ABSTRACT:The climatology of thunderstorm (TS) activities over Bangladesh has been investigated using monthly, seasonal, and annual time series data of 29 meteorological stations in the country for a maximum period of 35 years . The climatology of the TS and its inter-annual variability and trends have been investigated using country average as well as station-wise data. The results of the trend analysis show that the country average TS frequency exhibits statistically significant trends for annual and seasonal data, except for winter. The monthly TS frequency shows significant increasing trends for the months April-November. The station-wise analysis of annual and seasonal data shows dominant increasing trends over the country, with a few stations having negative trends. The correlation coefficients of the time series of seasonal and annual TS frequency with rainfall and minimum and maximum temperature have been computed. Also, the composite climatology of geopotential height and temperature fields of the troposphere covering Bangladesh and its surrounding areas for the month of May individually for the years with high TS frequency and low TS frequency has been presented and analysed. The low level moisture and meridional component of wind fields have also been considered. Additionally, the correspondence of TS frequency for this month with the low level vertical wind shear (VWS) between 850 and 500 hpa levels for the u-component of the wind has also been studied using the data of 1976-2010, which shows that the TS frequency is correlated with VWS.

Drought is one of the most extreme climatic events in South Asia (SA) and has affected 1.44 billion people in last 68 years. The agriculture in many areas of this region is highly dependent on rainfall, which increases the vulnerability to drought. To mitigate the impact of drought on agriculture and food security, this study aims to develop a state-of-the-art system for monitoring agricultural drought over SA at a high spatial resolution (0.25∘) in near real-time. This study currently focuses on the rain-fed area, and the impact of irrigation is not incorporated. This open and interactive tool can assist in monitoring the near-present soil moisture conditions, as well as assessing the historical drought conditions for better management. The South Asia Drought Monitor (SADM) runs the mesoscale hydrologic model to simulate the soil moisture using observation-based meteorological forcing (at near real-time), morphological variables, and land cover data. The soil moisture index (SMI) has been calculated by estimating the percentile of the simulated soil moisture. The drought monitor displays the SMI in five classes based on severity: abnormally dry, moderate drought, severe drought, extreme drought and exceptional drought. The main functions of this open interactive system include the provisioning of up-to-date and historical drought maps, displaying long-term drought conditions and downloading soil moisture data. Comparison of the SMI with the standardized precipitation evapotranspiration index (SPEI) shows that the SMI and SPEI depict similar temporal distribution patterns. However, the SPEI (for 4, 6, 9 and 12 months) differs in the representation of the dry conditions in 1992, 2009, and 2015 and the wet condition in 1983, 1988, and 1990. We evaluated the implications of using different precipitation forcings in a hydrological simulation. A comparison of major drought characteristics such as areal extent, duration, and intensity, using different precipitation datasets show that uncertainty in precipitation forcings can significantly influence model output and drought characteristics. For example, the areal extent of one of the most severe droughts from 1986 to 1988 differs by 9% between ERA5 and CHIRPSv2.

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<p>South Asia (SA) is highly vulnerable to extreme climatic events and experiences a wide range of natural hazards such as floods, drought, storms, and sea-level rise.  Droughts are recurrent in SA and its impact on regional agriculture, food storage, and livelihood is enormous. Agricultural droughts have severe consequences on the economy, society, health and water resources sectors. In this work, a state-of-the-art monitoring system of soil moisture drought in SA is developed. This study aims at improving the agricultural drought monitoring system for SA and contributing towards better adaptation solutions in the region. The SA drought monitoring system is inspired by the German Drought Monitor (www.ufz.de/duerremonitor)[1]. First, we implement the mesoscale hydrologic model (mHM, https://git.ufz.de/mhm) to reconstruct daily soil moisture from 1981 to 2019 using a near-real-time precipitation product (CHIRPS version 2, 0.25-degree resolution). Second, the SMI is estimated with a non-parametric kernel-based cumulative distribution function [2] based on mHM’s historic soil moisture reconstruction. The generated SMI maps are classified into five classes based on severity: abnormally dry, moderate drought, severe drought, extreme drought and exceptional drought. Third, we develop the South Asia Drought Monitor (SADM) which is an interactive web-portal (http://southasiadroughtmonitor.pythonanywhere.com/) for the dissemination of the simulated near-real-time drought classes. To achieve maximum dissemination, the daily and monthly SMI fields will be uploaded and published on the SADM portal. The SADM will help to inform decision-makers, the general public, researchers, and stakeholders in the SA. The drought monitoring system will allow the scientific community to conduct micro-level in-depth research and to enable policymakers to formulate proper planning and to take mitigation measures in sectors encompassing energy, health, forestry, and agriculture at local to regional scales.</p><p> </p><p>[1] Zink, M., Samaniego, L., Kumar, R., Thober, S., Mai, J., Schäfer, D., Marx, A., 2016: The German drought monitor, Environ. Res. Lett. 11 (7), art. 074002, DOI:10.1088/1748-9326/11/7/074002.</p><p>[2] Samaniego, L., Kumar, R. and Zink, M.,2013: Implications of Parameter Uncertainty on Soil Moisture Drought Analysis in Germany, Journal of Hydrometeorology, DOI: 10.1175/JHM-D-12-075.1.</p><p> </p>