Dr. Ruzica Dadic

Photochemical release of iodine from snow has been suggested as a source of reactive iodine to the Arctic atmosphere, however understanding of the underlying mechanism and potential source strength is hindered by a lack of measurements of iodine concentration and speciation in snow. Moreover, the origin of snow iodine is also unknown. Here, we report iodine speciation measurements in Arctic snow on sea ice at a range of snow depths from 177 samples, representing 80 sampling events, from December 2019 to October 2020 collected during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition. We demonstrate that while there appears to be a source of iodine, in particular iodate, to the base of the snow over first year ice, this does not influence iodine concentration in the surface snow. There is instead evidence of a top-down source of iodine, potentially from iodine-enriched marine aerosol, as well as some evidence for episodic influx of iodate with dust. The potential for photochemical release of molecular iodine (I₂) from iodide in surface snow was investigated, and it was demonstrated that this could provide an iodine emission flux to the Arctic atmosphere comparable to oceanic fluxes. Knowledge of the prevalence and speciation of iodine in Arctic snow will contribute to better understanding of its contribution to observed concentrations of polar iodine oxide (IO), and hence its contribution to the depletion of tropospheric ozone in the Arctic.

The seasonal movement of the zero-degree isotherm across the Southern Ocean and Antarctic Peninsula drives major changes in the physical and biological processes around maritime Antarctica. These include spatial and temporal shifts in precipitation phase, snow accumulation and melt, thawing and freezing of the active layer of the permafrost, glacier mass balance variations, sea ice mass balance and changes in physiological processes of biodiversity. Here, we characterize the historical seasonal southward movement of the monthly near-surface zero-degree isotherm latitude (ZIL), and quantify the velocity of migration in the context of climate change using climate reanalyses and projections. From 1957 to 2020, the ZIL exhibited a significant southward shift of 16.8 km decade⁻¹ around Antarctica and of 23.8 km decade⁻¹ in the Antarctic Peninsula, substantially faster than the global mean velocity of temperature change of 4.2 km decade⁻¹, with only a small fraction being attributed to the Southern Annular Mode (SAM). CMIP6 models reproduce the trends observed from 1957 to 2014 and predict a further southward migration around Antarctica of 24 ± 12 km decade⁻¹ and 50 ± 19 km decade⁻¹ under the SSP2-4.5 and SSP5-8.5 scenarios, respectively. The southward migration of the ZIL is expected to have major impacts on the cryosphere, especially on the precipitation phase, snow accumulation and in peripheral glaciers of the Antarctic Peninsula, with more uncertain changes on permafrost, ice sheets and shelves, and sea ice. Longer periods of temperatures above 0 °C threshold will extend active biological periods in terrestrial ecosystems and will reduce the extent of oceanic ice cover, changing phenologies as well as areas of productivity in marine ecosystems, especially those located on the sea ice edge.

Changes in global mean sea level are a clear indicator of a warming climate, but local factors including land subsidence or uplift, cause changes in relative sea level that drive shoreline shifts. These local changes and their impact on coastal hazards matter to coastal communities. NZ SeaRise produced relative sea level projections for Aotearoa to include the latest global climate and Antarctic Ice Sheet research and estimates of vertical land movement at high spatial resolution. Research-informed communication to the public and planners included a web-based projections tool supplemented by written and visual narratives, and a media engagement plan. This communication, and analysis of media impact, provided a case study for audience-relevant information on sea-level rise. Information regarding shoreline change and evolving hazards, required for risk assessment, was not included in the NZ SeaRise projections. New research is needed to reduce uncertainty in future Antarctic Ice Sheet contribution to sea level, link changes in sea surface height to our dynamic land surface and enhance communication approaches. Several examples of the required research are presented here but ongoing efforts must refine the timing and magnitude of coastline change, better define coastal hazards and risks, and develop appropriate adaptation strategies for unavoidable climate change impacts.

Episodic deposition of light absorbing impurities on glaciers reduces albedo and exacerbates snow melt. In 2019/2020 a devastating Australian bushfire and desert dust event combined with favorable meteorological conditions transported an unprecedented mass of impurities across the Tasman Sea turning the Southern Alps of Aotearoa New Zealand red. Here we use time lapse cameras, airmass back trajectories, snow impurity geochemistry, and remote sensing to quantify the timing, provenance, and mass deposition of the event. Deposited in late November 2019, the impurities were dominated by mineral dust with a distinct southeastern Australian geochemical fingerprint. The event deposited ∼4,500 ± 500 tons of red dust to Southern Alps permanent snow and ice with a mean dust mass concentration of 6.5 ± 0.7 g m⁻². A southeast Australian desert dust storm generated by the same type of meteorological conditions as the 2020 New Year bushfires was the main driver of the glacier discoloration.

