Overshooting Tops Research Articles

Geostationary Satellite-Based Overshooting Top Detections and Their Relationship to Severe Weather over Eastern China

Overshooting tops (OTs), prominent signatures within deep convective storms, are produced by intense updrafts and are closely linked to heavy rainfall, strong winds, and other severe weather conditions. Using an OT dataset derived from multiyear observations of precipitation radar on board the Global Precipitation Measurement core observatory as a reference, the performances of two commonly used OT detection algorithms are evaluated for the Himawari-8 and Fengyun-4A satellites. The results indicate that the infrared contour-based algorithm based on Himawari-8 is the most effective for objective OT detection in eastern China. It exhibits a probability of detection (POD) of 62.1% and a false-alarm ratio (FAR) of 36.6%, outperforming others by achieving a greater POD and a lower FAR. Furthermore, based on the severe weather records from surface meteorological stations and nearby OT detections, a strong relationship is revealed between GEO-detected OTs and the occurrence of short-term heavy rainfall (e.g., ≥20 mm h−1) and extreme wind speed (e.g., ≥17.2 m s−1) events. The OT matched percentages for these events are 61.8% and 54.0%, respectively. This suggests that GEO satellite-based OT data can serve as an important objective product for forecasters to increase their understanding of severe convective storms.

OVERSHOOTING TOP OF CONVECTIVE CLOUD IN EXTREME WEATHER EVENTS OVER JAVA REGION BASED ON VISUAL IDENTIFICATION OF HIMAWARI 8 IMAGERY

Overshooting top (OT) in convective clouds is an essential feature in extreme weather nowcasting performed by weather forecasters to represent the core location of the severe region of the convective cloud. In addition, we can estimate the location of extreme weather events by utilising OT climatology. Unfortunately, it cannot be realised in tropical Indonesia, especially on Java Island at present, because there still needs to be more research on the presence of OT in extreme weather events. This research aims to study the presence of OT in extreme weather events on Java Island using extreme weather reports and the Himawari 8 satellite data. We detect the presence or absence of OT patterns at the location of the extreme weather event with Visual identification by using a visible channel (0.64 μm) with a spatial resolution of 500 m and sandwich products. We found that about 87% of extreme weather occurred accompanied by the appearance of OT patterns from convective clouds. A parallax effect of Himawari 8 caused the detected OT location in the southwest direction of the actual location. Extreme weather events accompanied by the OT feature of convective clouds most often occur in the transitional period of the rainy to dry season (MAM) and the rainy season (DJF). Meanwhile, extreme weather events rarely occur during the dry season (JJA). Extreme weather events accompanied by OT often occur from midday to late afternoon. OT in this study has a diameter between 2-15 km during extreme weather events. A time lag between the appearance of OT and extreme weather events in Java Island gives us opportunities for approximating and nowcasting the extreme weather events.

Distribution of cross-tropopause convection within the Asian monsoon region from May through October 2017

Abstract. We constructed a database of cross-tropopause convection in the Asian monsoon region for the months of May through October of 2017 using overshooting tops (OTs), deep convective features that penetrate the local cirrus anvil layer and the local tropopause, with Meteosat-8 geostationary satellite detections. The database of 40 918 OTs represents a hemispheric record of convection covering the study domain from 10∘ S to 55∘ N and from 40 to 115∘ E. With this database, we analyzed the geographic, monthly, and altitude distribution of this convection and compared it to the convective distributions represented by satellite observations of outgoing longwave radiation (OLR) and precipitation. We find that cross-tropopause convection is most active during the months of May through August (with daily averages of these months above 300 OTs per day) and declines through September and October. Most of this convection occurs within Northern India and Southern India, the Bay of Bengal, and the Indian Ocean regions, which together account for 75.1 % of all OTs. We further identify distinct, differing seasonal trends within the study subregions. For the Northern India, Southern India, and Bay of Bengal regions, the distribution of OTs follows the development of the Asian monsoon, with its north–south movement across the study period. This work demonstrates that when evaluating the effects of convection on lower stratospheric composition over the Asian monsoon region, it is important to consider the impact of cross-tropopause convection specifically, as well as the contributions from both land-based and oceanic regions due to the significant geographic and monthly variation in convective activity.

