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Greenland's peripheral glaciers are losing mass at an accelerated rate and are contributing significantly to sea level rise, but only a few direct observations are available. In this study, we use the unique combination of high-resolution remote sensing data and direct mass balance observations to quantify the contribution of a singular avalanche event to the mass balance of Freya Glacier (74.38° N, 20.82° W), a small (5.5 km2, 2021) mountain glacier in Northeast Greenland. Elevation changes calculated from repeated photogrammetric surveys in August 2013 and July 2021 show a high spatial variability, ranging from −11 to 18 m, with a glacier-wide mean of 1.56 ± 0.10 m (1.33 ± 0.21 m w.e.). After applying a seasonal correction of −0.6 ± 0.05 m w.e., the geodetic mass balance over the entire 8-year period (2013–2014 to 2020–2021) is found to be 0.73 ± 0.22 m w.e. A significant influence over the near-decadal mass balance stems from the exceptional winter mass balance of 2017–2018, which was 2.5 standard deviations above average (1.89 ± 0.05 m w.e.). After heavy snowfall in mid-February 2018, snow avalanches from the surrounding slopes affected more than one-third of the glacier surface and contributed 0.35 ± 0.04 m w.e., which is close to 20 % of the total winter mass balance of 2017–2018. Remote sensing data show that Freya Glacier is also prone to avalanches in other years but to a lesser spatial extent. Due to a gap in mass balance point observations caused by high accumulation rates (buried stakes) and the COVID-19 pandemic, the recently reported glacier-wide annual mass balances are rather crude estimates and show a negative bias of −0.22 m w.e. a−1 compared to the geodetic mass balance. Finally, we speculate that the projected future warming may increase the likelihood of extreme snowfall, thus potentially increasing the contribution of snow avalanches to the mass balance of mountain glaciers in Northeast Greenland.

The negative surface mass balance of glaciers and ice caps under a warming climate impacts local ecosystems, influencing the volume and timing of water flow in local catchments while also contributing to global sea level rise. Peripheral glaciers distinct to the Greenland ice sheet respond faster to climate change than the main ice sheet. Accurate assessment of surface mass balance depends on in situ observations of near-surface climate and ice ablation, but very few in situ observations of near-surface climate and ice ablation are freely available for Greenland's peripheral glaciers. The transect of three automated weather and ablation stations on the peripheral A. P. Olsen Ice Cap in northeast Greenland is an example of these much needed data. The transect has been monitored since 2008, and in 2022, the old weather and ablation stations were replaced by a new standardized setup. In order to ensure comparable data quality of the old and new monitoring station setups, it is necessary to re-evaluate the data collected between 2008 and 2022. This paper presents the fully reprocessed near-surface climate and ablation data from the A. P. Olsen Ice Cap transect from 2008 to 2022, with a focus on data quality and the usability in ice ablation process studies. The usability of the data is exemplified by the data in an energy balance melt model for two different years. We show that the inherent uncertainties in the data result in an accurate reproduction of ice ablation for just one of the two years. A transect of three automatic ablation and weather stations of this length is unique to Greenland's peripheral glaciers, and it has a broad scale of usage from input to climate reanalysis and detailed surface ablation studies. The dataset can be downloaded at https://doi.org/10.22008/FK2/X9X9GN (Larsen and Citterio, 2023).

Geometric effects induced by the underlying terrain slope or by tilt errors of the radiation sensors lead to an erroneous measurement of snow or ice albedo. Consequently, artificial diurnal albedo variations in the order of 1–20 % are observed. The present paper proposes a general method to correct tilt errors of albedo measurements in cases where tilts of both the sensors and the slopes are not accurately measured or known. We demonstrate that atmospheric parameters for this correction model can either be taken from a nearby well-maintained and horizontally levelled measurement of global radiation or alternatively from a solar radiation model. In a next step the model is fitted to the measured data to determine tilts and directions of sensors and the underlying terrain slope. This then allows us to correct the measured albedo, the radiative balance and the energy balance. Depending on the direction of the slope and the sensors a comparison between measured and corrected albedo values reveals obvious over- or underestimations of albedo. It is also demonstrated that differences between measured and corrected albedo are generally highest for large solar zenith angles.

A mesocosm experiment was conducted to evaluate the influence of photosynthetic performance on the energetic balance of coastal phytoplankton, in relation to community production and autotrophic phytoplankton biomass in future coastal oceans. Natural phytoplankton assemblages were incubated in field mesocosms under ambient condition (control: ca. 400 μatm CO2 and ambient temperature), and two sets of potential future ocean conditions (acidification: ca. 900 μatm CO2 and ambient temperature; greenhouse: ca. 900 μatm CO2 and 3 °C warmer). The photosynthetic performances were estimated by in vivo fluorometry (effective quantum yield (ΦPSII), steady-state light response curves (LCs)) and in situ incorporation of 14C (photosynthesis-irradiance curves). The ΦPSII and rETRm,LC (relative maximum electron transport rate) clearly reduced under acidification, in particular, when phytoplankton were exposed to high light levels. However, PBmax (maximum photosynthetic rate) was the same in the ambient and acidification conditions. Thus, phytoplankton utilized less light under acidification condition, but could still assimilate a similar amount of carbon compared to the ambient condition. The PBmax and α (photosynthetic efficiency) under greenhouse condition were significantly higher than those under ambient condition without any difference in ΦPSII, rETRm,LC and α,LC (electron transport efficiency) between the treatments. Therefore, phytoplankton utilized the same amount of light under greenhouse condition, but could assimilate more carbon than under ambient condition. As a result, Chl a normalized primary production was higher in greenhouse than in other conditions. Nevertheless, the community production did not change between the experimental treatments. The main reason for the lack of a change in primary production under future climate conditions is the control of autotrophic phytoplankton biomass by grazing. Consequently, acidification and greenhouse environments have a potential to increase growth and primary production of phytoplankton by enhancing inorganic carbon assimilation efficiency when top-down regulation is negligible.

Glacier-wide mass balance has been measured for more than sixty years and is widely used as an indicator of climate change and to assess the glacier contribution to runoff and sea level rise. Until recently, comprehensive uncertainty assessments have rarely been carried out and mass balance data have often been applied using rough error estimation or without consideration of errors. In this study, we propose a framework for reanalysing glacier mass balance series that includes conceptual and statistical toolsets for assessment of random and systematic errors, as well as for validation and calibration (if necessary) of the glaciological with the geodetic balance results. We demonstrate the usefulness and limitations of the proposed scheme, drawing on an analysis that comprises over 50 recording periods for a dozen glaciers, and we make recommendations to investigators and users of glacier mass balance data. Reanalysing glacier mass balance series needs to become a standard procedure for every monitoring programme to improve data quality, including reliable uncertainty estimates.