<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Culpepper, Joshua</style></author><author><style face="normal" font="default" size="100%">Sharma, Sapna</style></author><author><style face="normal" font="default" size="100%">Gunn, Grant</style></author><author><style face="normal" font="default" size="100%">Magee, Madeline R.</style></author><author><style face="normal" font="default" size="100%">Meyer, Michael F.</style></author><author><style face="normal" font="default" size="100%">Anderson, Eric J.</style></author><author><style face="normal" font="default" size="100%">Arp, Chris</style></author><author><style face="normal" font="default" size="100%">Cooley, Sarah W.</style></author><author><style face="normal" font="default" size="100%">Dolan, Wayana</style></author><author><style face="normal" font="default" size="100%">Hilary A. Dugan</style></author><author><style face="normal" font="default" size="100%">Duguay, Claude R.</style></author><author><style face="normal" font="default" size="100%">Jones, Benjamin M.</style></author><author><style face="normal" font="default" size="100%">Kirillin, Georgiy</style></author><author><style face="normal" font="default" size="100%">Ladwig, Robert</style></author><author><style face="normal" font="default" size="100%">Leppäranta, Matti</style></author><author><style face="normal" font="default" size="100%">Long, Di</style></author><author><style face="normal" font="default" size="100%">Magnuson, John J.</style></author><author><style face="normal" font="default" size="100%">Pavelsky, Tamlin</style></author><author><style face="normal" font="default" size="100%">Piccolroaz, Sebastiano</style></author><author><style face="normal" font="default" size="100%">Robertson, Dale M.</style></author><author><style face="normal" font="default" size="100%">Steele, Bethel G.</style></author><author><style face="normal" font="default" size="100%">Tom, Manu</style></author><author><style face="normal" font="default" size="100%">Weyhenmeyer, Gesa A.</style></author><author><style face="normal" font="default" size="100%">Woolway, R. Iestyn</style></author><author><style face="normal" font="default" size="100%">Xenopoulos, Marguerite A.</style></author><author><style face="normal" font="default" size="100%">Yang, Xiao</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">One-hundred fundamental, open questions to integrate methodological approaches in lake ice research</style></title><secondary-title><style face="normal" font="default" size="100%">Water Resources Research</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">cryosphere</style></keyword><keyword><style  face="normal" font="default" size="100%">lake ice</style></keyword><keyword><style  face="normal" font="default" size="100%">limnology</style></keyword><keyword><style  face="normal" font="default" size="100%">modeling</style></keyword><keyword><style  face="normal" font="default" size="100%">remote sensing</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2025</style></year><pub-dates><date><style  face="normal" font="default" size="100%">05/2025</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2024WR039042</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">61</style></volume><pages><style face="normal" font="default" size="100%">e2024WR039042</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;The rate of technological innovation within aquatic sciences outpaces the collective ability of individual scientists within the field to make appropriate use of those technologies. The process of in situ lake sampling remains the primary choice to comprehensively understand an aquatic ecosystem at local scales; however, the impact of climate change on lakes necessitates the rapid advancement of understanding and the incorporation of lakes on both landscape and global scales. Three fields driving innovation within winter limnology that we address here are autonomous real-time in situ monitoring, remote sensing, and modeling. The recent progress in low-power in situ sensing and data telemetry allows continuous tracing of under-ice processes in selected lakes as well as the development of global lake observational networks. Remote sensing offers consistent monitoring of numerous systems, allowing limnologists to ask certain questions across large scales. Models are advancing and historically come in different types (process-based or statistical data-driven), with the recent technological advancements and integration of machine learning and hybrid process-based/statistical models. Lake ice modeling enhances our understanding of lake dynamics and allows for projections under future climate warming scenarios. To encourage the merging of technological innovation within limnological research of the less-studied winter period, we have accumulated both essential details on the history and uses of contemporary sampling, remote sensing, and modeling techniques. We crafted 100 questions in the field of winter limnology that aim to facilitate the cross-pollination of intensive and extensive modes of study to broaden knowledge of the winter period.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">5</style></issue></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>32</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Dougherty, Charles E.