Sources of concentric gravity waves generated by a moving mesoscale convective system in southern Brazil

Abstract. The studies on the sources of three concentric gravity waves (CGWs) excited by a moving mesoscale convective system (MCS) on the night of 1–2 October 2019 are investigated. These CGWs were observed using a hydroxyl (OH) all-sky imager, whereas the MCS was observed by the Geostationary Operational Environmental Satellite (GOES). Using 2D spectral analysis, we observed that the three CGWs have horizontal wavelength λH between ∼30–55 km, phase speed cH∼70–90 m s−1, and period τ∼7–12 min. Using backward ray tracing, we found that two of the CGWs were excited from convective cores within the MCS. We also found that the epicenters of the two waves were close to the tropopause positions of the ray-traced paths and nearby convective cores. Regarding the source, we verified that on this night the tropopause was ∼-80 ∘C, which was ∼10 ∘C colder than the days preceding and after the MCS and also colder than usually observed. Since the tropopause height and temperature are fundamental parameters underlying the analysis of the overshooting extent, we developed our own methodology to establish a reference tropopause that would enable a quantitative estimate of this parameter. Since the MCS (CGWs source) was moving, the overshooting convective cores were tracked in space and time. Using the tracking of the overshooting tops (OTs) in space and time with the aid of reverse ray tracing, we found that two out of the three CGWs were excited by the MCS, whereas the source of the remaining one was not directly associated with the MCS.

Characteristics of a Jumping Cirrus Retrieved From Rapid Scans by Himawari‐8

AbstractA jumping cirrus (JC) is a cloud that forms a few kilometers above an anvil cloud downwind of an overshooting top (OT). A JC transports water vapor from the troposphere into the stratosphere, where water vapor is an important greenhouse gas. However, the microphysics of JC has not been explored thus far. Herein, 2.5‐min rapid scan images obtained from the geostationary weather satellite Himawari‐8 were analyzed for JC observations. A dark plume was observed to appear suddenly above an anvil cloud downwind of OTs and moved 1 km upwind within 2.5 min. The brightness temperature of the plume showed that it overlaid the anvil cloud. These characteristics matched those of a JC. The reflectivity of the assumed JC at a wavelength of 0.64 μm was 0.62, whereas that of the anvil cloud on the sunny side of the JC was 1.02. The measured reflectivities were compared to those simulated using ray tracing to retrieve the microphysics of the JC. The results indicated that dark reflectivity occurred because the JC was isolated above the anvil cloud, and bright reflectivity occurred because the anvil was illuminated by the sun and scattered light from the JC. The retrieved effective radius and ice water content of the JC were 23.4–28.0 μm and 0.12–0.15 g m−3, respectively. The JC appeared to transport 10 × 103 t of ice water above deep convection within 10 min. We applied the results to analyzing the best satellite geometry for detecting and measuring JC.

Outbreak of Negative Narrow Bipolar Events in Two Mid-Latitude Thunderstorms Featuring Overshooting Tops

Lightning discharges are the electrical production in thunderclouds. They radiate the bulk of radio signals in the very low-frequency and low-frequency (VLF/LF) that can be detected by ground-based receivers. One kind of special intra-cloud lightning discharges known as narrow bipolar events (NBEs) have been shown to be rare but closely linked to the convective activity that leads to hazardous weather. However, there is still lack of understanding on the meteorological conditions for thunderstorm-producing NBEs, especially for those of negative polarity, due to their rare occurrence. In this work, we aim to investigate what meteorological and electrical conditions of thunderclouds favor the production of negative NBEs. Combining with the VLF/LF radio signal measured by Jianghuai Area Sferic Array (JASA), S-band Doppler radar observation and balloon sounding data, two mid-latitude thunderstorms with outbreaks of negative NBEs at midnight in East China were analyzed. The comparison with the vertical radar profile shows that the bursts of negative NBEs occurred near thunderclouds with overshooting tops higher than 18 km. Manifestation of negative NBEs is observed with a relatively low spectrum width near thundercloud tops. Our findings suggest that the detection of negative NBEs would provide a unique electrical means to remotely probe overshooting tops with implications for the exchange of troposphere and stratosphere.

