Open AccessThe Intraseasonal Variability of the Indian Summer Monsoon Using TMI Sea Surface Temperatures and ECMWF Reanalysis
Author(s) -
Nicholas P. Klingaman,
Hilary Weller,
Julia Slingo,
Peter Inness
Publication year - 2008
Publication title -
journal of climate
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.315
H-Index - 287
eISSN - 1520-0442
pISSN - 0894-8755
DOI - 10.1175/2007jcli1850.1
Subject(s) - climatology , empirical orthogonal functions , outgoing longwave radiation , environmental science , predictability , monsoon , sea surface temperature , climate forecast system , madden–julian oscillation , la niña , atmospheric sciences , meteorology , el niño southern oscillation , precipitation , geology , geography , convection , mathematics , statistics
The northward-propagating intraseasonal (30–40 day) oscillation (NPISO) between active and break monsoon phases exerts a critical control on summer-season rainfall totals over India. Advances in diagnosing these events and comprehending the physical mechanisms behind them may hold the potential for improving their predictability. While previous studies have attempted to extract active and break events from reanalysis data to elucidate a composite life cycle, those studies have relied on first isolating the intraseasonal variability in the record (e.g., through bandpass filtering, removing harmonics, or empirical orthogonal function analysis). Additionally, the underlying physical processes that previous studies have proposed have varied, both among themselves and with studies using general circulation models. A simple index is defined for diagnosing NPISO events in observations and reanalysis, based on lag correlations between outgoing longwave radiation (OLR) over India and over the equatorial Indian Ocean. This index is the first to use unfiltered OLR observations and so does not specifically isolate intraseasonal periods. A composite NPISO life cycle based on this index is similar to previous composites in OLR and surface winds, demonstrating that the dominance of the intraseasonal variability in the monsoon climate system eliminates the need for more complex methods (e.g., time filtering or EOF analysis) to identify the NPISO. This study is also among the first to examine the NPISO using a long-period record of high-resolution sea surface temperatures (SSTs) from the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager. Application of this index to those SSTs demonstrates that SST anomalies exist in near quadrature with convection, as suggested by recent coupled model studies. Analysis of the phase relationships between atmospheric fields and SSTs indicates that the atmosphere likely forced the SST anomalies. The results of this lag-correlation analysis suggest that the oscillation serves as its own most reliable—and perhaps only—predictor, and that signals preceding an NPISO event appear first over the Indian subcontinent, not the equatorial Indian Ocean where the events originate.