widespread in the future Arctic Ocean with frequent lead formation due to thinner and more dynamic sea ice despite projected increases in high-Arctic snowfall. This could alter productivity, marine food webs and carbon sequestration in the Arctic Ocean.

Combined observations of Arctic sea ice with near‐coincident colocated X‐band, C‐band, and L‐band SAR satellite remote sensing and helicopter‐borne measurements

In this study, we compare colocated near-coincident X-, C-, and L-band fully polarimetry SAR satellite images with helicopter-borne ice thickness measurements acquired during the Norwegian Young sea ICE 2015 (N-ICE2015) expedition in the region of the Arctic Ocean north of Svalbard in April 2015. The air-borne surveys provide near-coincident snow plus ice thickness, surface roughness data, and photographs. This unique data set allows us to investigate how the different frequencies can complement one another for sea ice studies, but also to raise awareness of limitations. X-band and L-band satellite scenes were shown to be a useful complement to the standard SAR frequency for sea ice monitoring (C-band) for lead ice and newly formed sea ice identification. This may be in part be due to the frequency but also the high spatial resolution of these sensors. We found a relatively low correlation between snow plus ice thickness and surface roughness. Therefore, in our dataset ice thickness cannot directly be observed by SAR which has important implications for operational ice charting based on automatic segmentation.

Sea-ice thickness from field measurements in the northwestern Barents Sea

The Barents Sea is one of the fastest changing regions of the Arctic, and has experienced the strongest decline in winter-time sea-ice area in the Arctic, at -23 +/- 4% per decade. Sea-ice thickness in the Barents Sea is not well studied. We present two previously unpublished helicopter-borne electromagnetic (HEM) ice thickness measurements from the northwestern Barents Sea acquired in March 2003 and 2014. The HEM data are compared to ice thickness calculated from ice draft measured by ULS deployed between 1994 and 1996. These data show that ice thickness varies greatly from year to year; influenced by the thermodynamic and dynamic processes that govern local formation vs long-range advection. In a year with a large inflow of sea-ice from the Arctic Basin, the Barents Sea ice cover is dominated by thick multiyear ice; as was the case in 2003 and 1995. In a year with an ice cover that was mainly grown in situ, the ice will be thin and mechanically unstable; as was the case in 2014. The HEM data allow us to explore the spatial and temporal variability in ice thickness. In 2003 the dominant ice class was more than 2 years old; and modal sea-ice thickness varied regionally from 0.6 to 1.4 m, with the thinner ice being either first-year ice, or multiyear ice which had come into contact with warm Atlantic water. In 2014 the ice cover was predominantly locally grown ice less than 1 month old (regional modes of 0.5–0.8 m). These two situations represent two extremes of a range of possible ice thickness distributions that can present very different conditions for shipping traffic; or have a different impact on heat transport from ocean to atmosphere.

Comparison of Freeboard Retrieval and Ice Thickness Calculation From ALS, ASIRAS, and CryoSat‐2 in the Norwegian Arctic to Field Measurements Made During the N‐ICE2015 Expedition

We present freeboard measurements from airborne laser scanner (ALS), the Airborne Synthetic Aperture and Interferometric Radar Altimeter System (ASIRAS), and CryoSat-2 SIRAL radar altimeter; ice thickness measurements from both helicopter-borne and ground-based electromagnetic-sounding; and point measurements of ice properties. This case study was carried out in April 2015 during the N-ICE2015 expedition in the area of the Arctic Ocean north of Svalbard. The region is represented by deep snow up to 1.12 m and a widespread presence of negative freeboards. The main scattering surfaces from both CryoSat-2 and ASIRAS are shown to be closer to the snow freeboard obtained by ALS than to the ice freeboard measured in situ. This case study documents the complexity of freeboard retrievals from radar altimetry. We show that even under cold (below −15°C) conditions the radar freeboard can be close to the snow freeboard on a regional scale of tens of kilometers. We derived a modal sea-ice thickness for the study region from CryoSat-2 of 3.9 m compared to measured total thickness 1.7 m, resulting in an overestimation of sea-ice thickness on the order of a factor 2. Our results also highlight the importance of year-to-year regional scale information about the depth and density of the snowpack, as this influences the sea-ice freeboard, the radar penetration, and is a key component of the hydrostatic balance equations used to convert radar freeboard to sea-ice thickness.

Can we extend local sea-ice measurements to satellite scale? An example from the N-ICE2015 expedition

ABSTRACT Knowledge of Arctic sea-ice conditions is of great interest for Arctic residents, as well as for commercial usage, and to study the effects of climate change. Information gained from analysis of satellite data contributes to this understanding. In the course of using in situ data in combination with remotely sensed data, the question of how representative local scale measurements are of a wider region may arise. We compare in situ total sea-ice thickness measurements from the Norwegian young sea ICE expedition in the area north of Svalbard with airborne-derived total sea-ice thickness from electromagnetic soundings. A segmented and classified synthetic aperture radar (SAR) quad-pol ALOS-2 Palsar-2 satellite scene was grouped into three simplified ice classes. The area fractions of the three classes are: 11.2% ‘thin’, 74.4% ‘level’, and 14.4% ‘deformed’. The area fractions of the simplified classes from ground- and helicopter-based measurements are comparable with those achieved from the SAR data. Thus, this study shows that there is potential for a stepwise upscaling from in situ, to airborne, to satellite data, which allow us to assess whether in situ data collected are representative of a wider region as observed by satellites.

Does Your Lab Use Social Media?: Sharing Three Years of Experience in Science Communication

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.