Severe Local Convective Storms in Bangladesh: Part II

Atmospheric Research 95 (2010) 407–418

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Atmospheric Research

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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 rawinsonde 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

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 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 environmental 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.

Fig. 5. Mean zonal wind component proﬁles on severe local convective storm days (SLCSD, solid line) and non-severe local convective storm days (NSLCSD, Fig. 3. As in Fig. 1 except for the speciﬁc humidity. dashed line). 410 Y. Yamane et al. / Atmospheric Research 95 (2010) 407–418

layer from 3500 m to 5000 m are statistically significant at the confidence level of 99% or 95% with the maximum Z value at the level of 4500 m. This indicates that westerly flow in the middle layer is intensified on SLCSD compared with NSLCSD. This is consistent with the result of the case study of nor'wester in Dhaka (Mowla, 1986). Fig. 7 shows the mean meridional wind component profiles on SLCSD and NSLCSD. Positive differences between SLCSD and NSLCSD are found at the heights from the surface to 5700 m, and negative differences are found above the height of 5700 m. It is notable that the significant peak of the meridional wind component is found at the height of 500 m on SLCSD, and distinct maximum positive difference of about 2.5 ms−1 is found at its height. Fig. 8 shows the profile of the Z values for meridional wind components and the statistically significant levels of 99% and 95%. This figure shows that most of the positive differences under the level of 4000 m are statistically significant at the confidence level of 99% or 95%. The maximum positive difference in the meridional wind component at the height of 500 m corresponds to the maximum positive difference in the specific humidity at the same level on SLCSD shown in Figs. 3 and 4. The Bay of Bengal is located to the south of Bangladesh. The increase of the specific humidity in the lower layer on SLCSD is probably due to intensified southerly moist inflow across the Bay of Bengal in the lower layer. The intensification of the Fig. 6. As in Fig. 2 except for the zonal wind components. meridional wind components in the lower layer shown in this study is consistent with the results of some case studies of Fig. 5 shows the mean zonal wind component profiles on nor'wester in Bangladesh (e.g., Alam, 1986; Mowla, 1986). SLCSD and NSLCSD. Positive differences are found at the heights from 1000 m to 6000 m with the maximum positive 3.2. Convective parameters difference of about 3 ms− 1 at the height of 4500 m. Fig. 6 shows the profile of the Z values for the zonal wind We calculated various convective parameters to quantify component and the statistically significant levels of 95% and the environmental conditions in the outbreak of SLCS. The 99%. Fig. 6 shows that the positive differences in the middle

Fig. 7. As in Fig. 5 except for the meridional wind components. Fig. 8. As in Fig. 6 except for the meridional wind components. Y. Yamane et al. / Atmospheric Research 95 (2010) 407–418 411

Table 1 Statistics of convective parameters on severe local convective storm days and non-severe local convective storm days during the pre-monsoon season in Bangladesh.

Parameters Severe local convective storm days (59 days) Non-severe local convective storm days (135 days)

