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Detection and Inventory of Intense Pyroconvection in Western North America using GOES-15 Daytime Infrared Data
Intense wildfires occasionally generate fire-triggered storms, known as pyrocumulonimbus (pyroCb), that can inject smoke particles and trace gases into the upper troposphere and lower stratosphere (UTLS). This study develops the first pyroCb detection algorithm using three infrared (IR) channels fro...
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Published in: | Journal of applied meteorology and climatology 2017-02, Vol.56 (2), p.471-493 |
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container_title | Journal of applied meteorology and climatology |
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creator | Peterson, David A. Fromm, Michael D. Solbrig, Jeremy E. Hyer, Edward J. Surratt, Melinda L. Campbell, James R. |
description | Intense wildfires occasionally generate fire-triggered storms, known as pyrocumulonimbus (pyroCb), that can inject smoke particles and trace gases into the upper troposphere and lower stratosphere (UTLS). This study develops the first pyroCb detection algorithm using three infrared (IR) channels from the imager on board GOES-West (GOES-15). The algorithm first identifies deep convection near active fires via the longwave IR brightness temperature, distinguishing between midtropospheric and UTLS injections. During daytime, unique pyroCb microphysical properties are characterized by a medium-wave brightness temperature that is significantly larger than that in the longwave, allowing for separation of pyroCb from other deep convection. A cloud-opacity test reduces potential false detections. Application of this algorithm to 88 intense wildfires observed during the 2013 fire season in western North America resulted in successful detection of individual intense events, pyroCb embedded within traditional convection, and multiple, short-lived pulses of pyroconvective activity. Comparisons with a community inventory indicate that this algorithm captures the majority of pyroCb. The primary limitation is that pyroCb anvils can be small relative to GOES-West pixel size, especially in regions with large viewing angles. The algorithm is also sensitive to some false positives from traditional convection that either ingests smoke or exhibits extreme updraft velocities. A total of 26 pyroCb events are inventoried, including 31 individual pulses, all of which can inject smoke into the UTLS. Six of the inventoried intense pyroCb were not previously documented. Near-real-time application of this algorithm can be extended to other regions and to next-generation geostationary sensors, which offer significant advantages for pyroCb and fire detection. |
doi_str_mv | 10.1175/JAMC-D-16-0226.1 |
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This study develops the first pyroCb detection algorithm using three infrared (IR) channels from the imager on board GOES-West (GOES-15). The algorithm first identifies deep convection near active fires via the longwave IR brightness temperature, distinguishing between midtropospheric and UTLS injections. During daytime, unique pyroCb microphysical properties are characterized by a medium-wave brightness temperature that is significantly larger than that in the longwave, allowing for separation of pyroCb from other deep convection. A cloud-opacity test reduces potential false detections. Application of this algorithm to 88 intense wildfires observed during the 2013 fire season in western North America resulted in successful detection of individual intense events, pyroCb embedded within traditional convection, and multiple, short-lived pulses of pyroconvective activity. Comparisons with a community inventory indicate that this algorithm captures the majority of pyroCb. The primary limitation is that pyroCb anvils can be small relative to GOES-West pixel size, especially in regions with large viewing angles. The algorithm is also sensitive to some false positives from traditional convection that either ingests smoke or exhibits extreme updraft velocities. A total of 26 pyroCb events are inventoried, including 31 individual pulses, all of which can inject smoke into the UTLS. Six of the inventoried intense pyroCb were not previously documented. Near-real-time application of this algorithm can be extended to other regions and to next-generation geostationary sensors, which offer significant advantages for pyroCb and fire detection.</description><identifier>ISSN: 1558-8424</identifier><identifier>EISSN: 1558-8432</identifier><identifier>DOI: 10.1175/JAMC-D-16-0226.1</identifier><language>eng</language><publisher>Boston: American Meteorological Society</publisher><subject>Algorithms ; Anvils ; Brightness ; Brightness temperature ; Clouds ; Convection ; Data processing ; Daytime ; Detection ; Fire detection ; Fires ; Gases ; Laboratories ; Lower stratosphere ; Mathematical models ; Meteorological satellites ; Onboard ; Opacity ; Outdoor air quality ; Regions ; Remote sensing ; Sensors ; Smoke ; Smoke particles ; Storms ; Stratosphere ; Studies ; Surface radiation temperature ; Temperature ; Temperature effects ; Trace gases ; Troposphere ; Upper troposphere ; Wildfires</subject><ispartof>Journal of applied meteorology and climatology, 2017-02, Vol.56 (2), p.471-493</ispartof><rights>2017 American Meteorological Society</rights><rights>Copyright American Meteorological Society Feb 2017</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c335t-648f9d817f3bc676db6c4294ce555760e2ee2eb9f084ad7e35833714ef9831fc3</citedby><cites>FETCH-LOGICAL-c335t-648f9d817f3bc676db6c4294ce555760e2ee2eb9f084ad7e35833714ef9831fc3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.jstor.org/stable/pdf/26179883$$EPDF$$P50$$Gjstor$$H</linktopdf><linktohtml>$$Uhttps://www.jstor.org/stable/26179883$$EHTML$$P50$$Gjstor$$H</linktohtml><link.rule.ids>314,780,784,27924,27925,58238,58471</link.rule.ids></links><search><creatorcontrib>Peterson, David A.