Special Issue "Severe Storm"

A special issue of Atmosphere (ISSN 2073-4433). This special issue belongs to the section "Meteorology".

Deadline for manuscript submissions: closed (31 May 2020).

Special Issue Editor

Dr. Kevin K.W. Cheung
Website
Guest Editor
Department of Environmental Sciences, Macquarie University, Macquarie Park NSW 2109, Australia
Interests: meteorology; climatology; atmospheric physics; climate dynamics; numerical weather prediction; regional climate modeling
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Special Issue Information

Dear Colleagues,

Severe storm or local storm refers to weather phenomena with spatial sizes ranging from meso-gamma scale, to microscale, to convective scale. These storms develop in one or combined forms of thunderstorms and squalls, hailstorms, and tornadoes, as well as cases such as rainstorms, windstorms, and snowstorms. All these storms are high-impact weather systems, and in some parts of the world they severe damage and loss of infrastructure and even life every year. Given the small spatial scales of severe storms, their predictability is expected to be lower than the synoptic- and planetary-scale phenomena. However, regional climatology and specific environmental factors relevant to some of these storms are quite clear. Improvements in our forecasts of severe storms can only be obtained through a better understanding of the dynamics and physical processes of their development. This Special Issue aims to summarize the frontiers of research regarding severe storms. Studies in the following aspects are welcome.

Since in-situ observations are rare for these small-scale storm systems, observational platforms and techniques must be enhanced. Satellite instruments such as lightning sensors have been increasingly applied to monitor convective activities and storm developments.  Spaceborne radar is also improving in spatial resolution to observe precipitation. On the ground, fixed and mobile radar systems are useful tools with which to observe storm structure. In particular, a mobile radar with a raindrop size analyzer is an excellent tool with which to discover new storm microphysics. For some local storms, special observation techniques are necessary. Examples include the hail pad to measure hailstone size, especially in population-scarce regions. With these enhanced observations, studies on storm dynamics and physical processes during development should be promoted. Numerical modeling with cloud-resolving scales is feasible with today’s computational resources. One of the most challenging aspects of this study is to perform mesoscale and convective-scale data assimilation on numerical models.

Although the climatology of various types of storm has been established in many parts of the world, we only have very basic knowledge of the environmental factors responsible for storm development. General metrics (or discriminants) have been developed in previous studies for measuring storm potential; however, as mentioned, the factors behind the storm metrics are highly region-specific, and thus many more regional studies should be conducted. Moreover, specific metrics (e.g., those for hail versus tornado) are yet to be developed. On a global scale, the climate is changing. The behavior of some synoptic-scale storms has already changed since the pre-industrial period. Similarly, the behavior of local storms is also expected to change. Projecting future local storm activity would impose many challenges on our research community. Do our climate models have high enough resolution to imply local storm activity? Are there downscaling techniques that can add value to climate models in terms of local storm projection? Do we have the right metrics of local storms to project the future storm environment? Topics such as these and related research questions would be excellent additions to our Special Issue.

Dr. Kevin K.W. Cheung
Guest Editor

Manuscript Submission Information

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Keywords

  • mesoscale
  • convective scale
  • thunderstorm
  • squall
  • hailstorm
  • tornado
  • lightning
  • cloud-resolving model
  • data assimilation
  • storm metric
  • climate-change impact

Published Papers (3 papers)