Mean Median Standard deviation Mean Median Standard deviation

KI (K) 27.6 29.0 6.3 19.6 24.6 16.1 TT (K) 68.0 66.9 12.5 65.9 64.0 14.6 SSI (K) 0.8 0.7 3.5 3.9 2.8 5.1 LI (K) −0.2 0.1 3.2 3.6 2.6 5.4 PW (kg m− 2) 38.2 38.5 5.4 32.7 32.6 10.2 CAPE (J kg− 1) 1363 1170 1283 799 254 1107 CIN (J kg− 1) 322 300 239 209 224 202 SHEAR0-500 hPa (ms− 1) 16.7 16.5 6.6 16.2 16.3 7.0 MS0-1 km (×10− 3 s− 1) 20.0 19.2 7.7 18.8 18.0 6.0 MS0-2 km (×10− 3 s− 1) 16.7 16.2 5.4 15.6 15.0 4.0 MS0-3 km (×10− 3 s− 1) 15.0 14.6 4.0 14.5 14.1 3.6 MS0-4 km (×10− 3 s− 1) 14.3 13.9 3.1 14.1 13.7 3.3 SREH (m2 s− 2) 148 115 131 105 94 104 VGP0-1 km (ms− 2) 0.59 0.58 0.43 0.38 0.27 0.38 VGP0-2 km (ms− 2) 0.51 0.46 0.37 0.31 0.23 0.31 VGP0-3 km (ms− 2) 0.46 0.42 0.33 0.29 0.23 0.28 VGP0-4 km (ms− 2) 0.44 0.42 0.30 0.28 0.22 0.27 EHI 1.32 0.43 1.87 0.57 0.03 1.04 BRN 16.1 7.4 21.3 36.6 2.2 298.9 convective parameters investigated were the K Index (KI), Total (EHI), and Bulk Richardson Number (BRN). MS, SHEAR and Total (TT), Showalter Stability Index (SSI), Precipitable Water SREH are measures of vertical wind shear of the atmosphere. (PW), Convective Available Potential Energy (CAPE), Convec- The vertical wind shear is important for organization of tive Inhibition (CIN), Mean Shear (MS), the magnitude of the convection (supercell and multicell) (Weisman and Klemp, vector difference between the winds at the surface and the level 1982). Supercells and multicells have greater potential to of 500 hPa (hereinafter, referred to as SHEAR0-500 hPa for produce severe weather such as tornadoes than ordinary cells simplicity), Storm Relative Environmental Helicity (SREH), (e.g., Houze, 1993). Therefore, the vertical wind shear is an Vorticity Generation Parameter (VGP), Energy Helicity Index important ingredient for the outbreak of SLCS (Brooks et al. 2003). VGP, EHI and BRN are combinations of the thermal instability and vertical wind shear parameters and common indicators of the formation of supercells and tornadoes. Detailed deﬁnitions of these parameters are described in the

Fig. 9. Box and whisker plots of the K Index (KI) on severe local convective storm days (SLCSD) and non-severe local convective storm days (NSLCSD). The box contains the middle 50% of the data with the median shown with a horizontal line. The bottom and top of the box denote the 25th and 75th percentile, respectively. Vertical lines (whiskers) denote the 10th and 90th percentile, respectively. Fig. 10. As in Fig. 9 except for the Showalter Stability Index (SSI). 412 Y. Yamane et al. / Atmospheric Research 95 (2010) 407–418

Fig. 11. As in Fig. 9 except for the Lifted Index (LI). Fig. 13. As in Fig. 9 except for the Convective Available Potential Energy (CAPE).

Appendix. Table 1 shows statistics on convective parameters on SLCSD and NSLCSD. include various severe convective weather events. If we can We determined the statistical significance between con- discriminate between supercell and non-supercell, or tornado vective parameters on SLCSD and those on NSLCSD using the Z and non-tornado, dynamic parameters may be able to test. The result indicates that all thermodynamic parameters differentiate between these two categories. Therefore, the and combination parameters except for the TT and the BRN result in the present study does not necessarily indicate that the have statistical significance with the confidence level of 99%. vertical wind shear is not important for the formation of However, all dynamic parameters have no statistical signifi- tornadoes and supercells during the pre-monsoon season in cance with the level of 99%. The SLCSD identified in this study Bangladesh. In this study, we focus on convective parameters

Fig. 12. As in Fig. 9 except for the Perceptible Water (PW). Fig. 14. As in Fig. 9 except for the Convective Inhibition (CIN). Y. Yamane et al. / Atmospheric Research 95 (2010) 407–418 413

Fig. 15. As in Fig. 9 except for the Vorticity Generation Parameter between Fig. 17. As in Fig. 9 except for the Vorticity Generation Parameter between the surface and 1 km AGL (VGP0-1 km). the surface and 3 km AGL (VGP0-3 km). with the statistical signiﬁcance of the level of 99% between respectively. Vertical lines (whiskers) denote the 10th and 90th SLCSD and NSLCSD. percentile, respectively. We show box and whisker plots for each convective parameter in Figs. 9–19. The box contains the middle 50% of 3.2.1. K Index the data with the median shown with a horizontal line. The The mean and median values for the KI on SLCSD are 27.6 K bottom and top of the box denote the 25th and 75th percentile, and 29.0 K, and greater than those on NSLCSD (19.6 K and

