Modified instability index of the troposphere associated with thunderstorms / nor'westers over Bangladesh during the pre-monsoon season

The present study is an attempt to study different Modified Stability Indices in relation to the occurrence of severe thunderstorms/nor’westers in order to find out the critical values of different modified indices favorable for the formation of thunderstorms in Bangladesh. Computations have also been made for the stations in and around Bangladesh for studying the spatial distribution of the modified stability indices. The Modified Instability Indices such as Modified Cross Total Index (MCT), Modified Vertical Total Index (MVT), Modified Total Totals Index (MTT), Modified SWEAT Index (MSWI), Modified K-Index (MKI) and Modified Energy Index (MEI) show greater instability of the troposphere in the morning as compared to CT, VT, TT, SWI, KI and EI. The critical values of different modified instability indices at 0000 UTC over Dhaka are: MCT >= 20° C, MVT >= 26° C, MTT >= 46° C, MSWI > 300, MKI >= 40° C and MEI < -6 joules/gm respectively for the nor’westers to occur in Bangladesh. The spatial distributions of modified stability indices have revealed that maximum instability lies over the area of surface low pressure especially over Bihar, West Bengal and adjoining Bangladesh at 0000 UTC on the dates of occurrence of nor’westers. Nor’westers occur at theeastern end of the maximum instability. For severe nor’westers of tornadic intensity, the critical values of different modified instability indices at 0000 UTC over Dhaka are: MCT >= 20° C, MVT >= 28° C, MTT >= 50° C, MSWI >= 500, MKI >= 42° C and MEI < -8 joules/gm respectively for the nor’westers to occur in Bangladesh.

Prediction of Thunderstorms based on Atmospheric Instability Indices over Bangladesh using WRF-ARW Model

In this study an attempt has been made to inspect the forecasting of thunderstorms based on two cases (1st case: 17th May, 2019 and 2nd case: 31st March, 2019) over Dhaka using WRF Model. The model is run for 72 hours with 03 nested domain of 09 km, 03 km and 01 km horizontal resolutions using 0.25º X 0.25º six hourly global data assimilation system. For model simulation, Milbrandt-Yau Double-Moment 7-class scheme (9) has been used as microphysics scheme in this study. The model performance is evaluated by calculating hourly instability indices (VTI, TTI, KI, CTI, MCAPE, MCIN, BRN, LI, SI, SWI) value and have been compared with the threshold value of indices. Different meteorological parameters such as MSLP, temperature, winds at upper (300 hPa) and lower (925 hPa) level, relative humidity along with vertical cross section are also studied by the model and compared with the favorable conditions for forming of thunderstorms. Area rage rainfall (hourly) value has been also calculated and compared with indices value to comprehend the nature of thunderstorms. Observing the indices value it is seen that all indices value increase sharply 5-6 hours before of thunderstorm occurring and MCAPE is giving more reliable result. Moreover, this study shows that inner two domains (3 and 1 km resolution) are giving better results than outer one and which indices are more probable in forecasting of thunderstorm for our country as well as giving less Root Mean square Error. From the simulated and validated results, it can be concluded that the model performance of instability indices can be used as forecasting of thunderstorms over Bangladesh.

Tropospheric moisture and its relation with rainfall due to nor’westers in Bangladesh

Attempts have been made to compute the precipitable water content of the troposphere, weighted average water vapour and to correlate these parameters with different instability indices and also with the next 24-hr rainfall, next 24-hr maximum rainfall and next 24-hr country averaged rainfall in order to predicting rainfall due to nor’westers in Bangladesh. It has been found that the maximum number of nor’westers occur when the precipitable water is 25-45 mm hr-1 between 1000 and 500 hPa, the maximum frequency being 48 in the range of 35-45 mm hr-1. The spatial distribution of precipitable water indicates that the maximum precipitable water is concentrated over the area near the places of nor’westers. The specific humidity has been found to increase on the dates of occurrence of nor’westers in Bangladesh on most occasions. Maximum number of nor’westers occurs when the weighted average specific humidity between the surface (1000 hPa) and 500 hPa is 8-12 g kg-1, the maximum frequency being 43 in the range of 8-10 g kg-1. The study reveals that nor’westers have been found to occur near or at the eastern end of maximum weighted average specific humidity. It has also been found that nor’westers occur near the point of inter-section of the axes of moist and dry zones. A number of parameters of the troposphere over Dhaka at 0000 UTC on the dates of occurrence of nor’westers such as precipitable water (mm/hr), MSWI, SWI, SWI/TT, (q1000 – q850) weighted averaged specific humidity have statistically significant correlations with next 24-hour rainfall at Dhaka, next 24-hour maximum rainfall in Bangladesh and country averaged rainfall. The correlation co-efficients are relatively small and the standard errors of estimates are higher. The small correlation co-efficients are significant because of the large number of data.

