Premium
Hindcast skill improvement in Climate Forecast System (CFSv2) using modified cloud scheme
Author(s) -
Pokhrel Samir,
Hazra Anupam,
Chaudhari Hemantkumar S.,
Saha Subodh K.,
Paulose Febin,
Krishna Sujith,
Krishna Phani Murli,
Rao Suryachandra A.
Publication year - 2018
Publication title -
international journal of climatology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.58
H-Index - 166
eISSN - 1097-0088
pISSN - 0899-8418
DOI - 10.1002/joc.5478
Subject(s) - hindcast , environmental science , climatology , teleconnection , precipitation , monsoon , forecast skill , mode (computer interface) , meteorology , atmospheric sciences , computer science , geology , geography , operating system
Two sets of CFSv2 retrospective forecast experiments are performed to check the model's fidelity for operational forecast usage for the prediction of Indian summer monsoon rainfall (ISMR). The first experiment (Exp1) is identical to the present operational mode of the model. The second experiment (Exp2) includes major changes in terms of the different cumulus parameterization scheme, modified cloud microphysics scheme and the variable critical relative humidity. These changes have already shown enhancement in the seasonal viability of the model in the free‐run mode. This study has carried out exclusive hindcast experiments by combining the above mentioned major changes. There is a marked improvement in the spatial distribution of the precipitation and the amplitude of the annual cycle of ISMR. The underestimation of the peak of the annual cycle of ISMR in Exp1 is enhanced by 23% in Exp2. Because of better simulations of clouds and tropospheric temperature gradient, the point of maximum precipitation has migrated northwards from equator (Exp1) to 20°N (Exp2). These improvements also impress upon all the other aspect of the ocean–atmosphere coupled interaction, namely planetary‐scale Hadley circulation, air–sea interactions and most of the facets of monsoon teleconnections. The skill of extended Indian monsoon rainfall region (65°–95°E, 5°–35 N) has increased from 0.50 in Exp1 to 0.67 in Exp2 and the same holds true for other regions as well. The skill of Niño3.4 index enhances from 0.58 in Exp1 to 0.67 in Exp2. The dynamical wind shear based monsoon performance indices also show the surge in the skill score. The significant improvement of seasonal skill scores across all the variables clearly shows the dynamical consistency and at the same time establishes the superiority of the Exp2 for seasonal forecast. This work will add new dimension to develop a new genre of monsoon forecasting model.