Premium
Improved intraseasonal variability in the initialization of SINTEX‐F2 using a spectral cumulus parameterization
Author(s) -
Baba Yuya
Publication year - 2021
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.7220
Subject(s) - initialization , madden–julian oscillation , scheme (mathematics) , oscillation (cell signaling) , convection , climatology , environmental science , meteorology , sea surface temperature , mathematics , computer science , physics , geology , mathematical analysis , biology , genetics , programming language
A newly developed spectral cumulus parameterization (spectral scheme) was implemented in the Scale Interaction Experiment‐Frontier version 2 (SINTEX‐F2) seasonal prediction system to improve intraseasonal variability in the system initialization. A simple sea surface temperature (SST) nudging scheme using different SST data and restoring times was used to initialize the system, and the initialized atmosphere obtained from both the original convection scheme (Tiedtke scheme) and the new spectral scheme was evaluated against observational data. It was found that that climatology and variability simulated by the spectral scheme were comparable to those simulated by the original scheme. In addition, the intraseasonal variability represented by the Madden–Julian oscillation (MJO) was better simulated by the spectral scheme than the original scheme. An analysis of the structure of the organized convection revealed the successful simulation of low‐level shallow convection before the peak of the organized convection by the spectral scheme when compared with the observation, a result lacking in the original scheme simulation. In addition to the positive qualitative results, a statistical and quantitative analysis showed that the spectral scheme captured the MJO‐related variability better than the original scheme. In conclusion, the prediction system using the spectral scheme is expected to improve seasonal predictions for seasonal variability whose evolution is affected by intraseasonal variations.