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1. Holocene eolian sediment and organic matter from terraces and hillslopes around Healy, central Alaska

   https://doi.org/10.18739/A2X921M1C  

   Walker, Caitlin; Kaufman, Darrell; McKay, Nicholas; Schuur, Edward (January 2024, NSF Arctic Data Center)

   Three natural exposures near Healy, Alaska (Dry Creek, Panguingue Creek, and Healy Spur) and transects of shallow cores from three hillslopes near Eight Mile Lake were analyzed for particle-size distribution, loss-on-ignition for organic matter content, and radiocarbon dating. This study is part of a Master’s thesis research project by Walker at Northern Arizona University (https://www.proquest.com/openview/80b94829f88d5c8e0d0d678581079273/1?pq-origsite=gscholar&cbl=18750&diss=y). It builds on work of Marshall et al. (2023; doi: 10.1029/2022JG007290) who reported data from additional sediment cores taken along one of the hillslopes in this study, namely Hillslope A (https://arcticdata.io/catalog/view/doi:10.18739/A2F76683D). The motivation was to compare datasets of eolian material between different depositional settings, as well as identify trends in eolian thickness and particle size across the Healy landscape to reconstruct Holocene eolian deposition and identify the factors influencing depositon. 

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2. A Bin and a Bulk Microphysics Scheme Can Be More Alike Than Two Bin Schemes

   https://doi.org/10.1029/2022MS003303  

   Hu, Arthur Z.; Igel, Adele L. (March 2023, Journal of Advances in Modeling Earth Systems)

   Abstract Bin and bulk schemes are the two primary methods to parameterize cloud microphysical processes. This study attempts to reveal how their structural differences (size‐resolved vs. moment‐resolved) manifest in terms of cloud and precipitation properties. We use a bulk scheme, the Arbitrary Moment Predictor (AMP), which uses process parameterizations identical to those in a bin scheme but predicts only moments of the size distribution like a bulk scheme. As such, differences between simulations using AMP's bin scheme and simulations using AMP itself must come from their structural differences. In one‐dimensional kinematic simulations, the overall difference between AMP (bulk) and bin schemes is found to be small. Full‐microphysics AMP and bin simulations have similar mean liquid water path (mean percent difference <4%), but AMP simulates significantly lower mean precipitation rate (−35%) than the bin scheme due to slower precipitation onset. Individual processes are also tested. Condensation is represented almost perfectly with AMP, and only small AMP‐bin differences emerge due to nucleation, evaporation, and sedimentation. Collision‐coalescence is the single biggest reason for AMP‐bin divergence. Closer inspection shows that this divergence is primarily a result of autoconversion and not of accretion. In full microphysics simulations, lowering the diameter threshold separating cloud and rain category in AMP fromtoreduces the largest AMP‐bin difference to ∼10%, making the effect of structural differences between AMP (and perhaps triple‐moment bulk schemes generally) and bin even smaller than the parameterization differences between the two bin schemes. 

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3. Declining basal motion drives the long-term slowing of Athabasca Glacier, 1961-2019, Canada

   https://doi.org/10.18739/A23R0PV5K  

   Armstrong, William; Polashenski, David (January 2022, NSF Arctic Data Center)

   Globally, glaciers are shrinking in response to climate change, with implications for global sea level rise as well as downstream ecosystems and water resources. Sliding at the ice-bed interface (basal motion) provides a mechanism for glaciers to respond rapidly to climate change. While the short-term dynamics of glacier basal motion (&amp;amp;amp;amp;lt; 10 years) have received substantial attention, little is known about how basal motion and its sensitivity to subglacial hydrology changes over long (&amp;amp;amp;amp;gt; 50 year) timescales – this knowledge is required for accurate prediction of future glacier change. We compare historical data with modern estimates from field-collected and remotely-sensed data at Athabasca Glacier and show that, between 1961 and 2019, the glacier thinned by 51 meter ( - 18 %). However, a concurrent increase in surface slope results in minimal change in the average driving stress (-10 kilopascal, - 7%). These geometric changes coincide with a uniform surface slow down of surface velocity (-15 meter a-1, -45%). Historical observations and simplified ice modeling suggest that declining basal motion accounts for most of this slow down (63 % at a minimum). A decline in basal motion can be explained by increasing basal friction resulting from geometric change in addition to increasing meltwater flux through an efficient subglacial hydrologic system. There is some evidence that changes in basal motion in the overdeepened reach are responsible for slowing basal motion several km up-glacier. These results highlight the need to include time-varying dynamics of basal motion in glacier models and analyses. These findings suggest declining basal motion may reduce the flux of ice to lower elevations, helping to mitigate glacier mass loss in a warming climate. 

