The Study of Intensity, Duration and Type of Thunderstorms using Radar Images and Instability Indices in Southwest of Iran (Case Studies)
Corresponding author: Dr. Foroozan Arkian, Marine Science and Technology Faculty, Zafaranieh Street, Tehran, Iran Email:firstname.lastname@example.org; Tel: +989125805886; Fax: +982122404843
IDT: Intensity Duration and Type of the Storm; EHI: Energy- Helicity index;
CAPE: Convective Available Potential Energy; BRN: Bulk Richardson Number;
GFS: General Forecast System;
TOR: Tornadic Super-cell;
ORD: Single cell;
Cite this article: Arkian F. The Study of Intensity, Duration and Type of Thunderstorms using Radar Images and Instability Indices in Southwest of Iran (Case Studies). J J Hydrology.
2015, 1(1): 007.
SRH: Storm-Relative Helicity; PW: Precipitation Water of cloud; SI: Showalter stability Index;
TTI: Total Total Index; VWS: Vertical Wind Shear;
CTR: Cell Centroid Tracking; VIL: Vertical Integrated Liquid.
The knowledge of thunderstorms characteristics is necessar- ies for short term forecasting and long term planning in south- west of Iran near to Zagros ranges (mountains). A line of thun- derstorms rises along Zagros Mountains edge due to moisture air lifting. Therefore, knowing the formation mechanism of the thunderstorms can be helpful to reducing agricultural damag- es in the area.
Thunderstorms include different type such as Ordinary (ORD), Multi cell (MUL), super cell (SUP), Tornado (TOR) and squall line. Knupp and Stalker  investigated multi-cell thunder- storms using some indices such as convective available poten- tial energy, diluted updraft, cloud-layer depths, updraft area and radar images. Byko et al . studied downdraft reflectivity cores in SUP thunderstorms with high-resolution mobile radar and numerical simulation. Cores of downdraft lead to observe increasing circulation in low-level before full development in SUP thunderstorm. Downdraft cores are flooded to right pos- terior of storms and in occur dance with small-scale main ra- dar reflection. They helped to form a Hook Echo while observ- ing them in radar reflection and reaching to low levels.
Sounding climatologies have also been used to assess the environments related to particular types of thunderstorms. Bluestein and Parks  utilized soundings to compare the en- vironments of low-precipitation storms and classic supercells, and Rasmussen and Straka  investigated these and high-pre- cipitation supercells using a sounding climatology. Bluestein and Parker  have used soundings to investigate the modes of early storm organization near the dryline. A climatological sounding analysis of the environments associated with severe Oklahoma squall lines is reported in Bluestein and Jain  and non-severe squall lines in Bluestein et al . Salehi et al . in- vestigated vertical structure of severe thunderstorms in north- eastern Iran.
Rasmussen and Blanchard  examined all of the 0000 UTC soundings from the United States made during the year 1992 that have nonzero convective available potential ener- gy (CAPE). Soundings are classified as being associated with nonsupercell thunderstorms, supercells without significant tornadoes, and supercells with significant tornadoes. This classification is made by attempting to pair, based on the low-level sounding winds, an upstream sounding with each occurrence of a significant tornado, large hail, and/or 10 or more cloud-to-ground lightning flashes. Severe weather wind parameters (mean shear, 0–6-km shear, storm-relative helici- ty, and storm-relative anvil-level flow) and CAPE parameters (total CAPE and CAPE in the lowest 3000 m with buoyancy) are shown to discriminate weakly between the environments of the three classified types of storms. In the similar research, Arkian and Karimkhani  have determined the type of flood producing thunderstorms by some convective related parame- ters and radar images in northeast of Iran.
