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Climate change is a major concern to undergraduate students. Understanding climate change relies on an understanding of polar regions. However, courses on polar regions are rare at undergraduate institutions. Polar ENgagement through GUided INquiry (PENGUIN) modules were designed to give students experience with polar research in a variety of standard courses, including physics, computer science, physical chemistry, and economics, through using course-specific and computational tools to analyze polar data. Here, we present a new PENGUIN module taught in a statistics class, in which students apply statistical tools to ice core data to reconstruct past temperature records. Quantitative student responses on pre- and post-surveys were collected in a quasi-experimental context to assess student knowledge gains for a test group of 91 students and a control group of 73 students (who did not complete the module). Test-group students made statistically significant increases of 25 to 46% on all six statistics questions, with a normalized gain of 56%. By contrast, control group statistics knowledge gains ranged from −4 to 25%, with statistically significant increases for only three questions and a normalized gain of 22%. For polar research questions, the test group demonstrated increases in correct responses to polar research questions (11 to 31%), with statistically significant improvements (p < .05) of 22-31% on 3 of 6 polar research questions. These findings support the conclusion that PENGUIN modules can successfully teach course concepts while increasing polar literacy. 

Abstract. Atmospheric rivers (ARs) are the primary mechanism for transporting water vapor from low latitudes to polar regions, playing a significant role in extreme weather in both the Arctic and Antarctica. With the rapidly growing interest in polar ARs during the past decade, it is imperative to establish an objective framework quantifying the strength and impact of these ARs for both scientific research and practical applications. The AR scale introduced by Ralph et al. (2019) ranks ARs based on the duration of AR conditions and the intensity of integrated water vapor transport (IVT). However, the thresholds of IVT used to rank ARs are selected based on the IVT climatology at middle latitudes. These thresholds are insufficient for polar regions due to the substantially lower temperature and moisture content. In this study, we analyze the IVT climatology in polar regions, focusing on the coasts of Antarctica and Greenland. Then we introduce an extended version of the AR scale tuned to polar regions by adding lower IVT thresholds of 100, 150, and 200 kg m−1 s−1 to the standard AR scale, which starts at 250 kg m−1 s−1. The polar AR scale is utilized to examine AR frequency, seasonality, trends, and associated precipitation and surface melt over Antarctica and Greenland. Our results show that the polar AR scale better characterizes the strength and impacts of ARs in the Antarctic and Arctic regions than the original AR scale and has the potential to enhance communication across observational, research, and forecasting communities in polar regions. 

Abstract The Year of Polar Prediction in the Southern Hemisphere (YOPP-SH) held seven targeted observing periods (TOPs) during the 2022 austral winter to enhance atmospheric predictability over the Southern Ocean and Antarctica. The TOPs of 5–10-day duration each featured the release of additional radiosonde balloons, more than doubling the routine sounding program at the 24 participating stations run by 14 nations, together with process-oriented observations at selected sites. These extra sounding data are evaluated for their impact on forecast skill via data denial experiments with the goal of refining the observing system to improve numerical weather prediction for winter conditions. Extensive observations focusing on clouds and precipitation primarily during atmospheric river (AR) events are being applied to refine model microphysical parameterizations for the ubiquitous mixed-phase clouds that frequently impact coastal Antarctica. Process studies are being facilitated by high-time-resolution series of observations and forecast model output via the YOPP Model Intercomparison and Improvement Project (YOPPsiteMIIP). Parallel investigations are broadening the scope and impact of the YOPP-SH winter TOPs. Studies of the Antarctic tourist industry’s use of weather services show the scope for much greater awareness of the availability of forecast products and the skill they exhibit. The Sea Ice Prediction Network South (SIPN South) analysis of predictions of the sea ice growth period reveals that the forecast skill is superior to the sea ice retreat phase. 

Abstract Black carbon (BC) from fossil fuel and biomass combustion darkens the snow and makes it melt sooner. The BC footprint of research activities and tourism in Antarctica has likely increased as human presence in the continent has surged in recent decades. Here, we report on measurements of the BC concentration in snow samples from 28 sites across a transect of about 2,000 km from the northern tip of Antarctica (62°S) to the southern Ellsworth Mountains (79°S). Our surveys show that BC content in snow surrounding research facilities and popular shore tourist-landing sites is considerably above background levels measured elsewhere in the continent. The resulting radiative forcing is accelerating snow melting and shrinking the snowpack on BC-impacted areas on the Antarctic Peninsula and associated archipelagos by up to 23 mm water equivalent (w.e.) every summer. 

Outstanding questions about the RNA world hypothesis for the emergence of life on Earth concern the stability and self-replication of prebiotic aqueous RNA. Recent experimental work has suggested that solid substrates and low temperatures could help resolve these issues. Herein, we use classical molecular dynamics simulations to explore the possibility that the substrate is ice itself. Simulations at −20 °C show that an eight-nucleotide single strand of RNA, initially situated in the quasiliquid layer at the air/ice interface, exhibits a robust propensity to reorient itself -- its bases turn toward the (hydrophobic) air/ice interface, while its anionic phosphodiester oxygens align with the underlying ice lattice. Kinetic analysis of hydrogen bonding indicates resistance to hydrolysis that is greater than that of an aqueous single-strand RNA at the same temperature. This enhanced resistance, in turn, could increase the opportunities for polymerization and self-copying. These findings thus offer the possibility of a role for an ancient RNA world on ice distinct from that considered in extant elaborations of the RNA world hypothesis. This work is, to the best of our knowledge, the first molecular dynamics study of RNA on ice. 

