Modelling the impact of climate change on thunderstorm in Bangladesh based on global climate model simulations

Abstract

Climate change is an inevitable global challenge with long-term implications for the sustainable development of all countries. A changing climate leads to the changes in the frequency, intensity, spatial extent, duration, and timing of weather and climate extremes, and may also result in unprecedented extremes. With this changing climate, increase in severity and frequency of extreme weather events like thunderstorms and lightning activity over the globe is now a well-known phenomenon. In recent years, lightning incidents are also becoming more frequent in Bangladesh and claiming massive death toll. As Bangladesh is already known as one of the most vulnerable countries of the world in the event of climate change due to its unique geographical location, this vulnerability of the country due to climate change necessitates the investigation of the potential change in the frequency and regional variability of future thunderstorm activity in Bangladesh due to global warming in the 21st century. In this study temporal and spatial thunderstorm (TH) activity in Bangladesh for early (2020s), mid (2050s) and late century (2080s) has been investigated based on CMCC_CM (Centro Euro-Mediterraneo per Cambiamenti Climatici Climate Model) global climate data under RCP 8.5 scenario from the Coupled Model Intercomparison Project-Phase 5 (CMIP5).

This study demonstrates a statistically significant increasing trend in annual and seasonal (except winter) thunderstorm (TH) frequencies in Bangladesh for the historic period (1979-2017). The results show that the occurrence of thunderstorm is high in pre-monsoon and monsoon with the maximum number of occurrences in the month of April-May. On the other hand, the spatial analysis reveals that the northeastern and northern regions are the most thunderstorm prone while the southern part of Bangladesh is the least due to the variation of topography, atmospheric instability parameters and development of the low-pressure system over the country.

Atmospheric instability parameters (AIP) such as Convective Available Potential Energy (CAPE) and vertical wind shear (VWS) have widely been used to characterize the meteorological conditions that foster severe thunderstorm formation. Trend and spatiotemporal variability of CAPE and VWS have also been studied for the whole country. The trend analysis for 1979-2017 shows an increasing trend in annual and seasonal (except winter) CAPE whereas a decreasing trend for annual VWS.

This study explored the temporal relationship between thunderstorm and climatic variable (convective precipitation (CP), total precipitation (TP)) and AIP (CAPE, VWS) to understand the influence of them on the thunderstorm activity in Bangladesh. The results from the country-average analysis indicates that the occurrence of thunderstorm is highly correlated with CAPE, CP and TP with correlation coefficients (R) of 0.69, 0.65 and 0.63, respectively, on monthly scale.

Using the climate predictors (CP and TP) and AIP, statistical thunderstorm frequency prediction models (linear and non-linear regression) has been developed. The variables have been used in different combination as predictors. For non-linear regression generalized reduced gradient and simplex method has been used for optimization. Among the models, the non-linear regression model with CP and CAPE as predictors has been chosen for future thunderstorm frequency computation as it provided highest correlation.

AIP parameters (CAPE and VWS) for the 21st century has been computed using Metpy toolbox. CMCC model simulated future atmospheric state air temperature, geo-potential height, and relative humidity, at several standard pressure levels has been used as input in Metpy. The thermodynamic properties of the lifted air parcel have been computed at different vertical pressure levels and hence CAPE and VWS have been computed at each horizontal grid of the selected GCM within Bangladesh. Comparison of CAPE, VWS and CP data from the CMCC GCM and those from the ERA-interim reanalysis data shows that there are some biases in the CMCC data for the base period 1979-2005. Therefore, bias correction techniques based on either Quantile mapping (QMAP) or Artificial Neural Network have been applied. Results from temporal variation of future bias corrected CAPE shows a noticeable increase in the coming future with the highest increase in CAPE in 2080. Consistent with previous studies, a decreasing trend in VWS has been noticed as a result of a weakening horizontal temperature gradient between the tropic and pole due to climate change.

Future thunderstorm frequency has been computed from the bias corrected CAPE and CP using the best statistical TH frequency model developed in this study. The risk of thunderstorms in Bangladesh is projected to become more common in a future climate due to increased CAPE and CP. Annual changes in TH frequency in different stations are projected to vary between -3 to 20% in 2020, 9 to 35% in 2050 and 16 to 60% in 2080. Spatial distribution of future thunderstorm depicts that the northeastern part of the country will remain as the most vulnerable region also in the 21st century. The country average changes in TH frequency in pre-monsoon, monsoon, post monsoon and winter season of 2080 are projected to be 39, 35, 68 and 41%, respectively. In summary, this study adds to the rising consensus that there will be more frequent thunderstorm in the coming decades due to increasing atmospheric instability led by the increased moisture and CAPE in a warm future Bangladesh. Thus, the outcome of this study is expected to contribute in disaster preparedness, management and mitigation. However further studies are needed by considering an ensemble of climate models to make a more certain conclusion, even if the potential for thunderstorms is projected to increase in this study because of rising temperatures and more moisture in the atmosphere.