In this research we try to find the type of thunderstorms that produce severe shower and destructive hail in southwestern of Iran. We’ve used Reflectivity and Vertically Integrated Liq- uid (VIL) product of radar for determination of the intensity, duration and type (IDT) of thunderstorms. Since, Reflectivity of radar is not sufficient to identify thunderstorm types, we’ve calculated some instability indices such as showalter index, K index, Total Total index, Convective available potential energy (CAPE), Bulk Richardson number (BRN), Helicity, Energy-He- licity index, Vertical wind shear and Precipitable water (PW). However, no known baseline exists that is adequate to support these quantifications in the different area such as ours region, we tried to find type of storms with preset threshold of the parameters and then verify them with our observation from storms and compare them with the result of Rasmussen and Blanchard  paper.
Materials and method
Severe thunderstorm codes (80 to 99) was extracted from the dataset of twenty synoptic and agricultural standard weath- er stations for 2007-2013 years in southwest of Iran (Khuz- estan province). Furthermore, insurance offices and disaster task force has confirmed the storms that produced destructive large hail, lighting and severe shower in the area. In this study, three cases was chosen in 2010, 2011 and 2013. Surface and upper air data were taken from General Forecast System (GFS). These data have a spatial resolution of 0.5°×0.5° and a tempo- ral resolution of 6 h. Also, the soundings compared here are contained in Radiosonde Data for southwestern Iran, and were all made at 1200 UTC formal sounding. The dataset contain- ing some sounding-derived parameters such as K, Showalter, Total-Total, Helicity and Energy-Helicity (EHI) indices; Con- vective Available Potential Energy(CAPE) and Bulk Richardson Number (BRN) are used for detect type of thunderstorms.
The radar data used in this study were reflectivity scans from S-band radar. From low to high level 360° scans at elevation angles of 0.5° and 19.5° were obtained every 15 min out to a range of 250 km. The S-band radar characteristic is listed in Table. 1. These surveillance scans were used to identify struc- ture of cumulus clouds in their early development stage prior to precipitation. We have used radar images for identify IDT of thunderstorms.
The classes of storm are Single-cells, Multi-cells, Super-cell, Tornadic Super-cells and Squall line storms. These categories of storms (convective cells) were defined as bellow:
Tornadic Super-cell (TOR): This category was designed to identify soundings associated with tornadic Super-cells. Su- per-cell (SUP): For comparison to the TOR category, informa- tion from the climatological database was sought to identify Super-cells without significant tornadoes.
Single-cell (ORD): This category was designed to exclude Supercells. This was done by including soundings associated with a modest amount of cloud-to-ground lightning, but ex- cluding soundings associated with damaging wind, large hail, or any tornado.
Multi-cell (MUL): Multicellular organisms are organisms that consist of more than one cell, in contrast to single-celled or- ganisms. To form a multicellular organism, these cells need to identify and attach to the other cells.
Complex cells (clusters): This category has been organized into two or more single cells that merge together. Squall line: This category associated with ensemble of single/Multi /Su- per-cells that accompanied with a cold front.
The studied area (Khuzestan province) can be basically divid- ed into two regions, the rolling hills and mountainous regions north of the Ahwaz Ridge, and the plains and marsh lands to its south. The climate of Khuzestan is generally hot and oc- casionally humid, particularly in the south, while winters are much more cold and dry. Summertime temperatures routinely exceed 40 degrees Celsius and in the winter it can drop below freezing, with occasional snowfall, all the way south to Ahwaz.
Ahwaz weather radar works in S Doppler frequency band and is used for short-term forecasting, rainfall flood and road and aviation.
Case Study (2 November 2010)
The convective cells was triggered in the north of Khuzestan province (32.16˚ N, 48.25˚ E, Sea level height 82m) with sever lightning, high wind, showering at 18:00 UTC until early next morning. The maximum rainfall in the some stations was ex- ceed to 54 mm/day. Also, sever hail shower was reported in
the some villages with baseball-size that made agricultural damage, cars and head injury. Hourly and daily precipitation (DP) of Khuzestan province listed in Table. 2.
