Validation of Satellite-Based Objective Overshooting Cloud-Top Detection Methods Using CloudSat Cloud Profiling Radar Observations

Bedka, Kristopher M.; Dworak, Richard; Brunner, Jason; Feltz, Wayne F.

doi:10.1175/jamc-d-11-0131.1

Cited by 39 publications

(37 citation statements)

References 15 publications

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“…IRW-texture OT detection method Bedka et al (2010) describe the IRW-texture OT detection algorithm in full detail, but a short summary is provided here for context. The algorithm was designed to accurately identify pixels penetrating through the tropopause region and its output was not expected to specifically be a ''severe weather detection'' product.…”

Section: Methodsmentioning

confidence: 99%

“…The 30-km match statistics are slightly lower than in Bedka's (2011) study over Europe; however, OTs were detected near tornadic storms 32% more often over the United States. This difference could be related to the fact that large low-level wind shear is much more common than strong convective available potential energy (CAPE) over the European domain (Brooks et al 2003;Bedka 2011). Therefore, tornadic storms associated with weaker updrafts relative to storms that produce severe hail-winds, resulting in a less prominent or possibly nonexistent OT signature in IRW BT imagery.…”

Section: Comparison Between Spc Severe Weather Reports and Ot Detementioning

confidence: 99%

“…The volume of data used in this study far exceeds that from previous work, which had primarily relied on a limited sample size of case studies, or in the case of Bedka (2011), a relatively small severe weather event database.…”

Section: Introductionmentioning

confidence: 99%

“…An objective OT detection product has been developed that focuses on the attributes of OTs as depicted in GOES-12 Imager IRW imagery (Bedka et al 2010). Clusters of pixels significantly colder than the surrounding anvil cloud with a diameter consistent with commonly observed OTs are identified through this approach.…”

Section: Introductionmentioning

confidence: 99%

“…The accuracy of this so-called IRW-texture method has been quantified relative to OT signatures depicted in National Aeronautics and Space Administration (NASA) CloudSat Cloud Profiling Radar (CPR) data and cloudresolving NWP model output (Bedka et al 2010;Bedka et al 2012). While these studies provide relatively consistent false-alarm rate (FAR) statistics for the OT detection product, neither utilized a large sample size of geostationary satellite imagery over the CONUS that is currently available to operational weather forecasters; thus, these FARs may not be representative of nearreal-time CONUS product output and more validation must be done.…”

Section: Introductionmentioning

confidence: 99%

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Comparison between GOES-12 Overshooting-Top Detections, WSR-88D Radar Reflectivity, and Severe Storm Reports

Dworak

Bedka

Brunner

et al. 2012

Weather and Forecasting

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Studies have found that convective storms with overshooting-top (OT) signatures in weather satellite imagery are often associated with hazardous weather, such as heavy rainfall, tornadoes, damaging winds, and large hail. An objective satellite-based OT detection product has been developed using 11-mm infrared window (IRW) channel brightness temperatures (BTs) for the upcoming R series of the Geostationary Operational Environmental Satellite (GOES-R) Advanced Baseline Imager. In this study, this method is applied to GOES-12 IRW data and the OT detections are compared with radar data, severe storm reports, and severe weather warnings over the eastern United States. The goals of this study are to 1) improve forecaster understanding of satellite OT signatures relative to commonly available radar products, 2) assess OT detection product accuracy, and 3) evaluate the utility of an OT detection product for diagnosing hazardous convective storms. The coevolution of radar-derived products and satellite OT signatures indicates that an OT often corresponds with the highest radar echo top and reflectivity maximum aloft. Validation of OT detections relative to composite reflectivity indicates an algorithm false-alarm ratio of 16%, with OTs within the coldest IRW BT range (,200 K) being the most accurate. A significant IRW BT minimum typically present with an OT is more often associated with heavy precipitation than a region with a spatially uniform BT. Severe weather was often associated with OT detections during the warm season (April-September) and over the southern United States. The severe weather to OT relationship increased by 15% when GOES operated in rapid-scan mode, showing the importance of high temporal resolution for observing and detecting rapidly evolving cloud-top features. Comparison of the earliest OT detection associated with a severe weather report showed that 75% of the cases occur before severe weather and that 42% of collocated severe weather reports had either an OT detected before a severe weather warning or no warning issued at all. The relationships between satellite OT signatures, severe weather, and heavy rainfall shown in this paper suggest that 1) when an OT is detected, the particular storm is likely producing heavy rainfall and/or possibly severe weather; 2) an objective OT detection product can be used to increase situational awareness and forecaster confidence that a given storm is severe; and 3) this product may be particularly useful in regions with insufficient radar coverage.