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Research

Open AccessArticle
Damaging Convective and Non-Convective Winds in Southwestern Iberia during Windstorm Xola
Atmosphere 2020, 11(7), 692; https://doi.org/10.3390/atmos11070692 - 30 Jun 2020
Abstract
On 23 December 200923/12/2009, windstorm Xola struck mainland Portugal, causing serious damage in a small area north of Lisbon (Oeste region) and in the south region, inflicting economic losses of over EUR 100 million. In both areas, several power towers, designed to withstand [...] Read more.
On 23 December 200923/12/2009, windstorm Xola struck mainland Portugal, causing serious damage in a small area north of Lisbon (Oeste region) and in the south region, inflicting economic losses of over EUR 100 million. In both areas, several power towers, designed to withstand up to 46 ms−1 winds, were destroyed. The causes of these two distinct damaging wind events were investigated. Xola was revealed to have a prominent cloud head and a split cold front structure. In the southern region, the damages were due to downburst winds, associated with a mesovortex, observed in a bow echo line triggered by an upper cold front. The cloud head presented several dry air intrusion signatures, co-located with tops progressively lowering towards the hooked tip. This tip revealed features consistent with the presence of slantwise convection, the descending branches of which may have been strengthened by evaporating cooling. At the reflectivity cloud head tip, a jet streak pattern was identified on weather radar, with Doppler velocities exceeding 55 m s−1, just 400 m above ground. This signature is coherent with the presence of a Sting jet, and this phenomenon was associated with the strongest wind gusts (over 40 ms−1) and the largest damages in the Oeste region. Full article
(This article belongs to the Special Issue Severe Storm)
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Open AccessArticle
Rainfall Contribution of Tropical Cyclones in the Bay of Bengal between 1998 and 2016 using TRMM Satellite Data
Atmosphere 2019, 10(11), 699; https://doi.org/10.3390/atmos10110699 - 12 Nov 2019
Cited by 2
Abstract
In the Bay of Bengal (BoB) area, landfalling Tropical Cyclones (TCs) often produce heavy rainfall that results in coastal flooding and causes enormous loss of life and property. However, the rainfall contribution of TCs in this area has not yet been systematically investigated. [...] Read more.
In the Bay of Bengal (BoB) area, landfalling Tropical Cyclones (TCs) often produce heavy rainfall that results in coastal flooding and causes enormous loss of life and property. However, the rainfall contribution of TCs in this area has not yet been systematically investigated. To fulfil this objective, firstly, this paper used TC best track data from the Indian Meteorological Department (IMD) to analyze TC activity in this area from 1998 to 2016 (January–December). It showed that on average there were 2.47 TCs per year generated in BoB. In 1998, 1999, 2000, 2005, 2008, 2009, 2010, 2013, and 2016 there were 3 or more TCs; while in 2001, 2004, 2011, 2012, and 2015, there was only 1 TC. On a monthly basis, the maximum TC activity was in May, October, and November, and the lowest TC activity was from January to April and in July. Rainfall data from the Tropical Rainfall Measurement Mission (TRMM) were used to estimate TC rainfall contribution (i.e., how much TC contributed to the total rainfall) on an interannual and monthly scale. The result showed that TCs accounted for around 8% of total overland rainfall during 1998–2016, and with a minimum of 1% in 2011 and a maximum of 34% in 1999. On the monthly basis, TCs’ limited rainfall contribution overland was found from January to April and in July (less than 14%), whereas the maximum TC rainfall contribution overland was in November and December (16%), May (15%), and October (14%). The probability density functions showed that, in a stronger TC, heavier rainfall accounted for more percentages. However, there was little correlation between TC rainfall contribution and TC intensity, because the TC rainfall contribution was also influenced by the TC rainfall area and frequency, and as well the occurrence of other rainfall systems. Full article
(This article belongs to the Special Issue Severe Storm)
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Open AccessArticle
Analysis of Lightning and Precipitation Activities in Three Severe Convective Events Based on Doppler Radar and Microwave Radiometer over the Central China Region
Atmosphere 2019, 10(6), 298; https://doi.org/10.3390/atmos10060298 - 01 Jun 2019
Cited by 1
Abstract
Hubei Province Region (HPR), located in Central China, is a concentrated area of severe convective weather. Three severe convective processes occurred in HPR were selected, namely 14–15 May 2015 (Case 1), 6–7 July 2013 (Case 2), and 11–12 September 2014 (Case 3). In [...] Read more.
Hubei Province Region (HPR), located in Central China, is a concentrated area of severe convective weather. Three severe convective processes occurred in HPR were selected, namely 14–15 May 2015 (Case 1), 6–7 July 2013 (Case 2), and 11–12 September 2014 (Case 3). In order to investigate the differences between the three cases, the temporal and spatial distribution characteristics of cloud–ground lightning (CG) flashes and precipitation, the distribution of radar parameters, and the evolution of cloud environment characteristics (including water vapor (VD), liquid water content (LWC), relative humidity (RH), and temperature) were compared and analyzed by using the data of lightning locator, S-band Doppler radar, ground-based microwave radiometer (MWR), and automatic weather stations (AWS) in this study. The results showed that 80% of the CG flashes had an inverse correlation with the spatial distribution of heavy rainfall, 28.6% of positive CG (+CG) flashes occurred at the center of precipitation (>30 mm), and the percentage was higher than that of negative CG (−CG) flashes (13%). Moreover, the quantity of thunderstorm cells in Case 1 was more than other cases, the peak time of +CG flashes was prior to that of total CG flashes in Case 2 and Case 3, and the time of +CG flashes’ peak in Case 2 was prior to that of precipitation at about 2 h. Based on the analysis of the cloud environment, there are three main reasons for the differences of CG flashes and precipitation. Firstly, the structure of the LWC vertical profile and the height of the LWC peak are different, and high LWC makes it difficult for the collision of ice particles to generate electricity. Secondly, the differences between convective available potential energy (CAPE), precipitation, and CG flashes is caused by the sudden increase of VD from 1.5 km to 3 km, and thirdly, the production of CG flashes is very sensitive to RH at the surface layer and the total CG flashes increase as the RH increasing. Full article
(This article belongs to the Special Issue Severe Storm)
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