Improvements in the representation of the Indian summer monsoon in the NCEP climate forecast system version 2
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Abstract
A new triggering mechanism for deep convection based on the heated condensation framework (HCF) is implemented into the National Centers for Environmental Prediction climate forecast system version 2 (CFSv2). The new trigger is added as an additional criterion in the simplified Arakawa–Schubert scheme for deep convection. Seasonal forecasts are performed to evaluate the influence of the new triggering mechanism in the representation of the Indian summer monsoon in the CFSv2. The HCF trigger improves the seasonal representation of precipitation over the Indian subcontinent. The new triggering mechanism leads to a significant, albeit relatively small, improvement in the bias of seasonal precipitation totals. In addition, the new trigger improves the representation of the seasonal precipitation cycle including the monsoon onset, and the probability distribution of precipitation intensities. The mechanism whereby the HCF improves convection over India seems to be related not only to a better representation of the background state of atmospheric convection but also to an increase in the frequency in which SAS is triggered. As a result, there was an increase in convective precipitation over India favored by the availability of moist convective instability. The increase in precipitation intensity leads to a reduction in the dry bias.
Keywords
Trigger function CFSv2 Indian summer monsoon Seasonal predictability ConvectionNotes
Acknowledgments
We thank the support from the National Monsoon Mission, Ministry of Earth Sciences, Government of India. We also thank the support from NSF (0830068), NOAA (NA09OAR4310058) and NASA (NNX09AN50G). We thank the two anonymous reviewers for their suggestions for the improvement of this manuscript. In addition, we thank the European Centre for Medium-Range Weather Forecasts (ECMWF) for making available the ERA-interim reanalysis and the National Aeronautics and Space Administration (NASA) for making available the MERRA reanalysis and the TRMM analysis. This work used the Extreme Science and Engineering Discovery Environment (XSEDE), which is supported by National Science Foundation grant number ACI-1053575.
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