The behaviour and distribution of iodine in the environment are of significant interest in a range of scientific disciplines, from health, as iodine is an essential element for humans and animals, to climate and air quality, to geochemistry. Aquatic environments are the reservoir for iodine, where it exists in low concentrations as iodide, iodate and dissolved organic iodine and in which it undergoes redox reactions. The current measurement techniques for iodine species are typically time-consuming, subject to relatively poor precision and require specialist instrumentation including those that require mercury as an electrode. We present a new method for measuring iodine species, that is tailored towards lower dissolved organic carbon waters, such as seawater, rainwater and snow, using ion exchange chromatography (IC) with direct ultra-violet spectrophotometric detection of iodide and without the need for sample pre-concentration. Simple chemical amendments to the sample allow for the quantification of both iodate and dissolved organic iodine in addition to iodide. The developed IC method, which takes 16 min, was applied to contrasting samples that encompass a wide range of aqueous environments, from Arctic sea-ice snow (low concentrations) to coastal seawater (complex sample matrix). Linear calibrations are demonstrated for all matrices, using gravimetrically prepared potassium iodide standards. The detection limit for the iodide ion is 0.12 nM based on the standard deviation of the blank, while sample reproducibility is typically <2% at >8 nM and ∼4% at <8 nM. Since there is no environmental certified reference material for iodine species, the measurements made on seawater samples using this IC method were compared to those obtained using established analytical techniques; iodide voltammetry and iodate spectrophotometry. We calculated recoveries of 102 ± 16% (n = 107) for iodide and 116 ± 9% (n = 103) for iodate, the latter difference may be due to an underestimation of iodate by the spectrophotometric method. We further compared a chemical oxidation and reduction of the sample to an ultra-violet digestion to establish the total dissolved iodine content, the average recovery following chemical amendments was 98 ± 4% (n = 92). The new method represents a simple, efficient, green, precise and sensitive method for measuring dissolved speciated iodine in complex matrices.

Snow significantly impacts the seasonal growth of Arctic sea ice due to its thermally insulating properties. Various measurements and parameterizations of thermal properties exist, but an assessment of the entire seasonal evolution of thermal conductivity and snow resistance is hitherto lacking. Using the comprehensive snow dataset from the Multidisciplinary Drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition, we have evaluated for the first time the seasonal evolution of the snow's and denser snow-ice interface layers' thermal conductivity above different ice ages (refrozen leads, first-year ice, and second-year ice) and topographic features (ridges). Our dataset has a density range of snow and ice between 50 and 900 kg m⁻³, and corresponding anisotropy measurements, meaning we can test the current parameterizations of thermal conductivity for this density range. Combining different measurement parameterizations and assessing the robustness against spatial heterogeneity, we found the average thermal conductivity of snow (<550 kg m⁻³) on sea ice remains approximately constant (0.26 ± 0.05 ) over time irrespective of underlying ice type, with substantial spatial and vertical variability. Due to this consistency, we can state that the thermal resistance is mainly influenced by snow height, resulting in a 2.7 times higher average thermal resistance on ridges (1.42 m² K W⁻¹) compared to first-year level ice (0.51 m² K W⁻¹). Our findings explain how the scatter of thermal conductivity values directly results from structural properties. Now, the only step is to find a quick method to measure snow anisotropy in the field. Suggestions to do this are listed in the discussion.

Snow plays an essential role in the Arctic as the interface between the sea ice and the atmosphere. Optical properties, thermal conductivity and mass distribution are critical to understanding the complex Arctic sea ice system’s energy balance and mass distribution. By conducting measurements from October 2019 to September 2020 on the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition, we have produced a dataset capturing the year-long evolution of the physical properties of the snow and surface scattering layer, a highly porous surface layer on Arctic sea ice that evolves due to preferential melt at the ice grain boundaries. The dataset includes measurements of snow during MOSAiC. Measurements included profiles of depth, density, temperature, snow water equivalent, penetration resistance, stable water isotope, salinity and microcomputer tomography samples. Most snowpit sites were visited and measured weekly to capture the temporal evolution of the physical properties of snow. The compiled dataset includes 576 snowpits and describes snow conditions during the MOSAiC expedition.

The microstructure of the uppermost portions of a melting Arctic sea ice cover has a disproportionately large influence on how incident sunlight is reflected and absorbed in the ice/ocean system. The surface scattering layer (SSL) effectively backscatters solar radiation and keeps the surface albedo of melting ice relatively high compared to ice with the SSL manually removed. Measurements of albedo provide information on how incoming shortwave radiation is partitioned by the SSL and have been pivotal to improving climate model parameterizations. However, the relationship between the physical and optical properties of the SSL is still poorly constrained. Until now, radiative transfer models have been the only way to infer the microstructure of the SSL. During the MOSAiC expedition of 2019-2020, we took samples and, for the first time, directly measured the microstructure of the SSL on bare sea ice using X-ray micro-computed tomography. We show that the SSL has a highly anisotropic, coarse, and porous structure, with a small optical diameter and density at the surface, increasing with depth. As the melting surface ablates, the SSL regenerates, maintaining some aspects of its microstructure throughout the melt season. We used the microstructure measurements with a radiative transfer model to improve our understanding of the relationship between physical properties and optical properties at 850 nm wavelength. When the microstructure is used as model input, we see a 10-15% overestimation of the reflectance at 850 nm.This comparison suggests that either a) spatial variability at the meter scale is important for the two in situ optical measurements and therefore a larger sample size is needed to represent the microstructure or b) future work should investigate either i) using a ray-tracing approach instead of explicitly solving the radiative transfer equation or ii) using a more appropriate radiative transfer model.