Interrelation among different instability indices of the troposphere over Dhaka associated with thunderstorms/nor'westers over Bangladesh during the pre-monsoon season

Attempts have been made to correlate different instability indices among themselves statistically. The study reveals that the Showalter Stability Index (SI) has moderate to good correlations with different instability indices except Dew-point Index (DPI), Vertical Total Index (VT), Modified Vertical Total Index (MVT) and Modified K-Index (MK). Most of the correlations co-efficient are found to be significant up to 99% level of significance except Dry Instability Index (DII), which has correlation with SI up to 95% level of significance. Lifted Index (LI) has moderate to good correlation with different instability indices except DII, K-Index (KI) and MVT. Most of the correlations co-efficient are significant up to 99% level of significance except VT, SWEAT Index (SWI) and MKI, which have correlation with LI up to 95% level of significance. Unmodified instability indices have moderate to strong correlation with the corresponding modified instability indices, having 99% level of significance. The correlation co-efficient of VT and MVT, SWI and Modified SWEAT Index (MSWI), and KI and MKI are comparatively large. Standard errors of estimate are small in almost all the cases except a few. The regression equations obtained are likely to be helpful in the computation of different instability indices.

A New Approach for the Analysis of Deep Convective Events: Thunderstorm Intensity Index

In this study, an investigation of a new thunderstorm intensity index (TSII) derived from lightning data is performed, along with its relationship to rain, wind, hail and waterspouts as well as instability indices (CAPE, LI, KI, and DLS). The study area is located in the northeastern Adriatic and includes various terrain types in a relatively small area (coastal, flatlands, hills and valleys, and mountain regions). The investigated period covers 11 years (2008–2018). The mathematical algorithm standing behind the TSII is based on the well-established methodology of lightning jump, allowing us to recognize areas where intensification in thunderstorms occurred. Our results suggest that these areas (with a positive TSII) experience significantly higher rain intensities and have higher total amounts of precipitation compared with areas where thunderstorms did not generate a TSII. Moreover, 76% of thunderstorm hail cases were associated with the presence of a TSII within a 15 km distance. The maximum reported wind speed also has higher values on a day with a TSII. Out of 27 waterspout events associated with lightning, 77% were related to a TSII. Due to the good spatial (3 km × 3 km) and high temporal (2 min) resolution of lightning data, the TSII can recognize even a local and short-lived intense system that is often misread by radars and satellites due to their inferior temporal resolution. The TSII is designed to be used as a climatological and diagnostic variable that could serve in lieu of more established data sources (e.g., station measurements and observations, radar imagery, etc.) if they are unavailable.

Delineating the dynamics of growth and instability of different Non-Timber Forest Products (NTFP’s) in Gujarat

The importance of Non-Timber Forest Products (NTFPs) and its contribution to rural livelihoods and alleviating rural poverty is well known in Gujarat and emerging as the source of income for the rural poor. Therefore, promotion of Non-Timber Forest Products (NTFP) species, therefore, the present study aimed at to examine the growth rates and instability of different forest products. The secondary data on quantity and value of different wood and non-wood products from the year 1996-97 to 2017-18 were compiled from published sources. The results revealed that quantity of Mahuda flowers and Honey increased significantly while majority of NTFPs found to be decreased but it is statistically non-significant during overall period. Instability indices of both quantity as well as value of NTFPs found to be higher during overall period. The quantity of teak timber significantly increased in Valsad circle but it significantly decreased in Ahmedabad circle, while change in value found to be nonsignificant in all circles during overall period because of irregular and timely non-availability of NTFPs.

Bottom Communities and Abiotic Factors: Analysis of Statistical Relationship Using the Instability Index and Virtual Species Distribution

