Drought is primarily an agricultural phenomenon that refers to conditions where plants are responsive to certain levels of moisture stress that affect both the vegetative growth and yield of crops. It occurs when supply of moisture stored in the soil is insufficient to meet the optimum need of a particular type of crop. Causes of drought in Bangladesh are related to climate variability and non-availability of surface water resources. While it may be possible to indicate the immediate cause of a drought in a particular location, it often is not possible to identify an underlying cause. Therefore, to improve all these services in favour of enhancing agricultural production and reducing food insecurity in Bangladesh, it is mandatory to develop an effective way for disseminating the SPI data indicating drought indices to farmers, and enhance drought and climate resilience. To develop future plan and policy in agricultural sector of Bangladesh, it is vital to understand the previous droughts events with accurate indicators. Since this study will contribute to the agricultural development of Bangladesh therefore there is an obvious need to understand the change of drought frequency all over Bangladesh using a standardized drought index. The main intention of this project is to prepare a proper baseline for forecasting drought indices using SPI data. So, the final outcome of this project would be a knowledge base where a proper forecasting tools and dissemination networks can be updated/developed for farmers.

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.