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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.

High-resolution, well-dated climate archives provide an opportunity to investigate the dynamic interactions of climate patterns relevant for future projections. Here, we present data from a new, annually dated ice core record from the eastern Ross Sea, named the Roosevelt Island Climate Evolution (RICE) ice core. Comparison of this record with climate reanalysis data for the 1979-2012 interval shows that RICE reliably captures temperature and snow precipitation variability in the region. Trends over the past 2700 years in RICE are shown to be distinct from those in West Antarctica and the western Ross Sea captured by other ice cores. For most of this interval, the eastern Ross Sea was warming (or showing isotopic enrichment for other reasons), with increased snow accumulation and perhaps decreased sea ice concentration. However, West Antarctica cooled and the western Ross Sea showed no significant isotope temperature trend. This pattern here is referred to as the Ross Sea Dipole. Notably, during the Little Ice Age, West Antarctica and the western Ross Sea experienced colder than average temperatures, while the eastern Ross Sea underwent a period of warming or increased isotopic enrichment. From the 17th century onwards, this dipole relationship changed. All three regions show current warming, with snow accumulation declining in West Antarctica and the eastern Ross Sea but increasing in the western Ross Sea. We interpret this pattern as reflecting an increase in sea ice in the eastern Ross Sea with perhaps the establishment of a modern Roosevelt Island polynya as a local moisture source for RICE

High-resolution, well-dated climate archives provide an opportunity to investigate the dynamic interactions of climate patterns relevant for future projections. Here, we present data from a new, annually dated ice core record from the eastern Ross Sea, named the Roosevelt Island Climate Evolution (RICE) ice core. Comparison of this record with climate reanalysis data for the 1979-2012 interval shows that RICE reliably captures temperature and snow precipitation variability in the region. Trends over the past 2700 years in RICE are shown to be distinct from those in West Antarctica and the western Ross Sea captured by other ice cores. For most of this interval, the eastern Ross Sea was warming (or showing isotopic enrichment for other reasons), with increased snow accumulation and perhaps decreased sea ice concentration. However, West Antarctica cooled and the western Ross Sea showed no significant isotope temperature trend. This pattern here is referred to as the Ross Sea Dipole. Notably, during the Little Ice Age, West Antarctica and the western Ross Sea experienced colder than average temperatures, while the eastern Ross Sea underwent a period of warming or increased isotopic enrichment. From the 17th century onwards, this dipole relationship changed. All three regions show current warming, with snow accumulation declining in West Antarctica and the eastern Ross Sea but increasing in the western Ross Sea. We interpret this pattern as reflecting an increase in sea ice in the eastern Ross Sea with perhaps the establishment of a modern Roosevelt Island polynya as a local moisture source for RICE.

The spatial distribution of alpine snow covers is characterised by large variability. Taking this variability into account is important for many tasks including hydrology, glaciology, ecology or natural hazards. Statistical modelling is frequently applied to assess the spatial variability of the snow cover. For this study, we assembled seven data sets of high-resolution snow-depth measurements from different mountain regions around the world. All data were obtained from airborne laser scanning near the time of maximum seasonal snow accumulation. Topographic parameters were used to model the snow depth distribution on the catchment-scale by applying multiple linear regressions.We found that by averaging out the substantial spatial heterogeneity at the metre scales, i.e. individual drifts and aggregating snow accumulation at the landscape or hydrological response unit scale (cell size 400 m), that 30 to 91% of the snow depth variability can be explained by models that are calibrated to local conditions at the single study areas. As all sites were sparsely vegetated, only a few topographic variables were included as explanatory variables, including elevation, slope, the deviation of the aspect from north (northing), and a wind sheltering parameter. In most cases, elevation, slope and northing are very good predictors of snow distribution. A comparison of the models showed that importance of parameters and their coefficients differed among the catchments. A “global” model, combining all the data from all areas investigated, could only explain 23% of the variability. It appears that local statistical models cannot be transferred to different regions. However, models developed on one peak snow season are good predictors for other peak snow seasons.

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.

©2019. American Geophysical Union. All Rights Reserved. Ice core data record significant and abrupt past climate changes that are associated with large and rapid changes in atmospheric greenhouse gases, such as methane. Due to the gradual close-off of gas bubbles and the relatively fast diffusion of gases within the firn column, even a discrete or quick step increase in air composition may be smoothed or integrated in the data; current laboratory analyses of gases consider the mean gas content value across all bubbles in a sample, rather than the content of individual bubbles. The convolution of the distribution of trapping ages with the history of atmospheric composition thus smears the measured gas record in each sample. We developed a nondestructive method to determine pressure distribution in all bubbles in a sample and estimate the shape of the trapping function derived from that bubble pressure distribution and site characteristics. Our method works not only for present conditions but also through varying paleo-atmospheric conditions, while providing accurate measurements of morphological bubble properties. The method is based on using temperature-driven air bubble migration as a proxy for the pressure of individual bubbles, which we combine with a model for bubbly ice densification to obtain the gas trapping functions and constrain the age distribution of air bubbles for past conditions, which are preserved at different depths. The trapping functions will help us to obtain a more accurate gas signal in the future that is less attenuated through the age distribution of the gas during the close-off process.