Open AccessComparative evaluation of the skill of a global circulation model and a limited area model in simulating tropical cyclones in the north Indian Ocean
Author(s) -
Mohapatra G. N.,
Rakesh V.,
Mohanty P. K.,
Himesh S.
Publication year - 2018
Publication title -
meteorological applications
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.672
H-Index - 59
eISSN - 1469-8080
pISSN - 1350-4827
DOI - 10.1002/met.1718
Subject(s) - climatology , tropical cyclone , gcm transcription factors , environmental science , tropical cyclone forecast model , cyclone (programming language) , general circulation model , meteorology , forecast skill , computer science , geography , geology , oceanography , climate change , field programmable gate array , computer hardware
Considerable improvement has taken place in forecasting tropical cyclones at 24–48 hr leads; however, improving the accuracy of tropical cyclone forecasts at longer leads is still a major scientific challenge. The major bottleneck in accurate tropical cyclone forecasts using limited area models (LAMs) comes from the use of artificial lateral boundary conditions, especially at longer leads. Although global circulation models (GCMs) still cannot match the horizontal resolution that can be implemented in a LAM over a smaller domain, it is possible that better representation of scales and thus scale interactions in a global domain can lead to better simulation of tropical cyclones with a GCM even with relatively coarser resolution. This hypothesis is tested in the present work with a GCM and a LAM configuration. Thirty cyclones over the north Indian Ocean that represent different seasons and intensities during 1999–2012 are considered. Analysis of forecast skills at three leads (24 hr, 48 hr and 96 hr) show that while the LAM has better skill compared to the GCM at shorter leads (<48 hr), the GCM has significantly higher skill at longer leads (96 hr). The two configurations are found to exhibit somewhat complementary skills in terms of forecast lead and the severity of the cyclones. Therefore, it is suggested that a methodology combining both LAMs and GCMs can provide more reliable forecasts.