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This paper presents an analysis of the bed detecting capabilities of an ice sounding radar integrated onto a small, unmanned aircraft system (UAS). We evaluated the average signal-to-noise ratio (SNR) and signal-to-interference ratio (SINR) of radar measurements collected by the UAS over Greenland’s Helheim Glacier in 2022 and compared those to radar measurements collected over the same region using a radar-equipped Twin Otter around 2008. The statistical analysis presented of the SNR and the SINR shows that both systems have comparable bed detection capabilities. While the average SNR for all points considered is more than 20 dB higher for the Twin Otter system, the average SINR of both has a similar value. The overall average SINR is 9.79 dB for the UAS and 9.19 dB for the MA. As it is discussed in the paper, the lower SNR of the UAS system is attributed to its lower operating frequency, while the comparable SINR depends on various factors. The results of this paper have implications on planning and design of future field deployments. 

Bacterial cells are covered by a complex carbohydrate coat of armor that allows bacteria to thrive in a range of environments. As a testament to the importance of bacterial glycans, effective and heavily utilized antibiotics including penicillin and vancomycin target and disrupt the bacterial glycocalyx. Despite their importance, the study of bacterial glycans lags far behind their eukaryotic counterparts. Bacterial cells use a large palette of monosaccharides to craft glycans, leading to molecules that are significantly more complex than eukaryotic glycans and that are refractory to study. Fortunately, chemical tools designed to probe bacterial glycans have yielded insights into these molecules, their structures, their biosynthesis, and their functions. 

Abstract. During the concluding phase of the NASA OperationIceBridge (OIB), we successfully completed two airborne measurementcampaigns (in 2018 and 2021, respectively) using a compact S and C band radarinstalled on a Single Otter aircraft and collected data over Alaskanmountains, ice fields, and glaciers. This paper reports seasonal snow depthsderived from radar data. We found large variations in seasonalradar-inferred depths with multi-modal distributions assuming a constantrelative permittivity for snow equal to 1.89. About 34 % of the snowdepths observed in 2018 were between 3.2 and 4.2 m, and close to 30 % of thesnow depths observed in 2021 were between 2.5 and 3.5 m. We observed snowstrata in ice facies, combined percolation and wet-snow facies, and dry-snow facies fromradar data and identified the transition areas from wet-snow facies to icefacies for multiple glaciers based on the snow strata and radarbackscattering characteristics. Our analysis focuses on the measured strataof multiple years at the caldera of Mount Wrangell (K'elt'aeni) to estimate the localsnow accumulation rate. We developed a method for using our radar readingsof multi-year strata to constrain the uncertain parameters of interpretationmodels with the assumption that most of the snow layers detected by theradar at the caldera are annual accumulation layers. At a 2004 ice core and2005 temperature sensor tower site, the locally estimated average snowaccumulation rate is ∼2.89 m w.e. a−1 between the years2003 and 2021. Our estimate of the snow accumulation rate between 2005 and2006 is 2.82 m w.e. a−1, which matches closely to the 2.75 m w.e. a−1 inferred from independent ground-truth measurements made the sameyear. The snow accumulation rate between the years 2003 and 2021 also showeda linear increasing trend of 0.011 m w.e. a−2. This trend iscorroborated by comparisons with the surface mass balance (SMB) derived forthe same period from the regional atmospheric climate model MAR (ModèleAtmosphérique Régional). According to MAR data, which show anincrease of 0.86 ∘C in this area for the period of 2003–2021, thelinear upward trend is associated with the increase in snowfall and rainfallevents, which may be attributed to elevated global temperatures. Thefindings of this study confirmed the viability of our methodology, as wellas its underlying assumptions and interpretation models. 

The CSforALL movement to bring computational thinking to K-12 has been a boon for practitioners and language developers. This panel features three educators passionate about a particular lan- guage that has been successful with K-12 audiences. Each will demonstrate their language, describe what makes it unique, and share some of the fun and engaging projects students have created. 

Abstract The geographical variability, frequency content, and vertical structure of near‐surface oceanic kinetic energy (KE) are important for air‐sea interaction, marine ecosystems, operational oceanography, pollutant tracking, and interpreting remotely sensed velocity measurements. Here, KE in high‐resolution global simulations (HYbrid Coordinate Ocean Model; HYCOM, and Massachusetts Institute of Technology general circulation model; MITgcm), at the sea surface (0 m) and at 15 m, are compared with KE from undrogued and drogued surface drifters, respectively. Global maps and zonal averages are computed for low‐frequency (<0.5 cpd), near‐inertial, diurnal, and semidiurnal bands. Both models exhibit low‐frequency equatorial KE that is low relative to drifter values. HYCOM near‐inertial KE is higher than in MITgcm, and closer to drifter values, probably due to more frequently updated atmospheric forcing. HYCOM semidiurnal KE is lower than in MITgcm, and closer to drifter values, likely due to inclusion of a parameterized topographic internal wave drag. A concurrent tidal harmonic analysis in the diurnal band demonstrates that much of the diurnal flow is nontidal. We compute simple proxies of near‐surface vertical structure—the ratio 0 m KE/(0 m KE + 15 m KE) in model outputs, and the ratio undrogued KE/(undrogued KE + drogued KE) in drifter observations. Over most latitudes and frequency bands, model ratios track the drifter ratios to within error bars. Values of this ratio demonstrate significant vertical structure in all frequency bands except the semidiurnal band. Latitudinal dependence in the ratio is greatest in diurnal and low‐frequency bands.