Arctic sea ice is changing rapidly. Its retreat significantly impacts Arctic heat fluxes, ocean currents, and ecology, warranting the continuous monitoring and tracking of changes to sea ice extent and thickness. L-band (1.4 GHz) microwave radiometry can measure sea ice thickness for thin ice ≤1 m, depending on salinity and temperature. The sensitivity to thin ice makes L-band measurements complementary to radar altimetry which can measure the thickness of thick ice with reasonable accuracy. During the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition, we deployed the mobile ARIEL L-band radiometer on the sea ice floe next to research vessel Polarstern to study the sensitivity of the L-band to different sea ice parameters (e.g., snow and ice thickness, ice salinity, ice and snow temperature), with the aim to help improve/validate current microwave emission models. Our results show that ARIEL is sensitive to different types of surfaces (ice, leads, and melt ponds) and to ice thickness up to 70 cm when the salinity of the sea ice is low. The measurements can be reproduced with the Burke emission model when in situ snow and ice measurements for the autumn transects were used as model input. The correlation coefficient for modeled Burke brightness temperature (BT) versus ARIEL measurements was approximately 0.8. The discrepancy between the measurements and the model is about 5%, depending on the transects analyzed. No explicit dependence on snow depth was detected. We present a qualitative analysis for thin ice observations on leads. We have demonstrated that the ARIEL radiometer is an excellent field instrument for quantifying the sensitivity of L-band radiometry to ice and snow parameters, leading to insights that can enhance sea ice thickness retrievals from L-band radiometer satellites (such as Soil Moisture Ocean Salinity (SMOS) and Soil Moisture Active Passive (SMAP)) and improve estimates of Arctic sea-ice thickness changes on a larger scale.

Arctic rain on snow (ROS) deposits liquid water onto existing snowpacks. Upon refreezing, this can form icy crusts at the surface or within the snowpack. By altering radar backscatter and microwave emissivity, ROS over sea ice can influence the accuracy of sea ice variables retrieved from satellite radar altimetry, scatterometers, and passive microwave radiometers. During the Arctic Ocean MOSAiC (Multidisciplinary drifting Observatory for the Study of Arctic Climate) expedition, there was an unprecedented opportunity to observe a ROS event using in situ active and passive microwave instruments similar to those deployed on satellite platforms. During liquid water accumulation in the snowpack from rain and increased melt, there was a 4-fold decrease in radar energy returned at Ku- and Ka-bands. After the snowpack refroze and ice layers formed, this decrease was followed by a 6-fold increase in returned energy. Besides altering the radar backscatter, analysis of the returned waveforms shows the waveform shape changed in response to rain and refreezing. Microwave emissivity at 19 and 89 GHz increased with increasing liquid water content and decreased as the snowpack refroze, yet subsequent ice layers altered the polarization difference. Corresponding analysis of the CryoSat-2 waveform shape and backscatter as well as AMSR2 brightness temperatures further shows that the rain and refreeze were significant enough to impact satellite returns. Our analysis provides the first detailed in situ analysis of the impacts of ROS and subsequent refreezing on both active and passive microwave observations, providing important baseline knowledge for detecting ROS over sea ice and assessing their impacts on satellite-derived sea ice variables.

The influence of snow microstructure on thermal and radiative transfer in snow has not been thoroughly investigated as the tools necessary to efficiently measure microstructural geometry at millimeter resolution have not yet been available. Here we investigate the impact of snow microstructure on the thermal and radiative properties of snow and specifically determine the depth resolution of snow stratigraphy measurements needed to adequately model snow temperatures. To address this subject, detailed information on physical properties of the snow cover was collected at Summit, Greenland, in summer 2003. We present a new set of snow microstructure data, measured with a high-resolution penetrometer (SnowMicroPen (SMP)). The penetration resistance can be used to estimate the thickness of individual layers but also reflects the thickness and the number of bonds in the snowpack. SMP is a motor-driven, constant speed micropenetrometer acquiring 256 hardness measurements per millimeter. The data were used to describe the physical properties of snow and to compute snow temperatures in the topmost meter of the snowpack using the snow cover model SNOWPACK. The spatial resolution of the snow microstructure and the subsequent parametrization of SMP-estimated density strongly affected the modeled temperature and temperature gradients. The SMP-estimated density was used as an input to SNOWPACK and affected the thermal conductivity and radiative transfer in the snowpack. Our results thus show that highly resolved stratigraphic input data on the order of at least 1 cm are necessary to adequately simulate snow temperatures and snow metamorphism, including the observed formation of subsurface hoar in the high Arctic snow cover.