Pre-trained feature aggregated deep learning-based monitoring of overshooting tops using multi-spectral channels of GeoKompsat-2A advanced meteorological imagery

ABSTRACT Overshooting tops (OTs) play a crucial role in carrying tropospheric water vapor to the lower stratosphere. They are closely related to climate change as well as local severe weather conditions, such as lightning, hail, and air turbulence, which implies the importance of their detection and monitoring. While many studies have proposed threshold-based detection models using the spatial characteristics of OTs, they have shown varied performance depending on the seasonality and study areas. In this study, we propose a pre-trained feature-aggregated convolutional neural network approach for OT detection and monitoring. The proposed approach was evaluated using multi-channel data from Geo-Kompsat-2A Advanced Meteorological Imager (GK2A AMI) over East Asia. The fusion of a visible channel and multi-infrared channels enabled the proposed model to consider both physical and spatial characteristics of OTs. Six schemes were evaluated according to two types of data pre-processing methods and three types of deep learning model architectures. The best-performed scheme yielded a probability of detection (POD) of 92.1%, a false alarm ratio (FAR) of 21.5%, and a critical success index (CSI) of 0.7. The results were significantly improved when compared to those of the existing CNN-based OT detection model (POD increase by 4.8% and FAR decrease by 29.4%).

Identifying Outflow Regions of North American Monsoon Anticyclone-Mediated Meridional Transport of Convectively Influenced Air Masses in the Lower Stratosphere.

We analyzed the effect of the North American monsoon anticyclone (NAMA) on the meridional transport of summertime cross‐tropopause convective outflow by applying a trajectory analysis to a climatology of convective overshooting tops (OTs) identified in GOES satellite images, which covers the domain from 29°S to 68°N and from 205°W to 1.25°W for the time period of May to September, 2013. From this analysis, we identify seasonal development of geographically distinct outflow regions of convectively influenced air masses (CIAMs) from the NAMA circulation to the global stratosphere and quantify the associated meridional displacement of CIAMs. We find that prior to the development of the NAMA, the majority of CIAMs exit the study area in a southeastern region between 5°N and 35°N at 45°W (75.5% in May). During July and August, when the NAMA is strongest, two additional outflow regions develop that constitute the majority of outflow: 68.1% in a northeastern region between 35°N and 60°N at 45°W and 13.4% in a southwestern region between 5°N and 35°N at 145°W. The shift in the location of most CIAM outflow from the pre‐NAMA southeastern region to NAMA‐dependent northeastern and southwestern regions corresponds to a change in average meridional displacement of CIAMs from 3.3° northward in May to 24.5° northward in July and August. Meridional transport of CIAMs through persistent outflow regions from the NAMA circulation to the global stratosphere has the potential to impact global stratospheric composition beyond convective source regions.

A Deep-Learning Model for Automated Detection of Intense Midlatitude Convection Using Geostationary Satellite Images

AbstractIntense thunderstorms threaten life and property, impact aviation, and are a challenging forecast problem, particularly without precipitation-sensing radar data. Trained forecasters often look for features in geostationary satellite images such as rapid cloud growth, strong and persistent overshooting tops, U- or V-shaped patterns in storm-top temperature (and associated above-anvil cirrus plumes), thermal couplets, intricate texturing in cloud albedo (e.g., “bubbling” cloud tops), cloud-top divergence, spatial and temporal trends in lightning, and other nuances to identify intense thunderstorms. In this paper, a machine-learning algorithm was employed to automatically learn and extract salient features and patterns in geostationary satellite data for the prediction of intense convection. Namely, a convolutional neural network (CNN) was trained on 0.64-μm reflectance and 10.35-μm brightness temperature from the Advanced Baseline Imager (ABI) and flash-extent density (FED) from the Geostationary Lightning Mapper (GLM) on board GOES-16. Using a training dataset consisting of over 220 000 human-labeled satellite images, the CNN learned pertinent features that are known to be associated with intense convection and skillfully discriminated between intense and ordinary convection. The CNN also learned a more nuanced feature associated with intense convection—strong infrared brightness temperature gradients near cloud edges in the vicinity of the main updraft. A successive-permutation test ranked the most important predictors as follows: 1) ABI 10.35-μm brightness temperature, 2) ABI GLM flash-extent density, and 3) ABI 0.64-μm reflectance. The CNN model can provide forecasters with quantitative information that often foreshadows the occurrence of severe weather, day or night, over the full range of instrument-scan modes.

