{"id":446,"date":"2026-09-08T15:28:17","date_gmt":"2026-09-08T20:28:17","guid":{"rendered":"https:\/\/cimss.ssec.wisc.edu\/probsevere\/?p=446"},"modified":"2026-09-08T16:15:44","modified_gmt":"2026-09-08T21:15:44","slug":"september-squall-lines","status":"publish","type":"post","link":"https:\/\/cimss.ssec.wisc.edu\/probsevere\/2026\/09\/08\/september-squall-lines\/","title":{"rendered":"September Squall Lines"},"content":{"rendered":"\n<p class=\"wp-block-paragraph\">The balmy airmass across much of the eastern U.S. provided the fuel for severe storms across the Great Lakes and Mid-Atlantic regions for a while now.<\/p>\n\n\n\n<figure class=\"wp-block-image size-large\"><img loading=\"lazy\" decoding=\"async\" width=\"1024\" height=\"791\" src=\"https:\/\/cimss.ssec.wisc.edu\/probsevere\/wp-content\/uploads\/sites\/29\/2026\/09\/image-1024x791.png\" alt=\"\" class=\"wp-image-447\" srcset=\"https:\/\/cimss.ssec.wisc.edu\/probsevere\/wp-content\/uploads\/sites\/29\/2026\/09\/image-1024x791.png 1024w, https:\/\/cimss.ssec.wisc.edu\/probsevere\/wp-content\/uploads\/sites\/29\/2026\/09\/image-300x232.png 300w, https:\/\/cimss.ssec.wisc.edu\/probsevere\/wp-content\/uploads\/sites\/29\/2026\/09\/image-767x593.png 767w, https:\/\/cimss.ssec.wisc.edu\/probsevere\/wp-content\/uploads\/sites\/29\/2026\/09\/image.png 1100w\" sizes=\"auto, (max-width: 1024px) 100vw, 1024px\" \/><figcaption class=\"wp-element-caption\">18Z HRRR analysis of theta-e across the CONUS.<\/figcaption><\/figure>\n\n\n\n<p class=\"wp-block-paragraph\">ProbSevere v4 (PSv4) uses spatial AI methods and MRMS, lightning, and HRRR environmental information to predict the probability of severe weather in the next 45 minutes. NSSL is working on extending probabilistic predictions out to 6 hours using these data sources and more.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">These storms in Michigan and Ohio formed along and traversed a stationary boundary of high theta-e gradient. The PSv4 model did a commendable job highlighting the severe-wind producing segments, particularly in Michigan and eastern Ohio and southwest Pennsylvania. Once storms weakened in reflectivity and lightning activity in northern Ohio, probabilities also weakened (&lt; 25%), but there were sporadic severe wind reports.<\/p>\n\n\n\n<figure class=\"wp-block-video\"><video height=\"720\" style=\"aspect-ratio: 1280 \/ 720;\" width=\"1280\" controls src=\"https:\/\/cimss.ssec.wisc.edu\/probsevere\/wp-content\/uploads\/sites\/29\/2026\/09\/ps_20260903.mp4\"><\/video><figcaption class=\"wp-element-caption\">ProbSevere v4 probabilities (contours), NWS severe weather warnings (orange and red polygons), severe local storm reports 0-45 minutes after image time, and MRMS MergedReflectivity (background).<\/figcaption><\/figure>\n\n\n\n<p class=\"wp-block-paragraph\">Later on, the AI model correctly captured numerous severe wind reports (plotted 45 minutes after image time) in the main storm segments in West Virginia and Virginia\/Maryland.<\/p>\n\n\n\n<figure class=\"wp-block-video\"><video height=\"720\" style=\"aspect-ratio: 1280 \/ 720;\" width=\"1280\" controls src=\"https:\/\/cimss.ssec.wisc.edu\/probsevere\/wp-content\/uploads\/sites\/29\/2026\/09\/ps_20260904.mp4\"><\/video><figcaption class=\"wp-element-caption\">ProbSevere v4 probabilities (contours), NWS severe weather warnings (orange and red polygons), severe local storm reports 0-45 minutes after image time, and MRMS MergedReflectivity (background).<\/figcaption><\/figure>\n\n\n\n<p class=\"wp-block-paragraph\">On the Pennsylvania \/ New Jersey border, we see a small cluster of storms that had high probabilities ahead of it. The tree-based PSv3 never achieved a probability greater than 17%, whereas PSv4 had &gt; 75%. At this time, 4 minutes before a severe thunderstorm warning was issued, all of the reports in the next 45 minutes were within the \u2265 50% contour.