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

Authors

K. K. Osuri, Department of Agronomy and Department of Earth, Atmospheric, and Planetary Sciences, Purdue University, West Lafayette, IN 47907, USA
R. Nadimpalli, School of Earth Ocean and Climate Sciences, Indian Institute of Technology, Bhubaneswar, Odisha – 751 007, India
U. C. Mohanty, School of Earth Ocean and Climate Sciences, Indian Institute of Technology, Bhubaneswar, Odisha – 751 007, India
F. Chen, National Center of Atmospheric Research, Boulder, Colorado 80301, USA
M. Rajeevan, Ministry of Earth Sciences, New Delhi – 110003, India
Dev Niyogi, PurdueFollow

Abstract

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.

Comments

K. K. Osuri, R. Nadimpalli, U. C. Mohanty, F. Chen, M. Rajeevan & D. Niyogi Improved prediction of severe thunderstorms over the Indian Monsoon region using high-resolution soil moisture and temperature initialization. Scientific Reports 7, Article number: 41377. http://dx.doi.org/10.1038/srep41377

(CC BY 4.0)

Date of this Version

2016

DOI

10.1038/srep41377

Repository Citation

K. K. Osuri, R. Nadimpalli, U. C. Mohanty, F. Chen, M. Rajeevan & D. Niyogi Improved prediction of severe thunderstorms over the Indian Monsoon region using high-resolution soil moisture and temperature initialization. Scientific Reports 7, Article number: 41377. http://dx.doi.org/10.1038/srep41377

Custom Citation

K. K. Osuri, R. Nadimpalli, U. C. Mohanty, F. Chen, M. Rajeevan & D. Niyogi Improved prediction of severe thunderstorms over the Indian Monsoon region using high-resolution soil moisture and temperature initialization. Scientific Reports 7, Article number: 41377. http://dx.doi.org/10.1038/srep41377

Volume

7

Embargo

2-16-2017