The Dhaka University Journal of Earth and Environmental Sciences, Vol. 9 (2): 2020 Assessing Atmospheric Instability over the Bay of Bengal during October and November Months between 2007 – 2018 Saurav Dey Shuvo and Md. Rabiul Awal Department of Meteorology, University of Dhaka, Dhaka 1000, Bangladesh Manuscript received: 12 December 2020; accepted for publication: 22 April 2021 ABSTRACT: An attempt has been made in this research to delineate a pattern for atmospheric instability during the months of October and November from 2007 to 2018. The results show an alarming trend of increasing instability throughout the study period. The average temperature at 2-meters height around the Bay of Bengal has changed significantly over time. Most notably, the gap between monthly average highest and monthly average lowest temperatures (at 2-meters height) is more or less increasing from 2007 to 2018 – ranging from 3.0 degrees to 11.0 degrees Celsius. Similar tendencies are observed for CAPE (Convective Available Potential Energy) as well – with the highest value of more than 3000 J/Kg. The findings of this research will help in understanding the prevailing conditions over the Bay, and also enable better preparedness for any potential severe convective activities. Keywords: Atmospheric instability, Bay of Bengal, 2-m Air Temperature, CAPE INTRODUCTION surface, ocean, planetary boundary layer, and convective processes (Zhang and Emanuel, 2016; Xie Bangladesh is a deltaic country, located in South and Kubokawa, 1990). Several reasons; including – Asia – with the Himalayas to her North and the Bay of the re-curvature phenomena of a tropical cyclone in Bengal to her South. The coastal region represents an the Bay of Bengal, shallow continental shelf, funnel area of 47, 201 square kilometers (km), which is about shape at the head of the Bay of Bengal, almost sea- 32% of Bangladesh’s total geographical coverage level orography of the coastal land, and high density (Rasheed, 2008). Bangladesh is globally recognized as of population; are responsible for the large impacts of one of the most vulnerable countries due to natural tropical cyclones in Bangladesh (Murty and El-Sabh, disasters. In 2004, the United Nations Development 1992). The climatic conditions of the country are Program (UNDP) ranked Bangladesh as the number modified and regulated by these unique settings, but one nation at risk for tropical cyclones and number six ultimately make the country more vulnerable to for floods (MoEF, 2009). tropical cyclones (Paul and Routray, 2010; Ali, 1996). Tropical Cyclones in the past have caused massive Bangladesh is regularly affected by devastating damage to the coastal region of Bangladesh (Ramsay, natural disasters because of its geographic location, 2017). The post-monsoon months are always a threat unique natural settings, and characteristics of tropical to the country as some of the most destructive tropical monsoon (Paul, 2012; Haque, 1995; Elahi, 1991). The cyclones have formed during this season – mostly most common and catastrophic natural disasters that during October and November (Singh, 2007). So far commonly occur include tropical cyclones, storm in this century – Cyclone Sidr has been the most surges, tornados, floods, droughts, and nor-westers destructive post-monsoonal TC (Islam et al., 2011), (Ali, 1999). The country is hit by at least one tropical which made landfall on Bangladesh’s coast at around cyclone each year (Haque, 1997; Mooley, 1980) that th 1600 UTC on 15 November 2007 (Paul, 2009). makes the coastal area more unsafe for the people Although no such post-monsoon cyclones with that living there (Murty and Neralla, 1992). The much intensity have not hit Bangladesh since, the meteorological origin of tropical cyclones (TC) is probability of recurrence for such a catastrophe is not owing to many complex interactions among land so low either (Bensi and Weaver, 2020); especially considering the situation of the Bay in October and Corresponding author: Saurav Dey Shuvo November of recent years (Baaqeel et al., 2018). Email: [email protected] Atmospheric Instability is always responsible for the intensification of convective activities (Chen et al., DOI: https://doi.org/10.3329/dujees.v9i2.55089 2015; Caron et al., 2013; Craig and Gray, 1996). 