<\/p>\n\n\n\n<figure class=\"wp-block-image size-large\"><img loading=\"lazy\" decoding=\"async\" width=\"937\" height=\"1024\" src=\"https:\/\/cimss.ssec.wisc.edu\/probsevere\/wp-content\/uploads\/sites\/29\/2026\/09\/PS_20260904-0430-937x1024.png\" alt=\"\" class=\"wp-image-451\" srcset=\"https:\/\/cimss.ssec.wisc.edu\/probsevere\/wp-content\/uploads\/sites\/29\/2026\/09\/PS_20260904-0430-937x1024.png 937w, https:\/\/cimss.ssec.wisc.edu\/probsevere\/wp-content\/uploads\/sites\/29\/2026\/09\/PS_20260904-0430-274x300.png 274w, https:\/\/cimss.ssec.wisc.edu\/probsevere\/wp-content\/uploads\/sites\/29\/2026\/09\/PS_20260904-0430-767x839.png 767w, https:\/\/cimss.ssec.wisc.edu\/probsevere\/wp-content\/uploads\/sites\/29\/2026\/09\/PS_20260904-0430.png 1084w\" sizes=\"auto, (max-width: 937px) 100vw, 937px\" \/><figcaption class=\"wp-element-caption\">ProbSevere v4 probabilities (contours), severe local storm reports 0-45 minutes after image time, and MRMS MergedReflectivity (background) for storms in eastern Pennsylvania.<\/figcaption><\/figure>\n\n\n\n<p class=\"wp-block-paragraph\">On September 5th, moderate shear, excellent CAPE, and a triggering cold front produced numerous damaging wind gusts. PSv4 again did well with these convective clusters, particularly in the Carolinas.<\/p>\n\n\n\n<figure class=\"wp-block-video\"><video height=\"720\" style=\"aspect-ratio: 1280 \/ 720;\" width=\"1280\" controls src=\"https:\/\/cimss.ssec.wisc.edu\/probsevere\/wp-content\/uploads\/sites\/29\/2026\/09\/ps_20260905.mp4\"><\/video><\/figure>\n","protected":false},"excerpt":{"rendered":"<p>The balmy airmass across much of the eastern U.S. provided the fuel for severe storms across the Great Lakes and Mid-Atlantic regions for a while now. ProbSevere v4 (PSv4) uses spatial AI methods and MRMS, lightning, and HRRR environmental information to predict the probability of severe weather in the next 45 minutes. NSSL is working [&hellip;]<\/p>\n","protected":false},"author":14,"featured_media":451,"comment_status":"closed","ping_status":"","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[5],"tags":[6],"class_list":["post-446","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-psv4","tag-psv4"],"acf":[],"_links":{"self":[{"href":"https:\/\/cimss.ssec.wisc.edu\/probsevere\/wp-json\/wp\/v2\/posts\/446","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/cimss.ssec.wisc.edu\/probsevere\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/cimss.ssec.wisc.edu\/probsevere\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/cimss.ssec.wisc.edu\/probsevere\/wp-json\/wp\/v2\/users\/14"}],"replies":[{"embeddable":true,"href":"https:\/\/cimss.ssec.wisc.edu\/probsevere\/wp-json\/wp\/v2\/comments?post=446"}],"version-history":[{"count":4,"href":"https:\/\/cimss.ssec.wisc.edu\/probsevere\/wp-json\/wp\/v2\/posts\/446\/revisions"}],"predecessor-version":[{"id":456,"href":"https:\/\/cimss.ssec.wisc.edu\/probsevere\/wp-json\/wp\/v2\/posts\/446\/revisions\/456"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/cimss.ssec.wisc.edu\/probsevere\/wp-json\/wp\/v2\/media\/451"}],"wp:attachment":[{"href":"https:\/\/cimss.ssec.wisc.edu\/probsevere\/wp-json\/wp\/v2\/media?parent=446"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/cimss.ssec.wisc.edu\/probsevere\/wp-json\/wp\/v2\/categories?post=446"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/cimss.ssec.wisc.edu\/probsevere\/wp-json\/wp\/v2\/tags?post=446"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}