{"id":307,"date":"2014-08-07T22:11:09","date_gmt":"2014-08-07T22:11:09","guid":{"rendered":"https:\/\/ejssm.org\/archives\/?p=307"},"modified":"2022-05-15T03:37:04","modified_gmt":"2022-05-15T03:37:04","slug":"vol-9-2-2014","status":"publish","type":"post","link":"https:\/\/ejssm.org\/archives\/2014\/vol-9-2-2014\/","title":{"rendered":"Vol 9-2 2014"},"content":{"rendered":"<h4>Southern Great Plains Wildfire Outbreaks<\/h4>\n<p><em>T. Todd Lindley, Gregory P. Murdoch, Jared L. Guyer, Gary D. Skwira, Kenneth J. Schneider, Seth R. Nagle, Kurt M. Van Speybroeck, Bradley R. Smith, Micah-John Beierle<\/em><\/p>\n<h4>Abstract<\/h4>\n<p>Destructive wildfire outbreaks are a preeminent natural hazard on the grass-dominated landscape of the southern Great Plains.\u00a0 These southern Great Plains wildfire outbreaks (SGPWOs) are characterized by tens of wildfires that evolve on spatial and temporal scales closely tied to the passage of midlatitude cyclones when dormant herbaceous vegetation is particularly dry and abundant.\u00a0 Ten SGPWOs inflicted tragic losses of life and property across eastern New Mexico, west Texas, and Oklahoma between December 2005 and April 2009.\u00a0 This study reviews the conditions that promoted these dangerous phenomena.\u00a0 Texas A&amp;M; Forest Service records reveal that enhanced seasonal wildfire activity and increased potential for SGPWOs typically occurs during El Ni\u00f1o Southern Oscillation cold phases (La Ni\u00f1a), especially when preceded by positive growing-season rainfall anomalies.\u00a0 The antecedent state of predominately fine grassland vegetative fuels associated with SGPWOs is quantified per Energy Release Component (ERC, fuel model G).\u00a0 Average ERC values &gt;50 (&gt;70th percentile) supported the 2005-2009 SGPWOs on the Great Plains of Texas.\u00a0 Meteorological composites that quantify mean synoptic patterns during SGPWOs are generated via Rapid Update Cycle analyses, and averaged vertical temperature, moisture, and wind profiles are presented.\u00a0 Further analyses of subsynoptic low and midlevel tropospheric temperatures and winds illustrate a tendency for wildfires to occur near 2-m and 850-hPa thermal ridges when overspread by 500-hPa wind maxima.\u00a0 The juxtaposition of these atmospheric features appears to be a useful meso-<em>\u03b1<\/em>-scale predictor of heightened wildfire risks.\u00a0 Recognition of the presented seasonal indicators toward a fire-prone regime influenced strategic preparations for the historic 2011 Texas wildfires.\u00a0 Operational use of composite pattern recognition-based forecasts in tactical decision support is demonstrated for the 27 February 2011 &#8220;firestorm&#8221;, a particularly damaging SGPWO during an unprecedented fire season.\u00a0 Average ERC values &gt;75 (&gt;95<sup>th<\/sup>\u00a0percentile) additionally supported prolonged burn periods with the passage of subsequent fire outbreak-bearing weather systems during the spring of 2011.\u00a0 Lastly, seasonal trends and the chronology of climatic and environmental signals prior to SGPWOs are highlighted, per a summary of conditions that preceded all of the 2005-2011 episodes.<\/p>\n<p>Full Text: <a href=\"https:\/\/ejssm.org\/archives\/wp-content\/uploads\/2021\/09\/vol9-2.pdf\">PDF<\/a><\/p>\n<p>Citation:<br \/>\nLindley, T. T., G. P. Murdoch, J. L. Guyer, G. D. Skwira, K. J. Schneider, S. R. Nagle, K. M. Van Speybroeck, B. R. Smith, and M.-J. Beierle, 2014:\u00a0Southern Great Plains wildfire outbreaks.\u00a0<i>Electronic J. Severe Storms Meteor.<\/i>,\u00a0<b>9<\/b>\u00a0(2), 1-43.<\/p>\n<p>Keywords:<br \/>\nfire weather, wildfires, land cover, mesoscale processes, seasonal forecasting, synoptic meteorology<\/p>\n","protected":false},"excerpt":{"rendered":"<h5>Southern Great Plains Wildfire Outbreaks<\/h5>\n<p><i>T. Todd Lindley, Gregory P. Murdoch, Jared L. Guyer, Gary D. Skwira, Kenneth J. Schneider, Seth R. Nagle, Kurt M. Van Speybroeck, Bradley R. Smith, Micah-John Beierle<\/i><\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_genesis_hide_title":false,"_genesis_hide_breadcrumbs":false,"_genesis_hide_singular_image":false,"_genesis_hide_footer_widgets":false,"_genesis_custom_body_class":"","_genesis_custom_post_class":"","_genesis_layout":"","footnotes":""},"categories":[2],"tags":[40,44,18,80,17,79],"class_list":{"0":"post-307","1":"post","2":"type-post","3":"status-publish","4":"format-standard","6":"category-article","7":"tag-fire-weather","8":"tag-land-cover","9":"tag-mesoscale-processes","10":"tag-seasonal-forecasting","11":"tag-synoptic-meteorology","12":"tag-wildfires","13":"entry"},"featured_image_src":null,"featured_image_src_square":null,"author_info":{"display_name":"Elke","author_link":"https:\/\/ejssm.org\/archives\/author\/elke\/"},"_links":{"self":[{"href":"https:\/\/ejssm.org\/archives\/wp-json\/wp\/v2\/posts\/307","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/ejssm.org\/archives\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/ejssm.org\/archives\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/ejssm.org\/archives\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/ejssm.org\/archives\/wp-json\/wp\/v2\/comments?post=307"}],"version-history":[{"count":5,"href":"https:\/\/ejssm.org\/archives\/wp-json\/wp\/v2\/posts\/307\/revisions"}],"predecessor-version":[{"id":903,"href":"https:\/\/ejssm.org\/archives\/wp-json\/wp\/v2\/posts\/307\/revisions\/903"}],"wp:attachment":[{"href":"https:\/\/ejssm.org\/archives\/wp-json\/wp\/v2\/media?parent=307"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/ejssm.org\/archives\/wp-json\/wp\/v2\/categories?post=307"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/ejssm.org\/archives\/wp-json\/wp\/v2\/tags?post=307"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}