4.5 Article

Comparison of Reanalysis Data Sets to Comprehend the Evolution of Tropical Cyclones Over North Indian Ocean

Journal

EARTH AND SPACE SCIENCE
Volume 7, Issue 2, Pages -

Publisher

AMER GEOPHYSICAL UNION
DOI: 10.1029/2019EA000978

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Funding

  1. Department of Science and Technology (DST), India

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Several reanalysis data sets are being used for understanding the role of environmental factors controlling tropical cyclones (TCs) evolution. Six reanalysis data sets, namely, European Center for Medium-range Weather Forecast (ECMWF) ERA-Interim (ERAI) reanalysis, Global Forecast System (GFS) analysis, Japan Meteorological Agency's 55-year reanalysis projects reanalysis (JRA55), Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA2) reanalysis, NCEP Climate Forecast System Reanalysis (CFSR), and fifth generation of ECMWF atmospheric reanalysis of global climate (ERA5), have been evaluated for the representation of track, intensity, and structure of 28 TCs which occurred over North Indian Ocean (NIO) during the period 2006-2015. The errors in track, intensity, and minimum sea level pressure (MSLP) of TCs are estimated with respect to the best track data set of India Meteorological Department (IMD). The representation of inner core structure of TCs has been compared. The smallest error in the position of TCs center, MSLP, and maximum wind speed is found in GFS analysis followed by ERA5 and CFSR reanalysis, respectively. GFS and CFSR data sets capture the most intense stages of the TCs followed by the ERA5 data set, while the other three are unable to obtain intensification beyond the severe cyclonic storm stage. The structures of TCs are better represented in GFS analysis followed by ERA5 reanalysis. However, GFS analysis represents early intensification and, in some cases, overprediction of the category of TCs, especially during the most intensified stages (beyond cyclonic storms). Thus, GFS analysis captures the evolution of TCs more realistically, followed by the ERA5 reanalysis data set.

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