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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. We document the isotopic evolution of near-surface snow at the East Greenland Ice Core Project (EastGRIP) ice core site in northeast Greenland using a time-resolved array of 1 m deep isotope (δ18O, δD) profiles. The snow profiles were taken from May–August during the 2017–2019 summer seasons. An age–depth model was developed and applied to each profile, mitigating the impacts of stratigraphic noise on isotope signals. Significant changes in deuterium excess (d) are observed in surface snow and near-surface snow as the snow ages. Decreases in d of up to 5 ‰ occur during summer seasons after deposition during two of the three summer seasons observed. The d always experiences a 3 ‰–5 ‰ increase after aging 1 year in the snow due to a broadening of the autumn d maximum. Models of idealized scenarios coupled with prior work indicate that the summertime post-depositional changes in d (Δd) can be explained by a combination of surface sublimation, forced ventilation of the near-surface snow down to 20–30 cm, and isotope-gradient-driven diffusion throughout the column. The interannual Δd is also partly explained with isotope-gradient-driven diffusion, but other mechanisms are at work that leave a bias in the d record. Thus, d does not just carry information about source-region conditions and transport history as is commonly assumed, but also integrates local conditions into summer snow layers as the snow ages through metamorphic processes. Finally, we observe a dramatic increase in the seasonal isotope-to-temperature sensitivity, which can be explained solely by isotope-gradient-driven diffusion. Our results are dependent on the site characteristics (e.g., wind, temperature, accumulation rate, snow properties) but indicate that more process-based research is necessary to understand water isotopes as climate proxies. Recommendations for monitoring and physical modeling are given, with special attention to the d parameter. 

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.