The RELAMPAGO Lightning Mapping Array: Overview and Initial Comparison with the Geostationary Lightning Mapper

AbstractDuring November 2018–April 2019, an 11-station very high frequency (VHF) Lightning Mapping Array (LMA) was deployed to Córdoba Province, Argentina. The purpose of the LMA was validation of the Geostationary Lightning Mapper (GLM), but the deployment was coordinated with two field campaigns. The LMA observed 2.9 million flashes (≥ five sources) during 163 days, and level-1 (VHF locations), level-2 (flashes classified), and level-3 (gridded products) datasets have been made public. The network’s performance allows scientifically useful analysis within 100 km when at least seven stations were active. Careful analysis beyond 100 km is also possible. The LMA dataset includes many examples of intense storms with extremely high flash rates (>1 s−1), electrical discharges in overshooting tops (OTs), as well as anomalously charged thunderstorms with low-altitude lightning. The modal flash altitude was 10 km, but many flashes occurred at very high altitude (15–20 km). There were also anomalous and stratiform flashes near 5–7 km in altitude. Most flashes were small (<50 km2 area). Comparisons with GLM on 14 and 20 December 2018 indicated that GLM most successfully detected larger flashes (i.e., more than 100 VHF sources), with detection efficiency (DE) up to 90%. However, GLM DE was reduced for flashes that were smaller or that occurred lower in the cloud (e.g., near 6-km altitude). GLM DE also was reduced during a period of OT electrical discharges. Overall, GLM DE was a strong function of thunderstorm evolution and the dominant characteristics of the lightning it produced.

Identifying Source Regions and the Distribution of Cross-Tropopause Convective Outflow Over North America During the Warm Season.

We analyzed the interaction between the North American monsoon anticyclone (NAMA) and summertime cross‐tropopause convective outflow by applying a trajectory analysis to a climatology of convective overshooting tops (OTs) identified in GOES satellite images, which covers the domain from 29°S to 68°N and from 205 to 1.25°W for the time period of May through September 2013. With this analysis we identified seasonally, geographically, and altitude‐dependent variability in NAMA strength and in cross‐tropopause convection that control their interaction. We find that the NAMA has the strongest impact on the circulation of convectively influenced air masses in August. Over the entire time period examined the intertropical convergence zone contributes the majority of OTs with a larger fraction of total OTs at 370 K (on average 70%) than at 400 K (on average 52%). During August at 370 K, the convectively influenced air masses within the NAMA circulation, as determined by the trajectory analysis, are primarily sourced from the intertropical convergence zone (monthly average of 66.1%), while at 400 K the Sierra Madres and the Central United States combined constitute the dominant source region (monthly average of 44.1%, compared to 36.6% of the combined Intertropical Convergence Zone regions). When evaluating the impact of cross‐tropopause convection on the composition and chemistry of the upper troposphere and lower stratosphere, the effects of the NAMA on both the distribution of convective outflow and the residence time of convectively influenced air masses within the NAMA region must be considered.

A Contour-Based Algorithm for Automated Detection of Overshooting Tops Using Satellite Infrared Imagery

Overshooting top (OT) is a proxy for deep convection with intense updrafts. Using Himawari-8 infrared window (IRW) and water vapor (WV) imagery, this paper presents a contour-based OT detection algorithm based on the premise that the OT center is in a cold region enclosed by the local coldest (innermost) brightness temperature (BT) contour. Relative to existing IRW-texture algorithms, the contour-based algorithm offers improvement in two aspects. First, the new algorithm utilizes the WV minus IRW BT difference to capture the deep-convection pixels, and then removes the warmer pixels far from the cold center. Thus, compared with directly using a simple 215-K BT threshold to determine the possible OT pixels, many false alarms are avoided. Second, the new algorithm utilizes the BT contours to roughly depict and separate the anvil clouds and OT regions, and the anvil cloud pixels used to estimate the mean anvil cloud BT are outside the OT regions. Therefore, the computed BT gradient is more credible compared with the simple 225-K BT threshold. The accuracies of the OT detection algorithms are evaluated with 159 Global Precipitation Measurement-observed OT events collected from July 2015 to July 2017. The results indicate that the contour-based algorithm performs better than the original IRW-texture algorithm. The contour-based algorithm achieves a probability of detection (POD) of 67% and a false-alarm ratio (FAR) of 46%. Compared to the original IRW-texture algorithm, the contour-based algorithm increases the POD by 9% and decreases the FAR by 42%.

