Investigation on the Influence of the Column Ozone Anomaly on the Energetics of Tropical Cyclones Over NIO and Related Air–Sea Interaction

An investigation on the temporal and spatial variation of ozone using the total column ozone (TCO) values during the cyclonic activities over North Indian Ocean (NIO) is carried out during the period from 1997 to 2012. The stepwise variation of TCO during the passage of the tropical cyclones over the Bay of Bengal and the Arabian Sea of the NIO is examined. The anomalies in TCO are estimated at each step of the life span of the cyclones starting from the genesis to landfall stages. The result reveals that the TCO values are quite high prior to the formation of the depression over NIO; however, at the stage of cyclogenesis it decreases which, with the increase in the intensity of the cyclones, further decreases and becomes minimum near the coast during the landfall. The maximum negative anomaly in TCO is observed for maximum intensity of the tropical cyclones as well as during the landfall. The result further shows that when the cyclones die out after the landfall the TCO regains the normal value. It is further observed that the reduction in TCO enhances the accumulated cyclone energy over NIO. The result finally shows that, the higher the energy of the cyclones, the lower becomes the stratospheric warming, that is, the higher the stratospheric cooling.     

Convective energies in forecasting severe thunderstorms with one hidden layer neural net and variable learning rate back propagation algorithm

Thunderstorms are perennial features of India. However, the severe thunderstorms of pre — monsoon season (April–May) over Kolkata (22°32′N, 88°20′E) are of great concern for imparting devastating effect on life and property on the ground and aviation aloft. The study is thus, focused on developing one hidden layer neural network model with variable learning rate back propagation algorithm to forecast such thunderstorms. Convective available potential energy (CAPE) and convective inhibition energy (CIN) are selected as the input parameters of the model after the estimation of various skill scores like, Probability of Detection (POD), False Alarm Ratio (FAR), Heidke Skill Score (HSS) and Odds Ratio Skill Score (Yule’s Q) on different stability indices. During training the model, the squared error for forecasting severe thunderstorms is observed to be 0.0022 when the values of CIN within the range of 0 to 140 J kg^?1 is taken as the input whereas the error is observed to be 0.0114 while the values of CAPE within the range of 2000 to 7000 J kg^?1 is considered as the input. The values of CIN and CAPE at twelve to six hours prior to the occurrence of severe thunderstorms are considered in this study. During validation of the model, the percentage of prediction error with the values of CIN as input is observed to be 0.042% and that with CAPE as input is 0.162%. The values of CIN within the range of 0–140 J kg^?1 are observed to be more persistent in forecasting severe thunderstorms over Kolkata than the values of CAPE within the range of 2000–7000 J kg^?1.     

Disparity in the characteristic of thunderstorms and associated lightning activities over dissimilar terrains

Thunderstorms and associated lightning flash activities are studied over two different locations in India with different terrain features. Lightning imaging sensor (LIS) data from 1998 to 2008 are analyzed during the pre-monsoon months (March, April and May). The eastern sector is designated as Sector A that represents a 2° × 2° square area enclosing Kolkata (22.65°N, 88.45°E) at the centre and covering Gangetic West Bengal, parts of Bihar and Orissa whereas the north-eastern sector designated as Sector B that also represents a 2° × 2° square area encircling Guwahati (26.10°N, 91.58°E) at the centre and covering Assam and foot hills of Himalaya of India. The stations Kolkata and Guwahati are selected for the present study from Sector A and Sector B, respectively, as these are the only stations over the selected areas having Radiosonde observatory. The result of the present study reveals that the characteristics of thunderstorms over the two locations are remarkably different. Lightning frequency is observed to be higher in Sector B than Sector A. The result further reveals that though the lightning frequency is less in Sector A, but the associated radiance is higher in Sector A than Sector B. It is also observed that the radiance increases linearly with convective available potential energy (CAPE) and their high correlation reveals that the lightning intensity can be estimated through the CAPE values. The sensitivity of lightning activity to CAPE is higher at the elevated station Guwahati (elevation 54 m) than Kolkata (elevation 6 m). Moderate resolution imaging spectrometer (MODIS) data products are used to obtain aerosol optical depth and cloud top temperature and employed to find their responses on lightning radiance.     

