@article {4925,
	title = {Meteorological drivers of melt at two nearby glaciers in the McMurdo Dry Valleys of Antarctica},
	journal = {Journal of Glaciology},
	year = {2023},
	month = {12/2023},
	pages = {1 - 13},
	abstract = {<p>We study the meteorological drivers of melt at two glaciers in Taylor Valley, Antarctica, using 22 years of weather station observations and surface energy fluxes. The glaciers are located only 30 km apart, but have different local climates; Taylor Glacier is generally drier and windier than Commonwealth Glacier, which receives more snowfall due to its proximity to the coast. Commonwealth Glacier shows more inter-annual melt variability, explained by variable albedo due to summer snowfall events. A significant increase in surface melt at Commonwealth Glacier is associated with a decrease in summer minimum albedo. Inter-annual variability in melt at both glaciers is linked to degree-days above freezing during f{\"o}hn events, occurring more frequently at Taylor Glacier. At Taylor Glacier melt occurs most often with positive air temperatures, but f{\"o}hn conditions also favour sublimation, which cools the surface and prevents melt for the majority of the positive air temperatures. At Commonwealth Glacier, most of the melt instead occurs with sub-zero air temperatures, driven by strong solar radiative heating. Future melt at Taylor Glacier will likely be more sensitive to changes in f{\"o}hn events, while Commonwealth Glacier will be impacted more by changes in near coastal weather, where moisture inputs can drive cloud cover, snowfall and change albedo.</p>},
	keywords = {LTER-MCM, Antarctic glaciology, energy balance, glacier meteorology, ice/atmosphere interactions, melt-surface},
	issn = {0022-1430},
	doi = {10.1017/jog.2023.98},
	url = {https://www.cambridge.org/core/journals/journal-of-glaciology/article/meteorological-drivers-of-melt-at-two-nearby-glaciers-in-the-mcmurdo-dry-valleys-of-antarctica/2B8ED17DEC26AB5F0905BC4C7ACA02FA},
	author = {Hofsteenge, Marte G. and Cullen, Nicolas J. and Conway, Jonathan P. and Reijmer, Carleen H. and van den Broeke, Michiel R. and Katurji, Marwan}
}
@article {4837,
	title = {Meteorological connectivity from regions of high biodiversity within the McMurdo Dry Valleys of Antarctica},
	journal = {Journal of Applied Meteorology and Climatology},
	volume = {58},
	year = {2019},
	month = {11/2019},
	pages = {2437 - 2452},
	abstract = {<p>Meteorological connectivity between biological hot spots of the McMurdo Dry Valleys (MDVs) of Antarctica is thought to play a role in species distribution and abundance through the aeolian transport of bioaerosols. Understanding the potential role of such meteorological connectivity requires an understanding of near-surface wind flow within and between valley airsheds. To address this, we applied Lagrangian wind trajectory modeling to mesoscale (spatial resolution of ~1 km) weather model output to predict connectivity pathways, focusing on regions of high biodiversity. Our models produce maps of a likelihood metric of wind connectivity that demonstrate the synoptic and mesoscale dependence of connections between local, near-local, and nonlocal areas on wind transport, modulated by synoptic weather and topographic forcing. These connectivity areas can have spatial trends modulated by the synoptic weather patterns and locally induced topographically forced winds. This method is transferrable to other regions of Antarctica for broader terrestrial, coastal, and offshore ecological connectivity research. Also, our analysis and methods can inform better placement of aeolian dust and bioaerosol samplers in the McMurdo Dry Valleys, provide preliminary guidelines behind the meteorological controls of sediment transport and smaller particle distribution, and present quantifiable knowledge informing new hypotheses around the potential of wind acting as a physical driver for biological connectivity in the MDVs.</p>},
	keywords = {LTER-MCM, Antarctica, atmosphere, biosphere-atmosphere interaction, mesoscale models, mesoscale processes, numerical analysis/modeling},
	issn = {1558-8424},
	doi = {10.1175/JAMC-D-18-0336.1},
	url = {https://journals.ametsoc.org/view/journals/apme/58/11/jamc-d-18-0336.1.xml},
	author = {Katurji, Marwan and Khan, Basit and Sprenger, Michael A. and Datta, Rajasweta and Joy, Kurt and Zawar-Reza, Peyman and Ian Hawes}
}
