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Detection and Inventory of Intense Pyroconvection in Western North America using GOES-15 Daytime Infrared Data

机译:使用GOO-15白天红外数据检测和北美激烈的发球电机检测和清点

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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. Acloud-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.
机译:强烈的野火偶尔会产生火灾触发的风暴,称为Pyrocumulonimbus(Pyrocb),可将烟雾颗粒和痕量气体注入上层和较低的平流层(UTL)。本研究开发了使用来自船上的成像器的三个红外(IR)通道的第一个PyroCB检测算法(GES-15)。该算法首先通过长波IR亮度温度识别主动火灾附近的深度对流,区分中间体和UTLS注射。在白天期间,独特的PyroCB微药物性质的特征在于中波亮度温度,该温度明显大于龙波,​​允许从其他深对流中分离Pyrocb。 Acloud - 不透明度测试可降低潜在的假检测。在北美的2013年火季期间将该算法应用于88激烈的野火,导致在传统对流中的单个激烈事件,Pyrocb以及多重,短寿命脉冲的单个激烈事件的成功检测。与社区库存的比较表明该算法捕获了大多数PyroCB。主要限制是Pyrocb砧座相对于西部像素尺寸可以小,尤其是在具有大观察角度的区域中。该算法对来自传统对流的一些假阳性也敏感,可摄取烟雾或呈现极端上升速度。总共26个PyroCB事件进行了清点,其中包括31个单独的脉冲,所有这些都可以将烟雾注入UTL。以前没有记录过六个库存激烈的PyroCB。该算法的近实时应用可以扩展到其他地区和下一代地静止传感器,为PyroCB和火灾检测提供了显着的优势。

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