Fig. 16. As in Fig. 9 except for the Vorticity Generation Parameter between Fig. 18. As in Fig. 9 except for the Vorticity Generation Parameter between the surface and 2 km AGL (VGP0-2 km). the surface and 3 km AGL (VGP0-4 km). 414 Y. Yamane et al. / Atmospheric Research 95 (2010) 407–418

3.2.6. Convective Inhibition The mean and median values of CIN on SLCSD are 322 J kg−1 and 300 J kg−1, and greater than those on NSLCSD (209 g kg−1 and 224 g kg−1, respectively). The box and whisker plot for the CIN (Fig. 14) shows this parameter can distinguish between the two categories. More than 50% of data on NSLCSD are less than the median value on SLCSD. The length of the whisker extending from the bottom of the box on NSLCSD cannot be observed. This indicates the CIN on NSLCSD concentrates in the region with lower values. It is generally considered that the magnitude of the CIN is smaller on convective days. In this study, however, the mean and median values for the CIN on SLCSD are larger than those on NSLCSD. Fig. 1 shows the positive differences in temperature from 1000 m to 3500 m with the peak at the level of 2000 m. This indicates the production of a more stable layer in the lower layer on SLCSD. The larger values of the CIN on SLCSD may be due to this more stable layer in the lower layer. A stable layer in the lower layer increases the amount of potential instability. If there is dynamic forcing suitable for lifting a parcel in the environment with high CAPE, the parcel in the lowest layer can penetrate a stable layer, and the large amount of potential instability is

Fig. 19. As in Fig. 9 except for the Energy Helicity Index (EHI). released, thus, convection can be explosively developed. A sounding with a stable layer in the lower layer is recognized as one of the typical soundings associated with the outbreak 24.6 K, respectively). The box and whisker plot shows the KI on of severe thunderstorms in the United States (Bluestein, NSLCSD is widely found at lower values (Fig. 9). About 75% of 1993). However, this should be verified further, and more values on NSLCSD are under the median value on SLCSD. detailed studies are required in the future. It is possible that the soundings at 06 BST used in this study 3.2.2. Showalter Stability Index may sample remnants of the nocturnal inversion in the lower The mean and median values for the SSI on SLCSD are 0.8 K boundary layer, and this also may cause increase of the CIN. and 0.7 K, and less than those on NSLCSD (3.9 K and 2.8 K, Therefore, one may doubt whether the value of the CIN at respectively). The box and whisker plot for the SSI (Fig. 10) 06 BST is representative of the environment of SLCS. We focus shows a distinct difference in the distribution indicating that on comparing the CIN on SLCSD with that on NSLCSD in this the SSI can discriminate between the two categories. study and emphasize that the difference of the CIN between the two categories can be found with the statistical significance. 3.2.3. Lifted Index For the LI, the mean and median values on SLCSD are −0.2 K 3.2.7. Vorticity Generation Parameter and 0.1 K, and less than those on NSLCSD (3.6 K and 2.6 K, The mean and median values for all the VGPs on SLCSD are respectively). The box and whisker plot (Fig. 11)showstheLI greater than those on NSLCSD. The box and whisker plots has the ability to distinguish between the two categories. (Figs. 15–18) show there are distinct differences of the distributions between two categories, and the VGPs have the 3.2.4. Precipitable Water ability to discriminate between the two categories. The mean and median values for the PW on SLCSD are 38.2 g kg−1 and 38.5 g kg−1, and greater than those on NSLCSD 3.2.8. Energy Helicity Index (32.7 g kg−1 and 32.6 g kg−1, respectively). This result is The mean and median values for the EHI on SLCSD are 1.32 consistent with the finding shown in Fig. 4, where the amount and 0.43 and larger than those on NSLCSD (0.57 and 0.03, of water vapor in the atmosphere on SLCSD is larger than that respectively). The box and whisker plot (Fig. 19) shows the on NSLCSD. The box and whisker plot (Fig. 12) shows that the EHI can discriminate between the two categories. The length PW on NSLCSD is widely distributed at lower values. of the whiskers extending from the bottom of the boxes is considerably short in the two categories. In particular, the 3.2.5. Convective Available Potential Energy whisker from the bottom of the box cannot be determined on For the CAPE, the mean and median values on SLCSD are NSLCSD. This indicates the EHI concentrates over the range 1363 J kg− 1 and 1170 J kg− 1, and greater than those on with smaller values on NSLCSD. NSLCSD (799 g kg− 1 and 254 g kg− 1, respectively). The box and whisker plot for the CAPE (Fig. 13) can discriminate 3.3. Evaluation of forecast skill for convective parameters between the two categories. The length of the whisker extending from the bottom of the box on NSLCSD cannot be In this section, we evaluate the forecast skill of the con- determined. This indicates the CAPE extensively concentrates vective parameters using a skill score. The skill score used in over the range with relatively smaller values on NSLCSD. this study is the Heidke Skill Score (HSS; e.g., Wilks, 1995). Y. Yamane et al. / Atmospheric Research 95 (2010) 407–418 415

