Severe Local Convective Storms in Bangladesh: Part II

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Severe Local Convective Storms in Bangladesh: Part II Atmospheric Research 95 (2010) 407–418 Contents lists available at ScienceDirect Atmospheric Research journal homepage: www.elsevier.com/locate/atmos Severe local convective storms in Bangladesh: Part II. Environmental conditions Yusuke Yamane a,⁎,1, Taiichi Hayashi b, Ashraf Mahmmood Dewan c, Fatima Akter d a Pioneering Research Unit for Next Generation, Kyoto University, Gokasho, Uji, Kyoto, Japan b Disaster Prevention Research Institute, Kyoto University, Gokasho, Uji, Kyoto, Japan c Department of Geography and Environment, University of Dhaka, Dhaka - 1000, Bangladesh d Habitat for Humanity International - Bangladesh, Gulshan 2, Dhaka - 1212, Bangladesh article info abstract Article history: This paper examines the environmental conditions of severe local convective storms during the Received 13 May 2008 pre-monsoon season (from March to May) in Bangladesh. Received in revised form 30 October 2009 We compared composite soundings on severe local convective storm days (SLCSD) with those Accepted 9 November 2009 on non-severe local convective storm days (NSLCSD) using rawinsonde data at 06 Bangladesh Standard Time (BST) in Dhaka (90.3°E and 23.7°N). Temperatures are rising in the lower layer Keywords: and falling in the middle layer, and the amount of water vapor is significantly increasing in the Severe local convective storm lowest layer with southerly wind intensified on SLCSD compared with NSLCSD. This situation Environmental condition Pre-monsoon produces great thermal instability in the atmosphere on SLCSD. Bangladesh Convective parameters on SLCSD are computed with the rawinsonde data at 06 BST in Dhaka and compared with those on NSLCSD. The comparison shows that while most convective parameters related to thermal instability can discriminate between SLCSD and NSLCSD with statistical significance, no convective parameters related to the vertical wind shear can distinguish between the two categories. We evaluated the forecast skill of the convective parameters using Heidke Skill Score (HSS). The evaluation shows that the HSS for the Lifted Index and Precipitable Water are better among all parameters and have great forecast ability. © 2009 Elsevier B.V. All rights reserved. 1. Introduction on the environmental conditions of SLCS. Although some case studies of SLCS have been performed, their environmental We present the climatology of severe local convective storms conditions have not been comprehensively studied. (henceforth referred to simply as SLCS) in Bangladesh in the first Convective parameters (e.g., Convective Available Potential part of this paper (Yamane et al., 2009, hereafter Part I). This Energy) are useful tools for forecasting of SLCS. Many statistical paper presents the environmental conditions of SLCS during the studies of convective parameters in the outbreak of SLCS have pre-monsoon season (from March to May) in Bangladesh. been conducted. Rasmussen and Blanchard (1998) showed Clarifying the environmental conditions of SLCS is impor- statistical climatology of convective parameters in the outbreak tant for understanding their mechanism and forecasting. There of tornadic supercells in the United States using rawinsonde have been many studies of environmental conditions associat- data. Karmakar and Alam (2006) showed the statistics of ed with SLCS, especially in the United States (e.g., Maddox convective parameters associated with nor'westers (cf., Part I) (1976)). In Bangladesh, however, there has been little research during the pre-monsoon season in Bangladesh using rawin- sonde data at 06 Bangladesh Standard Time (BST) in Dhaka. They provided critical values indicating the likelihood of ⁎ Corresponding author. E-mail address: [email protected] (Y. Yamane). occurrence of nor'westers for each parameter. However, the 1 Present affiliation: Center for Southeast Asian Studies, Kyoto University, critical values provided in their study are subjectively deter- Kyoto, Japan. mined. For example, they provided the critical value of the 0169-8095/$ – see front matter © 2009 Elsevier B.V. All rights reserved. doi:10.1016/j.atmosres.2009.11.003 408 Y. Yamane et al. / Atmospheric Research 95 (2010) 407–418 Showalter Stability Index (SSI) as less than 3 K because 82.81% 3. Results of nor'wester events occurred when the SSI was less than 3 K. In addition, they did not assess the forecast skill of convective 3.1. Composite soundings parameters. Evaluating the forecast skill provides helpful information in the choice of proper parameters for the We investigated composite soundings on SLCSD compared prediction using the parameters. A skill score has commonly with those on NSLCSD. Fig. 1 shows the mean temperature been used for assessing the forecast skill objectively. Rasmussen differences profile between SLCSD and NSLCSD. The profile and Blanchard (1998) evaluated the forecast skill and provided shows the maximum of positive difference at the height of optimal values discriminating between tornadic supercell and 2000 m (about 1.2 K) and the maximum