Table. 1. Characteristic of S-band radar
|2||H Rotation Angle||0~3600||7||Antenna
|3||V Rotation angle||-2~1800||8||Radar mast
|4||Sea level height||24.5 m||9||Position stabili- zation
|5||Altitude||30 m||10||H/V rota-
Radar images were produced by Rainbow software in 15 min intervals and the convective cell is identified based on their ra- dar Max reflectivity by considering 40dBz threshold . Fig. 1 shows hook echo formation on 2 November 2010. Hook echo detection is sensitive to the space and time resolutions of the radar. The idea that a hook echo forms as hydrometeors from a super cell’s main echo region are advected toward the rear of the storm by the rotating updraft seems to have been widely accepted, although Lemon  and Rasmussen et al . Have documented hook echoes that form when reflectivity cores de- scend from aloft to low levels on the rear flank of the storm, initially detached from the main echo at low levels, and sub- sequently become connected to the main echo to form a hook echo. These observations suggest that hook echoes might not always form from the simple horizontal advection process envisioned by Browning  and Fujita . Of course, the evolution of the reflectivity field is never solely a result of the horizontal advection of precipitation anyway, because hydro- meteors fall relative to the air; that is, hook-echo formation in- escapably involves descending precipitation curtains. Thus, the question is not whether the descent of precipitation cores can contribute to hook-echo formation, but whether a spectrum of hook-echo formation exists, whereby the horizontal advection of precipitation might dominate the evolution of the low-level reflectivity field and formation of some hook echoes at one end of the spectrum (as in the studies by Fujita  and Browning ) and hydrometeor fall speeds dominate the evolution of the low-level reflectivity field and hook-echo formation at the other end of the spectrum (as in the cases documented by Ras- mussen et al. ).
Table. 2. Hourly and daily precipitation in the synoptic stations of
Khuzestan province during 1-3 November 2010.
|00||06||12 UTC||18 UTC||DP(mm)||00 UTC||06 UTC||12 UTC||18 UTC||DP(mm)|
Figure 1. Hook Echo formation on 2 November 2010.
Results show that the reflectivity core intensity and vertical growth must exceed 60 dBZ and 15 km for hail event, respec- tively. Also, VIL was estimated about 50 kg m-2 for hailstorm and often very high or increasing. Subsequently, values slowly subsided to 50 kg m-2 when baseball-size surface hail and vi- olent winds were actually being reported. High values of VIL and pronounced three-body scattering very often precede sur- face hail falls. VIL has predictive value in that it often develops during hail growth aloft and before very large hail reaches the surface. With the correlation of very large hail and often vi- olent winds with the most striking signatures, in these cases
km herein) and SRH unit is m2/s2. Table 3 shows SRH values for different percentile in soundings associated with non- super-cell thunderstorms (ORD), supercells without signifi- cant tornadoes (SUP), super-cells with significant tornadoes (TOR).
BL-6 km shear
In this section, the magnitude of the shear vector between the 0–500 m AGL mean wind and 6 km AGL wind (hereafter BL–6- km shear) is examined and shear unit is ms-1. Table. 3 shows the frequency of occurrence of various magnitudes of BL-6 km shear as a function of category.
Convective Available Potential Energy
CAPE Moncrieff and Miller  is in common use as a forecast tool for super-cells and it unit is Jkg-1. Table. 3 shows values of CAPE for ORD, TOR and SUP. Interestingly, CAPE is significantly different between ORD and SUP soundings, as well as between ORD and TOR soundings, suggesting that CAPE alone has some value as a super cell predictor, even when not paired with a measure of shear, although combined measures are much bet- ter.
Bulk Richardson number
The Bulk Richardson Number is calculated as follows:
VIL detection should suggest stronger wording in the resulting warning. The convective cells have relative quick movement in
( () ) (2)
CTR images and move toward North East. Vertical growth of cells indicates high updraft strength and their movement is re- lated to vertical wind shear .