Abstract. Improvements to climate model results in polar regions require improvedknowledge of cloud properties. Surface-based infrared (IR) radiancespectrometers have been used to retrieve cloud properties in polar regions,but measurements are sparse. Reductions in cost and power requirements toallow more widespread measurements could be aided by reducing instrumentresolution. Here we explore the effects of errors and instrument resolutionon cloud property retrievals from downwelling IR radiances for resolutionsof 0.1 to 20 cm−1. Retrievals are tested on 336 radiance simulationscharacteristic of the Arctic, including mixed-phase, verticallyinhomogeneous, and liquid-topped clouds and a variety of ice habits.Retrieval accuracy is found to be unaffected by resolution from 0.1 to 4 cm−1, after which it decreases slightly. When cloud heights areretrieved, errors in retrieved cloud optical depth (COD) and ice fractionare considerably smaller for clouds with bases below 2 km than for higherclouds. For example, at a resolution of 4 cm−1, with errors imposed(noise and radiation bias of 0.2 mW/(m2 sr cm−1) and biases intemperature of 0.2 K and in water vapor of −3 %), using retrieved cloudheights, root-mean-square errors decrease from 1.1 to 0.15 for COD, 0.3 to0.18 for ice fraction (fice), and 10 to 7 µm for iceeffective radius (errors remain at 2 µm for liquid effective radius).These results indicate that a moderately low-resolution, surface-based IRspectrometer could provide cloud property retrievals with accuracycomparable to existing higher-resolution instruments and that such aninstrument would be particularly useful for low-level clouds. 

Abstract Clouds have a large effect on the radiation budget and represent a major source of uncertainty in climate models. Supercooled liquid clouds can exist at temperatures as low as 235 K, and the radiative effect of these clouds depends on the complex refractive index (CRI) of liquid water. Laboratory measurements have demonstrated that the liquid‐water CRI is temperature‐dependent, but corroboration with field measurements is difficult. Here we present measurements of the downwelling infrared radiance and in‐situ measurements of supercooled liquid water in a cloud at temperatures as low as 240 K, made at South Pole Station in 2001. These results demonstrate that including the temperature dependence of the liquid‐water CRI is essential for accurate calculations of radiative transfer through supercooled liquid clouds. Furthermore, we show that when cloud properties are retrieved from infrared radiances (using the spectral range 500–1,200 cm⁻¹) spurious ice may be retrieved if the 300 K CRI is used for cold liquid clouds (∼240 K). These results have implications for radiative transfer in climate models as well as for retrievals of cloud properties from infrared radiance spectra. 

Abstract Supercooled fogs can have an important radiative impact at the surface of the Greenland Ice Sheet, but they are difficult to detect and our understanding of the factors that control their lifetime and radiative properties is limited by a lack of observations. This study demonstrates that spectrally resolved measurements of downwelling longwave radiation can be used to generate retrievals of fog microphysical properties (phase and particle effective radius) when the fog visible optical depth is greater than ∼0.25. For 12 cases of fog under otherwise clear skies between June and September 2019 at Summit Station in central Greenland, nine cases were mixed‐phase. The mean ice particle (optically‐equivalent sphere) effective radius was 24.0 ± 7.8 µm, and the mean liquid droplet effective radius was 14.0 ± 2.7 µm. These results, combined with measurements of aerosol particle number concentrations, provide evidence supporting the hypotheses that (a) low surface aerosol particle number concentrations can limit fog liquid water path, (b) fog can act to increase near‐surface aerosol particle number concentrations through enhanced mixing, and (c) multiple fog events in quiescent periods gradually deplete near‐surface aerosol particle number concentrations. 

Abstract. Polar regions are characterized by their remoteness, making measurements challenging, but an improved knowledge of clouds and radiation is necessary to understand polar climate change. Infrared radiance spectrometers can operate continuously from the surface and have low power requirements relative to active sensors. Here we explore the feasibility of retrieving cloud height with an infrared spectrometer that would be designed for use in remote polar locations. Using a wide variety of simulated spectra of mixed-phase polar clouds at varying instrument resolutions, retrieval accuracy is explored using the CO₂ slicing/sorting and the minimum local emissivity variance (MLEV) methods. In the absence of imposed errors and for clouds with optical depths greater than  ∼ 0.3, cloud-height retrievals from simulated spectra using CO₂ slicing/sorting and MLEV are found to have roughly equivalent high accuracies: at an instrument resolution of 0.5cm⁻¹, mean biases are found to be  ∼ 0.2km for clouds with bases below 2 and −0.2km for higher clouds. Accuracy is found to decrease with coarsening resolution and become worse overall for MLEV than for CO₂ slicing/sorting; however, the two methods have differing sensitivity to different sources of error, suggesting an approach that combines them. For expected errors in the atmospheric state as well as both instrument noise and bias of 0.2mW/(m²srcm⁻¹), at a resolution of 4cm⁻¹, average retrieval errors are found to be less than  ∼ 0.5km for cloud bases within 1km of the surface, increasing to  ∼ 1.5km at 4km. This sensitivity indicates that a portable, surface-based infrared radiance spectrometer could provide an important complement in remote locations to satellite-based measurements, for which retrievals of low-level cloud are challenging.