</style></author></authors><secondary-authors><author><style face="normal" font="default" size="100%">Hilary A. Dugan</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">The temporal and spatial dynamics of surface sediment on the permanently frozen lakes of Taylor Valley, Antarctica</style></title><secondary-title><style face="normal" font="default" size="100%">Freshwater and Marine Sciences</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">aeolian geomorphology</style></keyword><keyword><style  face="normal" font="default" size="100%">McMurdo Dry Valleys</style></keyword><keyword><style  face="normal" font="default" size="100%">permanently frozen lakes</style></keyword><keyword><style  face="normal" font="default" size="100%">polar lakes</style></keyword><keyword><style  face="normal" font="default" size="100%">remote sensing</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2025</style></year><pub-dates><date><style  face="normal" font="default" size="100%">05/2025</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://digital.library.wisc.edu/1793/95194</style></url></web-urls></urls><publisher><style face="normal" font="default" size="100%">University of Wisconsin-Madison</style></publisher><pub-location><style face="normal" font="default" size="100%">Madison, WI</style></pub-location><volume><style face="normal" font="default" size="100%">M.S.</style></volume><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;The McMurdo Dry Valleys are the largest unglaciated region of Antarctica and are home to some of the only perennially frozen lakes in the world. The ice covers of the Taylor Valley lakes are subject to decadal-length fluctuations in thickness, largely ranging between three and five meters thick. It has been hypothesized that the changes in ice cover thickness are due to a combination of climate factors and lake ice surface characteristics, but as of yet there have been no studies focusing on interannual dynamics of lake ice albedo by leveraging remote sensing datasets. Landsat 8 imagery was manipulated using spectral mixture analysis to find the abundance of sediment cover across three different Taylor Valley lakes from 2016-2024 during the sunlit period of the year. Peak sediment coverage was not synchronous across years, with Lake Hoare peaking the earliest in 2021, followed by East Lake Bonney and Lake Fryxell in 2023. West Lake Bonney had no apparent peak, although concentrations have declined since 2021. Overall sediment abundance values across all lakes ranged from near 0% to over 75%, though each lake has a different level of sediment coverage. Lake Fryxell and Lake Hoare had the highest mean sediment concentrations, followed by East Lake Bonney, then West Lake Bonney. The relationship between ice thickness and sediment coverage was strongest at Lake Fryxell, followed by East Lake Bonney. Lake Hoare and West Lake Bonney appear to have weaker links between ice thickness and surface sediment, likely driven by differences in overall sediment cover and shading from the surrounding landscape. Ice surface albedo is a historically understudied component of ice physical structure and thermal mechanics and should be more closely considered in future studies predicting ice thickness in the McMurdo Dry Valleys, especially in cases to predict total ice loss. Permanently frozen lakes exhibit unique ice dynamics compared to seasonally freezing lakes, due to their consistent lake ice, where previous years ice conditions have a large effect on ice into the future. The McMurdo Dry Valleys (MDVs), a large unglaciated region in Antarctica, contain many of the few permanently frozen lakes that exist globally. Albedo is a critical factor influencing lake ice mass balance and may strongly govern lake ice thickness. Changes in surface albedo on MDVs lakes occur as a result of aeolian sediment deposition from the surrounding bare soil landscape or physical changes in ice quality throughout the summer, like ice whitening. To investigate the importance of surface characteristics of Taylor Valley lake ice, a one-dimensional thermal diffusion model was developed using in situ meteorological data and a satellite derived ice albedo estimates to simulate ice thickness on East Lake Bonney, Antarctica. Ice thickness was modeled from late 2016 through 2024 using a novel ice albedo dataset, derived from Landsat 8 imagery using linear spectral mixture analysis. Estimated albedo values ranged from 0.5-0.85, covering years when sediment cover was very heavy to very low. Modeled ice thickness was strongly correlated with measured thicknesses. For the period of the year where manual ice thickness measurements are made, modeled ice thicknesses ranged between 2.92-4.16 m, where measured values for that same time span ranged between 3.06-4.19 m. When either increasing or decreasing albedo by 5-10%, mean ice thicknesses diverged by up to 0.8 m. Ice thicknesses are strongly influenced by surface sediment concentrations, and the contribution of a tailored albedo dataset was a valuable input that has historically been over-simplified.&lt;/p&gt;</style></abstract><work-type><style face="normal" font="default" size="100%">Master's thesis</style></work-type></record></records></xml>