Author Correction: On the processes influencing rapid intensity changes of tropical cyclones over the Bay of Bengal.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

On the processes influencing rapid intensity changes of tropical cyclones over the Bay of Bengal.

We present a numerical investigation of the processes that influenced the contrasting rapid intensity changes in Tropical Cyclones (TC) Phailin and Lehar (2013) over the Bay of Bengal. Our emphasis is on the significant differences in the environments experienced by the TCs within a few weeks and the consequent differences in their organization of vortex-scale convection that resulted in their different rapid intensity changes. The storm-relative proximity, intensity, and depth of the subtropical ridge resulted in the establishment of a low-sheared environment for Phailin and a high-sheared environment for Lehar. Our primary finding here is that in Lehar's sheared vortex, the juxtaposition in the azimuthal phasing of the asymmetrically distributed downward eddy flux of moist-entropy through the top of the boundary layer, and the radial eddy flux of moist-entropy within the boundary layer in the upshear left-quadrant of Lehar (40-80 km radius) establishes a pathway for the low moist-entropy air to intrude into the vortex from the environment. Conversely, when the azimuthal variations in boundary layer moist-entropy, inflow, and convection are weak in Phailin's low-sheared environment, the inflow magnitude and radial location of boundary layer convergence relative to the radius of maximum wind dictated the rapid intensification.

High-resolution gridded soil moisture and soil temperature datasets for the Indian monsoon region.

High-resolution soil moisture/temperature (SM/ST) are critical components of the growing demand for fine-scale products over the Indian monsoon region (IMR) which has diverse land-surface characteristics. This demand is fueled by findings that improved representation of land-state help improve rainfall/flood prediction. Here we report on the development of a high-resolution (4 km and 3 hourly) SM/ST product for 2001-2014 during Indian monsoon seasons (June-September). First, the quality of atmospheric fields from five reanalysis sources was examined to identify realistic forcing to a land data assimilation system (LDAS). The evaluation of developed SM/ST against observations highlighted the importance of quality forcing fields. There is a significant relation between the forcing error and the errors in the SM/ST. A combination of forcing fields was used to develop 14-years of SM/ST data. This dataset captured inter-annual, intra-seasonal, and diurnal variations under different monsoon conditions. When the mesoscale model was initialized using the SM/ST data, improved simulations of heavy rain events was evident, demonstrating the value of the data over IMR.

Improved prediction of severe thunderstorms over the Indian Monsoon region using high-resolution soil moisture and temperature initialization.

The hypothesis that realistic land conditions such as soil moisture/soil temperature (SM/ST) can significantly improve the modeling of mesoscale deep convection is tested over the Indian monsoon region (IMR). A high resolution (3 km foot print) SM/ST dataset prepared from a land data assimilation system, as part of a national monsoon mission project, showed close agreement with observations. Experiments are conducted with (LDAS) and without (CNTL) initialization of SM/ST dataset. Results highlight the significance of realistic land surface conditions on numerical prediction of initiation, movement and timing of severe thunderstorms as compared to that currently being initialized by climatological fields in CNTL run. Realistic land conditions improved mass flux, convective updrafts and diabatic heating in the boundary layer that contributed to low level positive potential vorticity. The LDAS run reproduced reflectivity echoes and associated rainfall bands more efficiently. Improper representation of surface conditions in CNTL run limit the evolution boundary layer processes and thereby failed to simulate convection at right time and place. These findings thus provide strong support to the role land conditions play in impacting the deep convection over the IMR. These findings also have direct implications for improving heavy rain forecasting over the IMR, by developing realistic land conditions.

Impact of parameterization of physical processes on simulation of track and intensity of tropical cyclone Nargis (2008) with WRF-NMM model.

The present study is carried out to investigate the performance of different cumulus convection, planetary boundary layer, land surface processes, and microphysics parameterization schemes in the simulation of a very severe cyclonic storm (VSCS) Nargis (2008), developed in the central Bay of Bengal on 27 April 2008. For this purpose, the nonhydrostatic mesoscale model (NMM) dynamic core of weather research and forecasting (WRF) system is used. Model-simulated track positions and intensity in terms of minimum central mean sea level pressure (MSLP), maximum surface wind (10 m), and precipitation are verified with observations as provided by the India Meteorological Department (IMD) and Tropical Rainfall Measurement Mission (TRMM). The estimated optimum combination is reinvestigated with six different initial conditions of the same case to have better conclusion on the performance of WRF-NMM. A few more diagnostic fields like vertical velocity, vorticity, and heat fluxes are also evaluated. The results indicate that cumulus convection play an important role in the movement of the cyclone, and PBL has a crucial role in the intensification of the storm. The combination of Simplified Arakawa Schubert (SAS) convection, Yonsei University (YSU) PBL, NMM land surface, and Ferrier microphysics parameterization schemes in WRF-NMM give better track and intensity forecast with minimum vector displacement error.

Comparison of thunderstorm simulations from WRF-NMM and WRF-ARW models over East Indian Region.

The thunderstorms are typical mesoscale systems dominated by intense convection. Mesoscale models are essential for the accurate prediction of such high-impact weather events. In the present study, an attempt has been made to compare the simulated results of three thunderstorm events using NMM and ARW model core of WRF system and validated the model results with observations. Both models performed well in capturing stability indices which are indicators of severe convective activity. Comparison of model-simulated radar reflectivity imageries with observations revealed that NMM model has simulated well the propagation of the squall line, while the squall line movement was slow in ARW. From the model-simulated spatial plots of cloud top temperature, we can see that NMM model has better captured the genesis, intensification, and propagation of thunder squall than ARW model. The statistical analysis of rainfall indicates the better performance of NMM than ARW. Comparison of model-simulated thunderstorm affected parameters with that of the observed showed that NMM has performed better than ARW in capturing the sharp rise in humidity and drop in temperature. This suggests that NMM model has the potential to provide unique and valuable information for severe thunderstorm forecasters over east Indian region.