Statistical procedures for quantifying the relationships between the community structure and abiotic variables start with selecting a minimum set of uncorrelated environmental factors that determine the ecological conditions essential for each of the species. This is especially important when constructing models of spatial distribution of species which are key to ecology of communities and conservation of nature. The aim of the study is to explore whether some applications of information theory can be used to rank environmental factors with respect to their contribution to the formation of the ecological structure of aquatic communities. We consider the applicability of the instability index, which is a special case of the Kullback-Leibler entropy divergence and reflects the information gain from the displacement of a particular realization of a random variable relative to its mean value. Using of instability indices allows to reduce multidimensional data sets on species structure of communities and abiotic factors to lower dimension sets of commensurate standardized variables and to explore the relationships between the latter. The initial data we used were the results of the long-term (1990–2019) hydrobiological survey of benthic communities in small and medium-sized rivers in the Middle and Lower Volga regions. We consider the indices of instability calculated for each of 147 taxa of macrozoobenthos and 8 geophysical and hydrochemical indicators. Based on these data, we constructed random forest regression models and calculated potential weights of environmental factors that determine ecological preferences of species. The most significant explanatory variables were used to construct distribution maps of «virtual species», which were compared with the corresponding empirical data. A habitat suitability map of chironomids (Diptera, Chironomidae), the Prodiamesinae subfamily, is presented. Instability indices can be effectively used for exploratory analysis of various ecosystems, e. g. ranking habitats according to the degree of environmental instability and / or species associations, selecting the most informative abiotic variables that determine the population density of the taxa, etc.

Inspection of new thunderstorm intensity index

&lt;p&gt;Lightning data provide very high spatial and temporal resolution allowing us to decompose thunderstorms into smaller segments. By using those segments we introduce a new Thunderstorm Intensity Index (TSII). Based on the mathematical background of lightning jump, TSII aims to identify the area which is most affected by the storm. Such index captures location in space and time where a thunderstorm experienced a sudden positive change in lightning activity, using the Eulerian standpoint. The advantage is independence to total number of flashes produced by the storm (which can vary significantly), and high temporal monitoring (2 min). An ongoing research (within SWALDRIC project) is performed on period of 11 years of lightning data and in a study area of NE Adriatic region. Validation is done against precipitation, wind, hail, waterspouts and comparison with ERA5 instability indices is made. Results show very good agreement between higher rain intensities and total precipitation in vicinity of TSII. Good agreement with hail occurrence, waterspout presence and wind gusts within 15km radius. Also, TSII turned to be invariant to the size of the system, thus allowing us to recognise small scale intense thunderstorms.&lt;/p&gt;

Thunderstorm Classification Functions Based on Instability Indices and GNSS IWV for the Sofia Plain

&lt;p&gt;Bulgaria is a country with a high frequency of hail and thunderstorms from May to September. For the May&amp;#8211;September 2010&amp;#8211;2015 period, statistical regression analysis was applied to identify predictors/classification functions that contribute skills to thunderstorm forecasting in the Sofia plain. The functions are based on (1) instability indices computed from radiosonde data from Sofia station F1, and (2) combination of instability indices and Integrated Water Vapor (IWV), derived from the Global Navigation Satellite System (GNSS) station Sofia-Plana, F2. Analysis of the probability of detection and the false alarm ratio scores showed the superiority of the F2 classification function, with the best performance in May, followed by June and September. F1 and F2 scores were computed for independent data samples in the period 2017&amp;#8211;2018 and confirmed the findings for the 2010&amp;#8211;2015 period. Analysis of IWV and lightning flash rates for a multicell and supercell thunderstorm in June and July 2014 showed that the monthly IWV thresholds are reached 14.5 and 3.5 hours before the thunderstorm, respectively. The supercell IWV peak registered 40 min before the thunderstorm, followed by a local IWV minimum corresponding to a peak in the flash rate. In both cases, an increase of IWV during severe hail was registered, which is likely related to the hydrometeor contribution to GNSS path delay. The results of this study will be integrated into the Bulgarian Integrated NowCAsting tool for thunderstorm forecasting in the warm/convective season.&lt;/p&gt;

Sounding-derived parameters associated with severe hail events in Romania

The present paper analyzes 549 severe weather events reported to the ESWD (European Severe Weather Database) that caused large hail in the territory of Romania. Values of atmospheric instability indices have been analyzed for these episodes using data from Bucharest and Budapest sounding stations. For a period of 140 days with episodes of large hail, 24 instability indices were analyzed to describe the atmospheric conditions of the main daily convective activity. The mean values for most indices characterize an unstable atmospheric environment. Of the indices that measure potential instability, VT (vertical totals index) and TT (totals index) had values that described a conductive atmospheric environment for the development of hailstorms. In addition, the interquartile values of LIV (lifted index using virtual temperature) had values lower than zero. For SWEAT (severe weather threat index) and CAPEV (convective available potential energy index using virtual temperature), only the values in the 75th percentile describe a very unstable environment (according to the literature). Strong linear correlations were registered between several pairs of indices such as CAPEV-LIV and SWEAT-SI that can be used for the operational forecast of hail.