Relationships between Deep Convection Updraft Characteristics and Satellite-Based Super Rapid Scan Mesoscale Atmospheric Motion Vector–Derived Flow

Abstract Rapid acceleration of cloud-top outflow near vigorous storm updrafts can be readily observed in Geostationary Operational Environmental Satellite-14 (GOES-14) super rapid scan (SRS; 60 s) mode data. Conventional wisdom implies that this outflow is related to the intensity of updrafts and the formation of severe weather. However, from an SRS satellite perspective, the pairing of observed expansion and updraft intensity has not been objectively derived and documented. The goal of this study is to relate GOES-14 SRS-derived cloud-top horizontal divergence (CTD) over deep convection to internal updraft characteristics, and document evolution for severe and nonsevere thunderstorms. A new SRS flow derivation system is presented here to estimate storm-scale (<20 km) CTD. This CTD field is coupled with other proxies for storm updraft location and intensity such as overshooting tops (OTs), total lightning flash rates, and three-dimensional flow fields derived from dual-Doppler radar data. Objectively identified OTs with (without) matching CTD maxima were more (less) likely to be associated with radar-observed deep convection and severe weather reports at the ground, suggesting that some OTs were incorrectly identified. The correlation between CTD magnitude, maximum updraft speed, and total lightning was strongly positive for a nonsupercell pulse storm, and weakly positive for a supercell with multiple updraft pulses present. The relationship for the supercell was nonlinear, though larger flash rates are found during periods of larger CTD. Analysis here suggests that combining CTD with OTs and total lightning could have severe weather nowcasting value.

Deep learning-based monitoring of overshooting cloud tops from geostationary satellite data

Overshooting tops can cause a variety of severe weather conditions, such as cloud-to-ground lightning, strong winds, and heavy rainfall, which can affect flight and ground operations. Many previous studies have developed overshooting top (OT) detection models. However, rather than identifying individual pixels in satellite images as OTs or non-OTs, we typically find OTs through visual inspection of the contextual information of pixels (i.e., dome-like shape). Such an approach is more intuitive, accurate, and generalizable regardless of the OT characteristics that are used in the existing OT detection algorithms. In this paper, a new approach is proposed for OT detection using deep learning, more specifically a convolutional neural network (CNN), which can mimic the human process by convolution operation. Himawari-8 satellite images were used as input data, which were chopped into patches (i.e., grids) with a 31 × 31 window size and binary detection (OT or non-OT) for each patch was the output of the model. The validation results show that CNN can be successfully applied for the detection of OTs over the tropical regions, showing a mean probability of detection (POD) of 79.68% and a mean false alarm ratio (FAR) of 9.78%.

Hazard Avoidance Products for Convectively-Induced Turbulence in Support of High-Altitude Global Hawk Aircraft Missions

A combination of satellite-based and ground-based information is used to identify regions of intense convection that may act as a hazard to high-altitude aircraft. Motivated by concerns that Global Hawk pilotless aircraft, flying near 60,000 feet, might encounter significant convectively-induced turbulence during research overflights of tropical cyclones, strict rules were put in place to avoid such hazards. However, these rules put constraints on science missions focused on sampling convection with onboard sensors. To address these concerns, three hazard avoidance tools to aid in real-time mission decision support are used to more precisely identify areas of potential turbulence: Satellite-derived Cloud-top height and tropical overshooting tops, and ground-based global network lightning flashes. These tools are used to compare an ER-2 aircraft overflight of tropical cyclone Emily in 2005, which experienced severe turbulence, to Global Hawk overflights of tropical cyclones Karl and Matthew in 2010 that experienced no turbulence. It is found that the ER-2 overflew the lowest cloud tops and had the largest vertical separation from them compared to the Global Hawk flights. Therefore, cold cloud tops alone cannot predict turbulence. Unlike the overflights of Matthew and Karl, Emily exhibited multiple lightning flashes and a distinct overshooting top coincident with the observed turbulence. Therefore, these tools in tandem can better assist in identifying likely regions/periods of intense active convection. The primary outcome of this study is an altering of the Global Hawk overflight rules to be more flexible based on the analyzed conditions.