The HSS is a skill score based on a contingency table and Table 2 deﬁned as The Heidke Skill Score (HSS) and thresholds yielding the best HSS for each convective parameter. = ; HSS =2ðad bcÞ fða + bÞðb + dÞ + ða + cÞðc + dÞg Parameter HSS Threshold

LI 0.29 −2.6 where a is the number of correct nonevent forecasts, b is the PW 0.29 31.9 number of false alarms, c is the number of events not detected, CAPE 0.24 1121 and d is the number of correct event forecasts. While the HSS SSI 0.24 0.7 gives a score of 1 for no incorrect forecasts, it gives a score of −1 VGP0-2 km 0.23 0.67 KI 0.21 29.6 for no correct forecast. The HSS takes into account the number VGP0-1 km 0.20 0.77 of correct random forecasts. The Critical Success Index (CSI) and VGP0-3 km 0.17 0.70 True Skill Score (TSS) are also common skill scores. However, VGP0-4 km 0.17 0.13 the CSI does not give credit for correctly forecasting a nonevent EHI 0.12 0.01 (Doswell et al., 1990). Moreover, the CSI and TSS do not take into account the number of correct random forecasts. The HSS gives credit for a correct forecast on a nonevent and takes into Table 2 shows the best HSSs and the thresholds yielding account the number of correct random forecasts. Thus, we the best HSS for each convective parameter. This table shows utilized the HSS for evaluation of the forecast skill of convective that the HSSs for the LI and PW are better among all parameters. parameters. The HSSs for the LI and PW are 0.29 and 0.29, and the thresholds The method of evaluation conducted in this study is as for them are −2.6 K and 31.9 kg m−2. The value of the HSS for follows. First, a threshold was set for a convective parameter, the CAPE is also relatively high. The values of the HSS and and the categorical forecast was performed using the threshold for the CAPE are 0.24 and 1121 J kg−1. In contrast, the threshold. Then, the HSS was obtained for the threshold. values of the HSS for the EHI, VGP0-3 km and VGP0-4 km are This procedure was continued until the threshold yielding the relatively worse among all parameters (0.17, 0.17 and 0.12, best HSS was obtained. Fig. 20 shows the example of this respectively). procedure for the CAPE. This figure shows that the HSS is Although the LI is similar to the SSI, there is a difference in changed with the varying threshold of the CAPE, and the best the HSS between the LI and SSI (0.29 and 0.24, respectively). HSS=0.24 for the CAPE is obtained when the threshold of the This is because the LI is defined using the parcel in the lowest − CAPE is 1121 J kg 1. If the HSS is not changed with a varying layer and properly reflects the significant increase of water threshold, then we employed the minimum threshold in the vapor in the lowest layer on SLCSD shown in Fig. 4. interval in which the threshold is varying with the constant The HSSs of the combination parameters are relatively HSS. In this study, we evaluated the HSSs for the convective low. This may be because we cannot distinguish between parameters that can distinguish between SLCSD and NSLCSD tornado and non-tornado or supercell or non-supercell in our with the statistical significance of the 99% confidence level. database as mentioned before. If we can discriminate among For the CIN, this study shows that the CIN on SLCSD tends to these categories, we could determine higher value of the HSS be larger than that on NSLCSD. Therefore, in the categorical of the combination parameters. forecast, the occurrence of SLCS is predicted when a value of the CIN is greater than a threshold. However, because the relationship between the increase of the CIN and the outbreak 4. Conclusion of SLCS should be verified further as mentioned above, we did not evaluate the forecast skill of the CIN in this study. This study presents environmental conditions of severe local convective storms (SLCS) during the pre-monsoon season (from March to May) in Bangladesh. Composite soundings on severe local convective storm days (SLCSD) were compared with those on non-severe local convective storm days (NSLCSD). The comparison shows the warming in the lower layer from 1000 m to 3500 m and cooling around the level of 5000 m on SLCSD compared with NSLCSD. Significant increase of the specific humidity in the lowest layer is found with a peak around the level of 500 m with southerly wind intensified at this level on SLCSD compared with NSLCSD. These ingredients produce the increase of thermal instability of the atmosphere on SLCSD. We evaluated which convective parameters can discriminate between SLCSD and NSLCSD using the test statistics. The evaluation shows that all thermodynamic parameters (KI, LI, SSI, PW, CAPE CIN) except for TT can discriminate between two categories with statistical significance. All dynamic parameters as indices of the vertical wind shear cannot discriminate between Fig. 20. Variation of the Heidke Skill Score (HSS) for the CAPE with the threshold of the CAPE changing in categorical forecast based on contingency the two categories. Combination parameters (EHI and VGP) table. The dotted line indicates HSS=0. except for BRN can discriminate between the two categories. 416 Y. Yamane et al. / Atmospheric Research 95 (2010) 407–418