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Section: Methodsmentioning

confidence: 99%

Section: Comparison Between Spc Severe Weather Reports and Ot Detementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Comparison between GOES-12 Overshooting-Top Detections, WSR-88D Radar Reflectivity, and Severe Storm Reports

Dworak

Bedka

Brunner

et al. 2012

Weather and Forecasting

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Convective vertical velocity and cloud internal vertical structure: An A‐Train perspective

Luo

Jeyaratnam

Iwasaki

et al. 2014

Geophysical Research Letters

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This paper describes a novel use of A-Train observations to estimate vertical velocities for actively growing convective plumes and to relate them to cloud internal vertical structure. Convective vertical velocity is derived from time-delayed (1-2 min) IR measurements from MODIS and IIR. Convective vertical velocities are found to be clustered around 2-4 m/s but the distributions are positively skewed with long tails extending to larger values. Land convection during the 13:30 overpasses has higher vertical velocities than those during the 1:30 overpasses; oceanic convection shows the opposite, albeit smaller, contrast. Our results also show that convection with larger vertical velocity tends to transport larger precipitation-size particle and/or greater amount of water substance to higher altitude and produces heavier rainfall. Finally, we discuss the implications of this study for the designs of future space-borne missions that focus on fast-evolving processes such as those related to clouds and precipitation.

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Characterizing tropical overshooting deep convection from joint analysis of CloudSat and geostationary satellite observations

Takahashi

Luo

2014

JGR Atmospheres

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[1] Tropical overshooting deep convection (ODC) plays an important role in affecting the heat and constituent budgets of the upper troposphere and lower stratosphere. This study investigates the properties and behaviors of such intense deep convection using a combination of CloudSat observations and geostationary satellite data. Our study approaches the subject from two unique perspectives: first, W-band cloud profiling radar (CPR) observations from CloudSat are used, which add to our knowledge of the internal vertical structure of tropical ODC; second, each snapshot observation from CloudSat is cast into the time evolution of the convective systems through joint analysis of geostationary satellite data, which provides a lifecycle view of tropical ODC. Climatology of tropical ODC based on CloudSat data is first presented and compared with previous works. Various parameters from CloudSat observations pertaining to cloud vertical extent, convective intensity, and convective environment are analyzed. Although results broadly agree with previous studies, we show that CloudSat CPR is capable of capturing both small cloud particles and large precipitation-size particles, thus presenting a more complete depiction of the internal vertical structure of tropical ODC. Geostationary satellite observations are analyzed in conjunction with CloudSat data to identify the life stage of the convective systems (CSs) in which ODC is embedded. ODC associated with the growing, mature, and dissipating stage of the CSs represents, respectively, 66.2%, 33.4%, and 0.4% of the total population. Convective intensity of the ODC is found to be stronger during the growing stage than the mature stage.Citation: Takahashi, H., and Z. J. Luo (2014), Characterizing tropical overshooting deep convection from joint analysis of CloudSat and geostationary satellite observations,

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Validation of Satellite-Based Objective Overshooting Cloud-Top Detection Methods Using CloudSat Cloud Profiling Radar Observations

Cited by 39 publications

References 15 publications

Comparison between GOES-12 Overshooting-Top Detections, WSR-88D Radar Reflectivity, and Severe Storm Reports

Comparison between GOES-12 Overshooting-Top Detections, WSR-88D Radar Reflectivity, and Severe Storm Reports

Convective vertical velocity and cloud internal vertical structure: An A‐Train perspective

Characterizing tropical overshooting deep convection from joint analysis of CloudSat and geostationary satellite observations

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