</creatorcontrib><creatorcontrib>Fromm, Michael D.</creatorcontrib><creatorcontrib>Solbrig, Jeremy E.</creatorcontrib><creatorcontrib>Hyer, Edward J.</creatorcontrib><creatorcontrib>Surratt, Melinda L.</creatorcontrib><creatorcontrib>Campbell, James R.</creatorcontrib><title>Detection and Inventory of Intense Pyroconvection in Western North America using GOES-15 Daytime Infrared Data</title><title>Journal of applied meteorology and climatology</title><description>Intense wildfires occasionally generate fire-triggered storms, known as pyrocumulonimbus (pyroCb), that can inject smoke particles and trace gases into the upper troposphere and lower stratosphere (UTLS). This study develops the first pyroCb detection algorithm using three infrared (IR) channels from the imager on board GOES-West (GOES-15). The algorithm first identifies deep convection near active fires via the longwave IR brightness temperature, distinguishing between midtropospheric and UTLS injections. During daytime, unique pyroCb microphysical properties are characterized by a medium-wave brightness temperature that is significantly larger than that in the longwave, allowing for separation of pyroCb from other deep convection. A cloud-opacity test reduces potential false detections. Application of this algorithm to 88 intense wildfires observed during the 2013 fire season in western North America resulted in successful detection of individual intense events, pyroCb embedded within traditional convection, and multiple, short-lived pulses of pyroconvective activity. Comparisons with a community inventory indicate that this algorithm captures the majority of pyroCb. The primary limitation is that pyroCb anvils can be small relative to GOES-West pixel size, especially in regions with large viewing angles. The algorithm is also sensitive to some false positives from traditional convection that either ingests smoke or exhibits extreme updraft velocities. A total of 26 pyroCb events are inventoried, including 31 individual pulses, all of which can inject smoke into the UTLS. Six of the inventoried intense pyroCb were not previously documented. Near-real-time application of this algorithm can be extended to other regions and to next-generation geostationary sensors, which offer significant advantages for pyroCb and fire detection.</description><subject>Algorithms</subject><subject>Anvils</subject><subject>Brightness</subject><subject>Brightness temperature</subject><subject>Clouds</subject><subject>Convection</subject><subject>Data processing</subject><subject>Daytime</subject><subject>Detection</subject><subject>Fire detection</subject><subject>Fires</subject><subject>Gases</subject><subject>Laboratories</subject><subject>Lower stratosphere</subject><subject>Mathematical models</subject><subject>Meteorological satellites</subject><subject>Onboard</subject><subject>Opacity</subject><subject>Outdoor air quality</subject><subject>Regions</subject><subject>Remote sensing</subject><subject>Sensors</subject><subject>Smoke</subject><subject>Smoke 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Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Peterson, David A.</au><au>Fromm, Michael D.</au><au>Solbrig, Jeremy E.</au><au>Hyer, Edward J.</au><au>Surratt, Melinda L.</au><au>Campbell, James R.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Detection and Inventory of Intense Pyroconvection in Western North America using GOES-15 Daytime Infrared Data</atitle><jtitle>Journal of applied meteorology and climatology</jtitle><date>2017-02-01</date><risdate>2017</risdate><volume>56</volume><issue>2</issue><spage>471</spage><epage>493</epage><pages>471-493</pages><issn>1558-8424</issn><eissn>1558-8432</eissn><abstract>Intense wildfires occasionally generate fire-triggered storms, known as pyrocumulonimbus (pyroCb), that can inject smoke particles and trace gases into the upper troposphere and lower stratosphere (UTLS). This study develops the first pyroCb detection algorithm using three infrared (IR) channels from the imager on board GOES-West (GOES-15). The algorithm first identifies deep convection near active fires via the longwave IR brightness temperature, distinguishing between midtropospheric and UTLS injections. During daytime, unique pyroCb microphysical properties are characterized by a medium-wave brightness temperature that is significantly larger than that in the longwave, allowing for separation of pyroCb from other deep convection. A cloud-opacity test reduces potential false detections. Application of this algorithm to 88 intense wildfires observed during the 2013 fire season in western North America resulted in successful detection of individual intense events, pyroCb embedded within traditional convection, and multiple, short-lived pulses of pyroconvective activity. Comparisons with a community inventory indicate that this algorithm captures the majority of pyroCb. 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subjects | Algorithms Anvils Brightness Brightness temperature Clouds Convection Data processing Daytime Detection Fire detection Fires Gases Laboratories Lower stratosphere Mathematical models Meteorological satellites Onboard Opacity Outdoor air quality Regions Remote sensing Sensors Smoke Smoke particles Storms Stratosphere Studies Surface radiation temperature Temperature Temperature effects Trace gases Troposphere Upper troposphere Wildfires |
title | Detection and Inventory of Intense Pyroconvection in Western North America using GOES-15 Daytime Infrared Data |
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