We evaluated the forecast skill of convective parameters Showalter Stability Index using the Heidke Skill Score (HSS). While the HSS of the LI and PW is better among all parameters, the HSS of the EHI is The Showalter Stability Index (SSI) is defined (Showalter, the worst. In addition, we can provide the critical values 1953)as that are helpful in forecasting the likelihood of the occur- ; rence of SLCS. SSI = T500 hPa Tp500 hPa The current study shows that differences with the where Tp is the temperature of a parcel lifted adiabat- statistical significance between SLCSD and NSLCSD can be 500 hPa ically from 850 hPa until saturated, and then moist adiabat- detected by analysis with rawinsonde data at 06 BST in ically to 500 hPa. T is the temperature at 500 hPa. Dhaka, and some convective parameters computed with the 500 hPa Negative SSI indicates the likelihood of convective activity. rawinsonde data can discriminate between the two categories. This indicates that the rawinsonde data at 06 BST in Lifted Index Dhaka are to some extent representative of the environment of SLCS and useful for the forecasting. Now, BMD does not The Lifted Index (LI) is defined (Galway, 1956)as have an effective method for the forecasting of SLCS. The results of this study will be helpful for introducing forecast- LI = T Tp⁎ ; ing using convective parameters based on the rawinsonde 500 hPa 500 hPa data at 06 BST in Dhaka. The convective parameters ⁎ where Tp500 hPa is the temperature of a parcel with the mean employed in this study were developed in another area, temperature and dewpoint temperature in the lowest 100 hPa especially the United States. Modification of the parameters lifted adiabatically until saturated, and then moist adiabati- may be efficient for further improving the forecast skill of cally to 500 hPa. T500 hPa is the temperature at 500 hPa. convective parameters. Negative LI indicates the likelihood of convective activity. The LI explicitly reflects the condition in the boundary layer Acknowledgments compared with the SSI.

