Reanalysis of the Indian summer monsoon: four dimensional data assimilation of AIRS retrievals in a regional data assimilation and modeling framework
Online Publication Date2017-07-04
Print Publication Date2018-04
Permanent link to this recordhttp://hdl.handle.net/10754/625661
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AbstractThis work is the first attempt to produce a multi-year downscaled regional reanalysis of the Indian summer monsoon (ISM) using the National Centers for Environmental Prediction (NCEP) operational analyses and Atmospheric Infrared Sounder (AIRS) version 5 temperature and moisture retrievals in a regional model. Reanalysis of nine monsoon seasons (2003–2011) are produced in two parallel setups. The first set of experiments simply downscale the original NCEP operational analyses, whilst the second one assimilates the AIRS temperature and moisture profiles. The results show better representation of the key monsoon features such as low level jet, tropical easterly jet, subtropical westerly jet, monsoon trough and the spatial pattern of precipitation when AIRS profiles are assimilated (compared to those without AIRS data assimilation). The distribution of temperature, moisture and meridional gradients of dynamical and thermodynamical fields over the monsoon region are better represented in the reanalysis that assimilates AIRS profiles. The change induced by AIRS data on the moist and thermodynamic conditions results in more realistic rendering of the vertical shear associated with the monsoon, which in turn leads to a proper moisture transport and the moist convective feedback. This feedback benefits the representation of the regional monsoon characteristics, the monsoon dynamics and the moist convective processes on the seasonal time scale. This study emphasizes the use of AIRS soundings for downscaling of ISM representation in a regional reanalysis.
CitationAttada R, Parekh A, Chowdary JS, Gnanaseelan C (2017) Reanalysis of the Indian summer monsoon: four dimensional data assimilation of AIRS retrievals in a regional data assimilation and modeling framework. Climate Dynamics. Available: http://dx.doi.org/10.1007/s00382-017-3781-z.
SponsorsWe thank the Director of ESSO-IITM for support. We are grateful to the anonymous reviewers for constructive comments and valuable suggestions, which have helped us to substantially improve this article. We also thank Dr. Oreste Reale for his valuable suggestions, edits and comments on our manuscript. We thank Mr. Cesar Weston and Dr. P. R. C. Reddy for language editing. The authors are grateful to NCAR, Boulder, Colorado, USA for making the WRF-ARW model available. The AIRS data used in this study are obtained from the NASA Goddard Earth Sciences (GES) Data and Information Services Center (DISC) Distributed Active Archive Center (DAAC). Authors are thankful to ECMWF for reanalysis obtained from their data server. Thanks are also due to TRMM and GPCP for providing the rainfall data used in this study. Produced downscale reanalysis in this study is presently available on request basis later it may be provided on open access.