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The influence of heat, moisture and moist static energy (MSE) budget, over the Arabian Sea and adjoining area (0*-30*N and 30*E-75*E), on the onset and activities of Asian summer monsoon has been studied in detail. The data base for this study consists of twice daily FGGE Level IIIb analysis for the period 16 May to 15 July 1979.The pentad mean variation, the vertical distribution and period averages of the various terms in energy budget equations are closely examined to find out their influence on the activities of monsoon. The study indicates the significant increase in the net enthalpy, latent heat energy (LHE), MSE and a number of budget parameters, well in advance of the onset of monsoon over Kerala coast. Further, a decreasing trend is observed in most of the above parameters about 5 days before the break monsoon condition which started over India on 16 July, 1979.The vertical distributions of the budget parameters reveal that during active monsoon period secondary maxima of horizontal heat and MSE flux divergences are observed in the upper troposphere which are replaced by minima during weak monsoon circulation. The broad features of the budget studies over the Arabian Sea are in good agreement with the large scale energetics (Mohanty et al. 1982a(Mohanty et al. , 1982b. Some of the significant departures in the results of the two studies have been discussed.

Abstract. In this study a non-hydrostatic version of Penn State University (PSU) -National Center for Atmospheric Research (NCAR) mesoscale model is used to simulate the super cyclonic storm that crossed Orissa coast on 29 October 1999. The model is integrated up to 123 h for producing 5-day forecast of the storm. Several important fields including sea level pressure, horizontal wind and rainfall are compared with the verification analysis/observation to examine the performance of the model. The model simulated track of the cyclone is compared with the best-fit track obtained from India Meteorological Department (IMD) and the track obtained from NCEP/NCAR reanalysis. The model is found to perform reasonably well in simulating the track and in particular, the intensity of the storm.

Forecasting thunderstorm is one of the most difficult tasks in weather prediction, due to their rather small spatial and temporal extension and the inherent nonlinearity of their dynamics and physics. Accurate forecasting of severe thunderstorms is critical for a large range of users in the community. In this paper, experiments are conducted with artificial neural network model to predict severe thunderstorms that occurred over Kolkata during May 3, 11, and 15, 2009, using thunderstorm affected meteorological parameters. The capabilities of six learning algorithms, namely, Step, Momentum, Conjugate Gradient, Quick Propagation, Levenberg-Marquardt, and Delta-Bar-Delta, in predicting thunderstorms and the usefulness for the advanced prediction were studied and their performances were evaluated by a number of statistical measures. The results indicate that Levenberg-Marquardt algorithm well predicted thunderstorm affected surface parameters and 1, 3, and 24 h advanced prediction models are able to predict hourly temperature and relative humidity adequately with sudden fall and rise during thunderstorm hour. This demonstrates its distinct capability and advantages in identifying meteorological time series comprising nonlinear characteristics. The developed model can be useful in decision making for meteorologists and others who work with real-time thunderstorm forecast.

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In this article, the interannual variability of certain dynamic and thermodynamic characteristics of various sectors in the Asian summer monsoon domain was examined during the onset phase over the south Indian peninsula (Kerala Coast). Daily average (0000 and 1200 UTC) reanalysis data sets of the National Centre for Environmental Prediction/National Centre for Atmospheric Research (NCEP/NCAR) for the period 1948-1999 were used. Based on 52 years onset date of the Indian summer monsoon, we categorized the pre-onset, onset, and post-onset periods (each an average of 5 days) to investigate the interannual variability of significant budget terms over the Arabian Sea, Bay of Bengal, and the Indian peninsula. A higher difference was noticed in low-level kinetic energy (850 hPa) and the vertically integrated generation of kinetic energy over the Arabian Sea from the pre-onset, onset, and post-onset periods. Also, significant changes were noticed in the net tropospheric moisture and diabatic heating over the Arabian Sea and Indian peninsula from the pre-onset to the post-onset period. It appears that attaining the magnitude of 40 m 2 s -2 and then a sharp rise in kinetic energy at 850 hPa is an appropriate time to declare the onset of the summer monsoon over India. In addition to a sufficient level of net tropospheric moisture (40 mm), a minimum strength of low-level flow is needed to trigger convective activity over the Arabian Sea and the Bay of Bengal. An attempt was also made to develop a location-specific prediction of onset dates of the summer monsoon over India based on energetics and basic meteorological parameters using multivariate

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The very severe cyclonic storm (VSCS) “Phailin (2013)” was the strongest cyclone that hit the eastern coast of the India Odisha state since the supercyclone of 1999. But the same story of casualties was not repeated as that of 1999 where approximately 10 000 fatalities were reported. In the case of Phailin, a record 1 million people were evacuated across 18 000 villages in both the Odisha and Andhra Pradesh states to coastal shelters following the improved operational forecast guidance that benefited from highly skillful and accurate numerical model guidance for the movement, intensity, rainfall, and storm surge. Thus, the property damage and death toll were minimized through the proactive involvement of three-tier disaster management agencies at central, state, and district levels.