We wish to thank Bangladesh Meteorological Departmet Precipitable Water (BMD) for providing rawinsonde data at Dhaka. This study was supported by Program for Improvement of Research Precipitable Water (PW) is defined (Huschke, 1959)as Environment for Young Researchers from Special Coordina- tion Funds for Promoting Science and Technology (SCF) 0 100 hPa commissioned by the Ministry of Education, Culture, Sports, PW = ∫ qdp≅∫qdp; Science and Technology (MEXT) of Japan. This work was also Ps Ps “ supported in part by Global COE Program: In search of where Ps is the surface pressure, and q is the specific humidity. ” Sustainable Humanosphere in Asia and Africa , MEXT, Japan. In this study, the top pressure is defined as 100 hPa because of the scarce amount of water vapor above 100 hPa. Appendix A Convective Available Potential Energy In this section, we describe details of the convective parameters used in this study. CAPE is defined (Moncrieff and Miller, 1976)as

K Index zEL ∫ = ; CAPE = g ðTvp TvÞ Tvdz The K Index (KI) is deﬁned (George, 1960)as zLFC

; where g is the gravitational acceleration, zLFC is the level of KI = T850 hPa T500 hPa + Td850 hPa ðT700 hPa Td700 hPaÞ LFC (level of free convection), and zEL is the equilibrium level, where T is temperature, and Td is dew point temperature. where the temperature excess of a parcel lifted from the LFC fi T850 hPa−T500 hPa indicates the lapse rate of temperature rst becomes zero above the LFC, and, Tvp and Tv are the between the lower layer and middle layer. Td850 hPa indicates virtual temperatures of the air parcel and the environment, fi the moisture content in the lower layer. T700 hPa−Td700 hPa is respectively. The CAPE is de ned as the net work of the a measure of the reduction of negative buoyancy through environment on a parcel per unit mass lifted from zLFC to zEL entrainment of dry air. The KI exceeding 28 K indicates the and the measurement of the development of convection. We likelihood of convection (Fuelbarg and Biggar, 1994). chose a parcel with thermodynamic properties averaged over the lowest 50 hPa. Total Total Convective Inhibition The Total Total (TT) is defined (Sadowski and Rieck, 1977) as Convective Inhibition (CIN) is defined (Colby, 1984)as

; zLFC TT = ðT850 hPa + Td850 hPaÞ2T500 hPa ∫ = ; CIN = g ðTvp TvÞ Tvdz where T is the temperature, and Td is the dew point temperature. zi Y. Yamane et al. / Atmospheric Research 95 (2010) 407–418 417 where zi is the initial level of the parcel lifted for calculating whether the statistical method in the United States is the CAPE, and, Tvp and Tv are the virtual temperatures of the applicable in Bangladesh. It is difficult to determine the air parcel and the environment, respectively. The CIN is storm motion vector in Bangladesh because of the lack of defined as the required net work to lift a negatively buoyant data. We confirmed that the average storm motion vector parcel per unit mass to the LFC. In general, the CIN is used for calculated with the statistical method mentioned above is the measurement of stability of the atmosphere. northwesterly and consistent with the empirical fact that storms frequently come from the northwest. Therefore, we Mean Shear and Vorticity Generation Parameter believe that the statistical method employed in this study is to some extent applicable in Bangladesh. Mean Shear (MS) is defined (Rasmussen and Wilhemson, The Energy Helicity Index (EHI) is defined (Hart and 1983)as Korotky, 1991; Davies, 1993)as

h h EHI = ðSREH × CAPEÞ = 1:6×105 MS = ∫ ∂V = ∂zdz = ∫ dz; 0 0 The EHI is the combination of the SREH and CAPE, and a where V is the horizontal velocity and h is the depth over measure of tornadic supercell. Rasmussen and Blanchard which the integration is performed. The MS is the length of the (1998) showed the EHI is highly correlated with the generation hodograph divided by the depth over which the hodograph of supercells in the United States of America. was measured. In this study, the MS was measured by the depth from the surface to 1 km AGL (Above Ground Level), Bulk Richardson Number 2 km AGL, 3 km AGL and 4 km AGL. The Vorticity Generation Parameter (VGP) is deﬁned The Bulk Richardson Number (BRN) is deﬁned (Weisman (Rasmussen and Wilhemson, 1983)as and Klemp, 1982)as