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4. MBSE Online Professional Development Learning Modules Data

   https://doi.org/10.4231/3DR2-VY15  

   Douglas, Kerrie; Huang, Wanju; Li, Tiantian; Marcos, Leonardo; Huang, Wanju (January 2025, Purdue University Research Repository)

   <p>The data was downloaded and captured through MBSE online learning modules. Deidentified learners&#39; activities within the modules, such as clickstreams and assignments, were captured in the data/</p> <p>&bull; All files here are student submissions to one or more of the modules in the MBSE program.</p> <p>&bull; All user data has either been removed or redacted from the submission.</p> <p>&bull; &ldquo;Andrew Hurt&rdquo; is not a student and none of these files came from him. He is the person who did the redaction.</p> <p>&bull; The naming structure of the files is as follows: [Module number]-[Module Offering Date]-[Submission Number]-[Part Number of Submission]. Example: M5-040422-S1-Part3. This file is from Module 5, which was offered on April 4, 2022, it is submission 1, and part 3 of submission 1.</p> <p>&bull; Note that submissions within or between modules are not necessarily connected to specific students. So &ldquo;Submission 1&rdquo; from module 5 is not the same user as &ldquo;Submission 1&rdquo; from module 6.</p> <p>&bull; Not all submissions have multiple parts.</p> <p>&bull; No .mdzip files (proprietary MagicDraw software files) have been included in this list.</p> <p>&bull; If a module or folder in the module is missing content from a particular offering, it is because either no one submitted anything or because the file was a .mdzip file and was not downloaded.</p> <p>&nbsp;</p> 

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5. Supercooled liquid fogs over the central Greenland Ice Sheet

   https://doi.org/10.5194/acp-19-7467-2019  

   Cox, Christopher J.; Noone, David C.; Berkelhammer, Max; Shupe, Matthew D.; Neff, William D.; Miller, Nathaniel B.; Walden, Von P.; Steffen, Konrad (January 2019, Atmospheric Chemistry and Physics)

   Abstract. Radiation fogs at Summit Station, Greenland (72.58^∘&thinsp;N,38.48^∘&thinsp;W; 3210&thinsp;m&thinsp;a.s.l.), are frequently reported by observers. Thefogs are often accompanied by fogbows, indicating the particles are composedof liquid; and because of the low temperatures at Summit, this liquid issupercooled. Here we analyze the formation of these fogs as well as theirphysical and radiative properties. In situ observations of particle size anddroplet number concentration were made using scattering spectrometers near 2 and 10&thinsp;m height from 2012 to 2014. These data are complemented bycolocated observations of meteorology, turbulent and radiative fluxes, andremote sensing. We find that liquid fogs occur in all seasons with thehighest frequency in September and a minimum in April. Due to thecharacteristics of the boundary-layer meteorology, the fogs are elevated,forming between 2 and 10&thinsp;m, and the particles then fall toward the surface.The diameter of mature particles is typically 20–25&thinsp;µm in summer.Number concentrations are higher at warmer temperatures and, thus, higher insummer compared to winter. The fogs form at temperatures as warm as −5&thinsp;^∘C, while the coldest form at temperatures approaching −40&thinsp;^∘C. Facilitated by the elevated condensation, in winter two-thirds offogs occurred within a relatively warm layer above the surface when thenear-surface air was below −40&thinsp;^∘C, as cold as −57&thinsp;^∘C,which is too cold to support liquid water. This implies that fog particlessettling through this layer of cold air freeze in the air column beforecontacting the surface, thereby accumulating at the surface as ice withoutriming. Liquid fogs observed under otherwise clear skies annually imparted1.5&thinsp;W&thinsp;m⁻² of cloud radiative forcing (CRF). While this is a smallcontribution to the surface radiation climatology, individual events areinfluential. The mean CRF during liquid fog events was 26&thinsp;W&thinsp;m⁻², andwas sometimes much higher. An extreme case study was observed toradiatively force 5&thinsp;^∘C of surface warming during the coldest partof the day, effectively damping the diurnal cycle. At lower elevations ofthe ice sheet where melting is more common, such damping could signal a rolefor fogs in preconditioning the surface for melting later in the day. 

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