Remote sensing and ground-based observations for nowcasting the category of thunderstorms based on peak wind speed over an urban station of India

Thunderstorms are the recurrent features of India and are responsible for the redistribution of excess heat and moisture in the atmosphere. However, the thunderstorms that occur over the urban station Kolkata (22°34′N, 88°22′E), India, during the pre-monsoon months of April and May are extremely devastating while accompanied with high wind speed, lightning flashes, torrential rain and occasional hail and tornadoes. The development and verification of a model output are described in this study. The system consists of multiple linear regression (MLR) equations, and the purpose is to nowcast the categories of thunderstorms over Kolkata, both ordinary (wind speed <65 km h^?1) and severe (wind speed ≥65 km h^?1) as per the warning provided by the India Meteorological Department for the prevalence of thunderstorms. The MODIS terra/aqua satellite data of cloud parameters, ground-based Radiosonde/Rawinsonde upper air observations and records of wind speed accompanied with thunderstorms over Kolkata are considered for the study. The MLR models are formulated with the cloud parameters as input and the target output being the peak wind speed associated with the pre-monsoon thunderstorms. The MLR model is trained with the data and records from 2002 to 2009, and the results are validated with the observations of 2010 and 2011. The results reveal that the accuracy in nowcasting the ordinary and severe categories of thunderstorms during the pre-monsoon season over Kolkata with MLR models are 94.26 and 91.29 %, respectively, with lead time <12 h.     

Performance of Counterfort Walls with Reinforced Granular and Fly Ash Backfills: Experimental Investigation

Experimental investigations on model counterfort retaining walls have been carried out to study the lateral movement of the walls and the nature of the failure modes. Mild steel plates of size 1,000 × 900 × 8 mm were used as model retaining walls and were placed in a tank of size 900 × 900 × 670 mm. Ennore sand, obtained from Madras India, and Fly ash, obtained from Panki Thermal Power Plant, India were used as backfill material. Tests were carried out both with and without reinforced backfill. Two types of loading conditions were applied: (i) line load and (ii) uniform surcharge. The shape and size of the failure wedge was studied by observing displacement of bands of colored through a Perspex plate fixed on one side of the tank. Plots of overturning moment against the rotation of a wall top show that with the increase in rotation of wall, the overturning moment decreases. The minimum value of overturning moment is taken as the limiting value. The failure surfaces obtained in different cases are linear and parabolic in shape.     

Temporal variability in the withdrawal phase of southwest monsoon over India and related consequences in northeast monsoon: a climatological perspective

Theoretical and Applied Climatology - The variability in duration of withdrawal phase of southwest monsoon over India is often witnessed to influence the northeast monsoon rainfall of India as...     

Generalized Potential Temperature in a Diagnostic Study of High Impact Weather over an Urban Station of India

The tropospheric atmosphere is neither absolutely dry nor completely saturated. It is, in general, moist. The purpose of the present study is to reveal the role of generalized potential temperature (GPT) in describing the humid state of the real moist atmosphere pertaining to understanding the prevalence of high impact weather systems over an urban station, Kolkata (22°32′N; 88°20′E), of India. A comparative study among GPT, equivalent potential temperature (EPT), potential temperature and relative humidity to reveal the significance of GPT in a precise understanding of the high impact weather of Kolkata is carried out. To attain the objectives, 50 cases of thunderstorms, 15 cases of tropical cyclones and 15 heavy rainfall days are selected during the pre-monsoon season (April–May) over Kolkata (22°32′N; 88°20′E), India. The condition—decision support system of rough set theory is adopted as the methodology. The result of the study reveals that GPT is the most pertinent convective parameter in estimating the prevalence of the high impact weather of Kolkata during the pre-monsoon season and is observed to be better than RH. The results, thus, show that the moist air is capable of describing the distribution of water vapour and thermodynamic properties of the real atmosphere more precisely than an absolutely dry and completely saturated state of the atmosphere.     

Nowcasting visibility during wintertime fog over the airport of a metropolis of India: decision tree algorithm and artificial neural network approach

Natural Hazards - The endeavor of the present research is to nowcast the spatial visibility during fog over the airport of Kolkata (22.6°N; 88.4°E), India, with artificial neural network...