1 = 2 CAPE VGP = MS × CAPE BRN = ; SHEAR06km The VGP was also evaluated from the surface to 1 km AGL, where SHEAR – is deﬁned as 2 km AGL, 3 km AGL and 4 km AGL (referred to VGP0-1 km, 0 6km VGP0-2 km, VGP0-3 km and VGP0-4 km). CAPE1/2 is propor- 1 2 2 SHEAR = fðU U : Þ + ðV V : Þ g; tional to the maximum updraft speed associated with convec- 06km 2 6km 0 5km 6km 0 5km tion. Thus, the VGP is a measure of formation of cyclonic updraft

(mesocyclone in supercell) produced through the tilting of where U6kmand U0.5 km are the zonal wind components at the horizontal vorticity. Rasmussen and Blanchard (1998) showed levels of 6 km and 0.5 km above sea level, respectively. V6km the VGP is highly correlated with the formation of supercells in and V0.5 km are the meridional wind components at the levels the United States. of 6 km and 0.5 km above sea level, respectively. The BRN is a common predictor of supercell. Weisman and Klemp (1982) Storm Relative Environmental Helicity and Energy Helicity Index showed that the environments with the BRN≤50 favored supercell, while those with the BRN≥50 favored multicell Storm Relative Environmental Helicity (SREH) is deﬁned using a numerical model. (Davies-Johnes, 1984)as References h ∫ ⋅ ∂ = ∂ ; SREH = k ðV CÞ × ð V zÞdz Alam, Q.M.S., 1986. A case study of nor'wester in Dhaka on April 7 1984. 0 Proc. Seminar on Local Severe Storms, Dhaka, Bangladesh Meteorol. Dep, pp. 167–180. where V is the horizontal velocity vector, C is the storm Brooks, H.E., Lee, J.W., Craven, J.P., 2003. The spatial distribution of severe motion vector, k is the unit vector in the vertical and h is the thunderstorm and tornado environments from global reanalysis data. Atmos. Res. 67–68, 73–94. depth over which the integration is performed (3 km herein). Bluestein, H.B., 1993. Synoptic–dynamic meteorology in midlatitudes: volume In computation of the storm motion vector, the following II. Observations and Theory of Weather Systems. Oxford University Press, assumptions were used in this study (Davies and Johns, New York, p. 594. – Colby, F.P., 1984. Convective inhibition as a predictor of convection during 1993). When 0 6 km mean wind speed is greater than AVE-SESAM-2. Mon. Wea. Rev. 112, 2239–2252. − 1 15.5 ms , the storm motion vector is assumed to have the Davies, J.M., 1993. Hourly helicity, instability, and EHI in forecasting supercell motion speed of 85% of 0–6 km mean wind speed and the tornadoes. Proc. 17th Conf. Severe Local Storms, St. Louis, MO: Amer. – directional deviation of 20° right of 0–6 km mean wind. Meteor. Soc. , pp. 107 111. Davies, J.M., Johns, R.H., 1993. Some wind and instability parameters − 1 When 0–6 km mean wind speed is less than 15.5 ms , the associated with strong and violent tornadoes. 1. Wind shear and helicity, storm motion vector is assumed to have the motion speed of The Tornado: Its Structure, Dynamics, Prediction, and Hazard. Geophys. – 75% of 0–6 km mean wind speed and the directional Monogr., No. 79: Ame. Geophys. Union, pp. 573 582. – Davies-Johnes, R.P., 1984. Streamwise vorticity: the origin of updraft rotation deviation of 30° right of 0 6 km mean wind. The SREH is a in supercell storms. J. Atmos. Sci. 41, 2991–3006. measure of potential for cyclonic updraft produced through Doswell, C.A., Davies-Jones, R., Keller, D.L., 1990. On summary measures of the tilting of horizontal vorticity by storm relative inﬂow, that skill in rare event forecasting based on contingency tables. Weather Forecast. 5, 576–585. is to say, mesocyclone associated with supercell. In the Fuelbarg, H.E., Biggar, D.G., 1994. The preconvective environment of summer computation of the storm motion vector, it may be doubtful thunderstorms over the Florida Panhandle. Weather Forecast. 9, 316–326. 418 Y. Yamane et al. / Atmospheric Research 95 (2010) 407–418

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