46 Shuvo and Awal Again, an imbalance in temperature is vital for the collects observational data from the Global increase in atmospheric instability (Gubenko and Telecommunications System (GTS) and other sources Rubinshtein, 2015; Marinaki et al., 2006). And, for analysis. Final Reanalysis (FNL) 1-degree by 1- formation of tropical cyclones is closely related to an degree data collected from National Center for increase in atmospheric instability (Lahaye and Environmental Prediction (NCEP) is used as initial Zeitlin, 2016; Williams and Renno, 1993). Apart from and Lateral Boundary Conditions (LBCs), which are that, there is a positive correlation between the updated at six hours intervals. strength of tropical cyclones and the prevalence of Table 1: An Overview of the Experimental Design for this atmospheric instability (Takemi and Yamasaki, 2020). Research Tropical cyclones in the Bay of Bengal, especially those formed in post-monsoon, are frequently Properties Configuration for the Research becoming stronger (Balaguru et al., 2014; Krishna, Dynamics Non-hydrostatic 2009). Therefore, research on the situation regarding Microphysics Ferrier (new Eta) scheme the recent condition of atmospheric instability over the Radiation scheme Dudhia for short-wave Bay is highly necessary. Studying the evolution of radiation / RRTMG for atmospheric instability will provide a better long-wave understanding of the genesis of tropical cyclones, Surface layer Noah-LSM scheme which in turn will assist in a more accurate prediction Cumulus parameterization Kain-Fritsch scheme of tropical cyclones (Montgomery and Smith, 2017; schemes Meng and Zhang, 2012). Therefore, the objective of PBL parameterization Yonsei University scheme Number of domains 01 (one) this research is to determine the tendency of Central points of the domain Central Latitude: 18°N; atmospheric instability over the Bay of Bengal during Central Longitude: 91°E October and November. Horizontal grid distance 18 kilometers Integration time step 90 seconds METHODOLOGY AND DATA USED IN THIS Number of grid points X-direction: 54 points; Y- RESEARCH direction: 108 points Map projection Mercator The study was done by recreating past scenarios Horizontal grid distribution Arakawa C-grid with the help of forcing data through the WRF Vertical co-ordinate Terrain-following (Weather Research and Forecasting) Model (version hydrostatic-pressure co- 4.0.1). The Weather Research and Forecasting (WRF) ordinate (33 sigma levels model (version 4.0.1) has been used to derive the up to 100 hPa) Time integration 3rd order Runge-Kutta temperature and CAPE values for the post-monsoon th season in Bangladesh. In the present research, the Spatial differencing scheme 6 order centered differencing ARW solver of the WRF model has been used. The Initial conditions Three-dimensional real- ARW system consists of fully compressible non- data (FNL: 1° × 1°) hydrostatic equations and different prognostic Lateral boundary condition Specified options for real- variables. The model’s vertical coordinate is terrain data following hydrostatic pressure and the horizontal grid Top boundary condition Gravity wave absorbing is Arakawa C-grid. Great detail on WRF Model can (diffusion or Rayleigh be found in the works of Skamarock et al. (2008). damping) Bottom boundary condition Physical or free-slip Table 1 has all the necessary information regarding Diffusion and Damping Simple Diffusion with No the setup of the experimental design for this research. Damping For this study, NCEP FNL Operational Model The WRF model has been configured in a single- Global Tropospheric Analyses data have been used nested domain (Figure 1) of 18 km horizontal grid from NCAR’s Research Data Archive (NCEP, 2000) spacing with 54×108 grids in the east-west and north- to simulate the surface temperature and convective south directions and 33 vertical levels. In this available potential energy over the coastal region of research, the Ferrier (new Eta) microphysics scheme Bangladesh during the post-monsoon season. Global coupling with the Kain-Fritsch cumulus Data Assimilation System (GDAS) continuously parameterization scheme has been used. Assessing Atmospheric Instability over the Bay of Bengal 47 The model has been integrated by using initial and values for 24 months (October and November for 12 LBCs from NCEP-FNL analyses data (Dutra et al., consecutive years) have been calculated from 2017) at six hourly intervals. The model has been simulated results. Again, CAPE is an essential simulated continuously for 31 days to get a long-range atmospheric instability index for studying tropical observational scenario starting with the initial cyclones (Molinari et al., 2012) and requires the conditions for 0000 UTC of 1st October and temperature values for calculation (Moncrieff and continuing up to 1800 UTC of 31st October; for the Miller, 1976). Monthly averaged CAPE values have years of 2007 to 2018. With a similar mechanism and been calculated and used in this research. Also, it experimental setup, simulated values of November should be noted that – all the averages used in this (for the aforementioned 12 years) have also been research are temporal averages, not spatial averages obtained. The instability