<?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%">Katurji, Marwan</style></author><author><style face="normal" font="default" size="100%">Khan, Basit</style></author><author><style face="normal" font="default" size="100%">Sprenger, Michael A.</style></author><author><style face="normal" font="default" size="100%">Datta, Rajasweta</style></author><author><style face="normal" font="default" size="100%">Joy, Kurt</style></author><author><style face="normal" font="default" size="100%">Zawar-Reza, Peyman</style></author><author><style face="normal" font="default" size="100%">Ian Hawes</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Meteorological connectivity from regions of high biodiversity within the McMurdo Dry Valleys of Antarctica</style></title><secondary-title><style face="normal" font="default" size="100%">Journal of Applied Meteorology and Climatology</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Antarctica</style></keyword><keyword><style  face="normal" font="default" size="100%">atmosphere</style></keyword><keyword><style  face="normal" font="default" size="100%">biosphere-atmosphere interaction</style></keyword><keyword><style  face="normal" font="default" size="100%">mesoscale models</style></keyword><keyword><style  face="normal" font="default" size="100%">mesoscale processes</style></keyword><keyword><style  face="normal" font="default" size="100%">numerical analysis/modeling</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2019</style></year><pub-dates><date><style  face="normal" font="default" size="100%">11/2019</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">https://journals.ametsoc.org/view/journals/apme/58/11/jamc-d-18-0336.1.xml</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">58</style></volume><pages><style face="normal" font="default" size="100%">2437 - 2452</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;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.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">11</style></issue></record></records></xml>