Climatology of Tropical Overshooting Tops in North Atlantic Tropical Cyclones

AbstractOrganized tropical convection, often characterized by overshooting tops, is a distinguishing quality of tropical cyclones (TCs). In this study, the climatology of tropical overshooting tops (TOTs) in North Atlantic Ocean TCs from 2004 to 2015 is examined. Previous studies have investigated the distribution of convection in TCs based on lightning data. The purpose of this study is to examine the distribution of TC convection from geostationary satellites using an objective TOT detection algorithm based on infrared brightness temperatures and empirically dependent thresholds. It will be shown that TOTs can provide an additional metric for identifying the characteristics of TC convection. Based on the 12-yr (2004–15) climatology, a distinct semidiurnal cycle in TOT activity is detected within 500 km of the TC center. In agreement with lightning data from previous studies, a predawn maximum (local to the TC) in TOTs is observed within 300 km of the TC center. A second predusk maximum is associated with TOTs between 300 and 500 km of the TC center. TC intensity and intensity trend along with environmental factors can affect the number and distribution of TOTs. For example, an exponential relationship exists between the number of TOTs and increasing sea surface temperatures. Conversely, increasing vertical wind shear magnitude decreases the density of TOTs, with a higher percentage of TOTs observed downshear of the wind direction. Generally, within 100 km (100–300 km) of the TC center, the preferred quadrant for TOTs is downshear left (downshear right), and increased TOT activity is observed right of TC motion. The findings corroborate previous lightning study results while providing additional insights into TC convection.

Favorable environments for the occurrence of overshooting tops in tropical cyclones

Based on Multifunctional Transport Satellite data and the infrared window-texture detection algorithm, the level of overshooting top (OT) activity within a tropical cyclone (TC), which is defined as the hourly mean number of OT occurrence, was statistically investigated in the western North Pacific basin for the period 2005–12. Based on the level of OT activity, the samples were divided into OT and non-OT cases or high-activity-OT (HA-OT) and low-activity-OT (LA-OT) cases. The differences in large-scale environmental variables between OT (HA-OT) and non-OT (LA-OT) cases were examined 12 hours prior to the OT occurrence. Statistical analysis showed that environmental differences did exist between the OT and non-OT cases. The OTs were more skewed towards the early stage of the TC life cycle, and mostly concentrated in low latitudes. Meanwhile, a sufficiently deep warm-water layer, large temperature difference between the upper- and lower-level troposphere, large humidity at the middle and upper levels, and large atmospheric instability, were favorable for OT occurrence. The differences in large-scale environmental characteristics between HA-OTs and LA-OTs were not as significant as those between OTs and non-OTs, but the HA-OT samples tended to occur when the vertical shear was weak and the TC intensity was low. Finally, statistical models were designed to predict the OT and HA-OT. When at least three OT (HA-OT) predictor thresholds were satisfied, the Peirce skill score reached a maximum value of 0.49 (0.30).

Electrical discharges in the overshooting tops of thunderstorms

AbstractPrevious studies have found that the vertical distribution of sources of very high frequency (VHF) signals from discharges mapped by Lightning Mapping Arrays typically have a secondary maximum in a storm's overshooting top. Low rates of these sources tend to occur continually throughout the lifetime of the overshooting top (OT), rather than sources occurring in the episodic distinct flashes observed at lower altitudes. This study examines the evolution of the VHF OT signature (VHF OT, defined here as a sustained period of ≥4 VHF sources per minute per 200 m layer above a storm's level of neutral buoyancy (LNB)) relative to the evolution of radar reflectivity and IR imagery of overshooting tops in three supercell and two multicell storms. The VHF OT began before OTs were detected in IR satellite imagery of the supercell storms. No OT was observed in IR imagery for either multicell storm, but this lack may have been due to the spatial and temporal resolution of the current IR imager. The VHF OT began near the time the 18 or 30 dBZ echo top rose above the LNB and ended near the time it fell below the LNB. There were too few radar volume scans of OTs in the multicell storms for a correlation analysis. In the supercell storms, however, the maximum altitude of VHF sources typically was less than or equal to the altitude of 18 dBZ echo tops and was correlated with these echo tops (linear correlation coefficient ≥0.86) during the period of the VHF OT.

