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A zoomed-in POES NOAA-AVHRR one-kilometer spatial resolution enhanced 10.8 µm IR channel image over southwestern Texas on 9 May 2003 at 2102 UTC. The enhanced-V quantitative parameters are labeled in the four panels (a) TMIN (K) and TMAX (K) (b) TDIFF (K) and DIST (KM) (c) DISTARMS (KM) and ANGLEARMS (Degrees), and (d) ORIENTATION.
Contexts in source publication
Context 1
... is usually observed downwind of TMIN and is enclosed by the V-feature region. Figure 2a shows a zoomed-in image of Figure 1a with TMIN and TMAX labeled. For this enhanced-V case, TMIN and TMAX were observed to have values of 192 K (-81° C) and 212 K (-61° C), respectively. ...
Context 2
... quantitative parameter of the enhanced-V is the distance between TMIN and TMAX (DIST). Figure 2b displays an enhanced-V with TDIFF and DIST applied and labeled. For this case, TDIFF and DIST were observed to have values of 20 K and 7 km, respectively. ...
Context 3
... is the angle between the two V-arms. Figure 2c shows DISTARMS and ANGLEARMS applied and labeled to an image; DISTARMS and ANGLEARMS were observed to have values of 22.5 km and 72 degrees, respectively. ...
Context 4
... quadrant was not counted more than once for each enhanced-V. Figure 2d shows an example of the quantitative parameter ORIENTATION. For this enhanced-V case, the enhanced-V orientation was determined to be the northeast quadrant because there were 49 degrees of angle present in the northeast quadrant, while only 23 degrees of angle were present in the southeast quadrant. ...
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... Using SRSOR data likely mitigates the latter problem; however, the raised concerns in mAMV quality justify the need to experiment with NWP model results to ensure that observed mAMV flow fields follow understood upper-level deep convective dynamics. The ARW model simulation is also used to test the associa- tion of the observed mAMV dynamics with the hy- pothesized obstacle flow-related dynamics of the enhanced-V signature (Brunner et al. 2007) and the generation mechanism of vertical vorticity at the cloud top for both supercell and nonsupercell thunderstorms. The mechanism of vertical vorticity generation is ex- plored using the nonlinearized vertical vorticity equa- tion, neglecting the effects of the Coriolis force, which is expressed as ...
... Stretching is also likely the tendency that causes larger vertical vorticity values to be observed downstream of the CTD maxi- mum, rather than a direct juxtaposition, as horizontal divergence (convergence) reduces (increases) the cur- rent magnitude of the vertical vorticity values. The lack of solenoidal generation of vorticity highlights the lack of obstacle-flow-related influences [such as those sus- pected to be involved in the development of the enhanced-V signature in GOES IR imagery; Brunner et al. (2007)] on the development of the vertical vorticity in the CTV couplet signature and is consistent with previous works on the dynamics of supercells ( Rotunno and Klemp 1982;Wiesmann andKlemp 1982, 1984). The same planar and cross-sectional views are ana- lyzed with a nonsupercell storm with no mean flow (Figs. ...
Super Rapid Scan Operations for the Geostationary Operational Environmental Satellite (GOES) R series (SRSOR) using GOES-14 have made experimentation with 1-min time-step data possible prior to the launch of the new satellite. A mesoscale atmospheric motion vector (mAMV) program is utilized in SRSOR with a Barnes analysis to produce objectively analyzed flow fields at the cloud tops of deep convection. Two non-supercell and four supercell storm cases are analyzed. Data from the SRSOR mAMV analysis are compared with both multi-Doppler analyses when available and idealized convection cases within the Weather Research and Forecasting (WRF) Model framework. It is found that using SRSOR data provides several additional trackable targets to produce mAMVs in rapidly "bubbling'' regions at the deep convective cloud-top level not previously available at lower temporal resolutions (, 1 min). Results also show that supercell storm cases produce long-lived maxima in SRSOR cloud-top divergence (CTD) and "couplet'' signatures in cloud-top vorticity (CTV), which when compared with idealized WRF Model simulations appear to form as a result of environmental horizontal vorticity tilting. Nonsupercell convection in contrast produced weaker, short-lived CTD signatures and no "CTV couplet'' signatures. These case study results suggest that with SRSOR data it might be possible to uniquely identify supercells using only mAMV-derived flow fields.
Above-anvil cirrus plumes (AACPs) in midlatitude convection are important indicators of severe storms and stratospheric hydration events. Recent studies of AACPs have shown large variability in their characteristics, although many of the causes remain unknown. Notably, some AACPs appear equally as cold (or colder) than the broader storm top when compared to the more frequently observed warm AACP feature in infrared satellite imagery. To confidently identify the presence of an AACP, trained experts utilize infrared imagery to support the primary source of AACP identification, visible imagery. Thus, nighttime AACPs are often left unidentified due to unavailable visible imagery, especially for cold AACPs. In this study, 89 warm and 89 cold AACPs from 1-min GOES-16 satellite imagery coupled with ground-based radar observations and reanalysis data are comparatively evaluated to answer the following research questions: 1) Why do some AACPs exhibit a warm feature in infrared imagery while others do not, and 2) what observable storm and environment differences exist between warm and cold AACPs? It is found that cold AACPs tend to occur in tropical environments, which feature higher, cold-point tropopauses. Conversely, warm AACPs tend to occur in midlatitude environments, with lower tropopauses accompanied by an isothermal region (or tropopause inversion layer) in the lower stratosphere. Similar storm characteristics are found for warm and cold AACP events, implying that infrared temperature variability is driven by environmental differences. Together, these results suggest that cold AACPs are predominantly tropospheric phenomena, while warm AACPs reside in the lower stratosphere.
Significance Statement
The purpose of this study is to determine why some storms with a specific cloud-top feature exhibit a broad warm spot in infrared satellite imagery while others appear cold. This is important because storms with this specific cloud-top feature, whether warm or cold, produce much more severe weather than most other storms. These cloud-top features are also potentially indicative of increased water vapor in the stratosphere, which results in warming of Earth’s climate. Our results help us better understand storms that are frequently severe and suggest that the storms with cold features are less important to understanding stratospheric water vapor and climate change.