of negative differ- non-tornadic supercell using Heidke Skill Score. ence at the height of 5000 m (about −1.4 K). The present study comprehensively examines the environ- To evaluate the statistical significance of the differences of mental conditions of SLCS during the pre-monsoon season in the mean profile between SLCSD and NSLCSD, we used the Bangladesh. Composite soundings and convective parameters test statistic Zab (e.g., Wilks, 1995). The Zab is defined as on severe local convective storm days were investigated qffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi compared with those on non-severe local convective storm = 2 = 2 = ; Zab = ðXa À XbÞ ðsa naÞ + ðsb nbÞ days. Furthermore, the forecast skill of the parameters was objectively evaluated using a skill score. We believe the present where Xa and Xb are the mean values for categories a and b study greatly contributes to the understanding and forecasting (categories a and b correspond to SLCSD and NSLCSD, of the environmental conditions of SLCS in Bangladesh. respectively), na and nb are the number of events for each category (in this study, na is 59 days and nb is 135 days), and sa 2. Data and methodology and sb correspondtostandarddeviations.Fig. 2 shows the profile of the Z values for temperature. Two dashed lines indicate the We used rawinsonde data provided by the Bangladesh significance level at 99% and 95%. Fig. 2 shows the positive Meteorological Department (BMD) in order to investigate differences from 1500 m to 3000 m and negative differences composite profiles and compute convective parameters. BMD from 4000 m to 5500 m are statistically significant at the generally conducts rawinsonde daily observations at 06 confidence level of 99% or 95%. Bangladesh Standard Time (BST) once a day. However, BMD Fig. 3 shows the mean specific humidity differences profile sometimes makes only two or three observations a week between SLCSD and NSLCSD. The profile shows positive because of financial limitations. The rawinsonde observation differences in the specific humidity from the surface to the is taken in Dhaka (90.3°E and 23.7°N). The data were middle level. The maximum positive difference is found at the interpolated every 50 m before making composite profiles height of 500 m (about 2.6 g kg−1). Fig. 4 shows the profile of and computing the convective parameters investigated in the Z values for the specific humidity and the statistically Section 3. significant levels of 99% and 95%. This figure shows that the The number of days with available rawinsonde data during the pre-monsoon season is 202 days from 2002 to 2005. We chose 67 severe local convective storm days (SLCSD) identified in Part I out of the 202 days with the available rawinsonde data. SLCSD are the days with reports of severe weather associated with deep convections (e.g., tornado, hail, lightning and wind gusts) on the surface. To investigate the environmental conditions of SLCS, we com- pare the environmental conditions of days with reports of severe weather with those of days without reports. Days without reports may include days with occurrence of a non- severe local convective storm. Therefore, days without reports are defined as non-severe local convective storm days (NSLCSD) in this study. SLCSD with zero Convective Available Potential Energy (CAPE) were excluded in this analysis because soundings with zero CAPE may be contam- inated by convections prior to the rawinsonde observations. Consequently, we selected 59 SLCSD and 135 NSLCSD during the pre-monsoon season. SLCSD with zero CAPE (8 days) are not included in NSLCSD. The present study attempts to investigate what environ- mental conditions on synoptic scale associated with SLCS are observed with the rawinsonde data at 06 BST in Dhaka and the probability of the forecasting using these sounding data. Rawinsonde data at one point and once a day are sufficiently representative of the synoptic-scale environments of SLCS and suitable for our objective. Thus, we conducted a study Fig. 1. Mean temperature difference profile between severe local convective based on the rawinsonde data at 06 BST in Dhaka. storm days (SLCSD) and non-severe local convective storm days (NSLCSD). Y. Yamane et al. / Atmospheric Research 95 (2010) 407–418 409 Fig. 2. Profile of the test statistic Z for the difference in mean temperature Fig. 4. As in Fig. 2 except for the specific humidity. between severe local convective storm days (SLCSD) and non-severe local convective storm days (NSLCSD). The dashed lines indicate the statistical where the magnitude of the positive difference is the largest significance level of 95% and 99%, respectively. in Fig. 4, is significantly large. Increasing the lapse rate of temperature between the lower layer and the middle layer positive differences from the surface to the height of about (shown in Fig. 1) and specific humidity in the lower layer fi fi 5000 m are statistically signi cant at the con dence level of (shown in Fig. 3) produces larger thermal instability of the 99% or 95%. In particular, the Z value at the height of 500 m, atmosphere on SLCSD compared with NSLCSD.
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