Lightning, overshooting top and hail characteristics for strong convective storms in Central Europe

Lightning activity in storms with overshooting tops and hail-producing storms over Central Europe is studied, in order to find typical lightning characteristics that can be useful in nowcasting of the severity of the storm and its ability to produce hail. The first part of the study gives the analysis of lightning activity in thunderstorms with overshooting tops (OT) for the warm part of the year (May–September) from 2009 to 2010 over central and southeastern Europe. Deep convective clouds with OT were detected in Meteosat Second Generation (MSG) Spinning Enhanced Visible and Infrared Imager (SEVIRI) data, using methods based on the infrared window (IRW, 10.8μm) channel and absorption channels of water vapor (WV, 6.2μm) and ozone (O3, 9.7μm) in the form of brightness temperature differences. The locations and times of the detected OT were compared to the distribution and types of lightning strokes, which were provided by the LINET Lightning Location System. The results show that the spatial distribution of lightning generally coincides with the spatial distribution of the detected OT. The largest numbers of lightning strokes and OT were found in western Hungary, southeastern Austria, northeastern Slovenia and the northern Adriatic. The largest number of OT occurred between 1600 and 1800 UTC, whereas from 0600 to 1000 UTC OT detections were rather rare. Lightning activity showed a similar temporal distribution, with an increase in lightning activity evident at or close to the time of the OT detections. At the time of and close to the location of the OT, the lightning was found to occur well above the tropopause and was clearly related to the OT of cumulonimbus clouds.In the second part of the study, lightning characteristics are studied for 35 events of hail-producing thunderstorms over Croatia in the summer months (May to September), from 2008 to 2012. The lightning distribution, also registered by LINET, was compared to hail parameters based on measurements at the hailpad polygon. A polygon with dimensions of 30km×20km was located in the area of highest average number of days with hail occurrence in the continental part of Croatia. In a majority of the studied cases, the number of total lightning strokes sharply increased slightly before the beginning of hailfall. At the time the hailfall started there is a brief decrease in the number of lightning strokes, followed by a sharp increase shortly after. Additionally, larger hailstones with higher kinetic energy values appeared at the beginning of the hailshower. Microphysical properties of the cloud tops, investigated using MSG SEVIRI 3.9μm reflectivity, i.e. profiles of the effective radii of cloud particles vs. temperature, clearly verify the presence of strong updrafts associated with hail-producing clouds.

Relationships between Tropical Cyclone Intensity and Eyewall Structure as Determined by Radial Profiles of Inner-Core Infrared Brightness Temperature

Abstract Radial profiles of infrared brightness temperature for 2405 different satellite observations from 14 western North Pacific tropical cyclones (TCs) from the 2012 season were analyzed and compared to intensity and changes in intensity. Four critical points along the inner core of each infrared (IR) brightness temperature (BT) profile were identified: coldest cloud top (CCT), first overshooting top (FOT), and lower (L45) and upper (U45) extent of the inner eyewall. Radial movement of the mean CCT point outward with increasing TC intensity, combined with subsequent warming of the mean L45 point with intensity, highlighted structure changes that are consistent with eye and eyewall development. When stratified by latitude and vertical wind shear, the CCT point moved radially outward for all cases, notably at higher intensities for lower-latitude TCs and at lower intensities for higher-latitude TCs. The majority of the warming of the L45 point with increasing intensity occurred for low-latitude and low-shear cases. Slopes of IR BT between the four critical points were statistically significantly negatively correlated with intensity, indicating that stronger (weaker) TCs had more (less) negative slopes of IR BT and more (less) vertical eyewall profiles. Furthermore, except in high-shear cases, the most negative correlations were found in the inner eyewall, consistent with results from recent studies based on radar reconnaissance data. Finally, 12-h changes in slope were found to lead 12-h changes in intensity most often at higher latitudes, providing evidence that changes in the secondary TC circulation may lead changes in the primary TC circulation for both strengthening and weakening TCs.