Instability indices calculation
In this research, some instability indices such as KI, SI, TTI, CAPE, PW, BRN, SRH, EHI, VWS were calculate by using Skew-T diagram and General Forecasting Model (GFS) data for identify the type of storms. Here is some indices definitions:
Storm-Relative Helicity (SRH)
SRH is sounding-derived shear parameter Davies-Jones et al.
 that defined as:
The bulk Richardson number (BRN) has been used as a su- per-cell predictor ever since it was investigated using numer- ical simulations Hart and Korotky . Weisman and Klemp (1982) determined that environments with BRN>50 favored multicellular events.
Energy– Helicity index
The Energy–Helicity index (EHI) [16,17] is defined as:
∫ ( ) (1)
This index is used operationally for super-cell and tornado forecasting, with values larger than 1.0 indicating a potential for supercells, and EHI .2.0 indicating a large probability of su- per-cells. The likelihood of significant tornadoes does increase with increasing EHI, as shown in Table. 3.
Where V is horizontal velocity, c is the storm motion vector, and h is the depth over which the integration is performed (3
Table. 3. Percentile of some indices for soundings associated with nonsuper-cell thunderstorms (ORD), supercells without significant tornadoes (SUP), supercells with significant tornadoes (TOR), .
|Parameter||ORD Percentile||SUP Percentile||TOR Percentile|
|Mean shear (0-4 km)||2.79-3.61||3.61-6.42||6.42-8.09||4.52-5.23||5.23-7.83||7.83-9.44||4.52-5.06||5.06-9.44||9.44-10.29|
Table. 4. Radar survey and instability indices for selected cases.
|cell name||Radar images||BRN||CAPE||Wind She ar (m/s)||SRH||EHI||TTI||KI||SI||Type||Itensity||PW (kg/m2)|
Instability indices of three cases (2 November 2010, 6 Novem- ber 2011 and 2 May 2013) listed in table. 4. Each cases are in- cluding several convective cells that named using Alphabet, for example, there are five convective cells (A, G, I1, I2, J) in case 1.
For identification of convective cells, all mentioned instability indices was calculated and they was compared with their own threshold in Table. 3 .
PW was calculated by GFS data for all convective cells. PW threshold is 8 kg/m2 for precipitation potential of cloud  and according to Table. 4 in all studied cases, PW is more than the threshold. K index, and TT index indicated high instability and high probably of thunderstorms, but SI didn`t show insta- bility in some cases. The result show different type of thunder- storms such as ORD, MUL and SUP in 2 Nov 2010 and 2011 and 05 May 2013 (Table. 4).
Three convective systems were studied to identify IDT of vio- lent thunderstorms by radar images and instability indices in southwest of Iran. One of our criterion for choosing the type of thunderstorm was vertical structure and reflectivity of convec- tive cells in radar images. Since, the radar images are not suffi- cient for thunderstorm identification, we also have calculated some instability indices for all cells and compare them with Table. 3  to identify the exact type of thunderstorms.
The amount of CAPE and component indices such as BRN and EHI in our area was lower than listed thresholds in Table. 3, therefore, determination of thunderstorms types by mentioned indices was not easy. The results show that the most thunder- storms are single cell in the coverage area of the S-band radar. By examining thunderstorms (containing 66 cells), practically, super cell with tornado sign, single cell and multicellular are 14%, 48.5% and 37.5%, respectively.
The results show that there is a direct relation between ver- tical growth of cells and vertical wind shear (VWS) in the ra- dar image. The intensity changed between 40 to 70 dBz and duration time of cells was between 30 to 405 min. Convective cells with quick horizontal movements in radar images have significant wind shear between 15-24 ms-1. VWS in layer be- tween 500-6000 m and SRH with compare to Rasmussen and Blanchard  thresholds imply for identify the storm types. Applying each of indices individually to determination of cell type is not adequate and at less 4 indices shows the exact type of storm. VIL was calculated more than 50 kg m-2 for all convec- tive cells accompanied by hail.
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