Tuyển tập các báo cáo nghiên cứu khoa học trên tạp chí khoa học vật lý quốc tế đề tài: THE COVARIABILITY BETWEEN ANOMALOUS NORTHEAST MONSOON RAINFALL IN MALAYSIA AND SEA SURFACE TEMPERATURE IN INDIAN-PACIFIC SECTOR: A SINGULAR VALUE DECOMPOSITION ANALYSIS APPROACH | Journal of Physical Science Vol. 17 2 101-115 2006 101 THE COVARIABILITY BETWEEN ANOMALOUS NORTHEAST MONSOON RAINFALL IN MALAYSIA AND SEA SURFACE TEMPERATURE IN INDIAN-PACIFIC SECTOR A SINGULAR VALUE DECOMPOSITION ANALYSIS APPROACH Liew Juneng and Fredolin T. Tangang Marine Science Program School of Environmental and Natural Resources Science Faculty of Science and Technology Universiti Kebangsaan Malaysia 43000 Bangi Selangor Malaysia Corresponding author tangang@ Abstract The singular value decomposition technique SVD is used to analyze the covariability between anomalous northeast monsoon NEM rainfall in Malaysia and the large-scale anomalous sea surface temperature SST in Indian Ocean Pacific Ocean and seas surrounding the Maritime Continent. The SVD analysis reveals two significant coupled modes of covariability with the first dominant mode explaining 75 while the second coupled mode explaining 15 of the total covariance. The first coupled mode highlights the covariability between anomalous NEM rainfall in East Malaysia and anomalous SST associated with the biennial oscillation type BO-type of the El Nino-Southern Oscillation ENSO . The second coupled mode highlights the covariability between anomalous NEM rainfall in West Malaysia and anomalous SST associated with the low frequency type LF-type of ENSO. Overall the BO-type and LF-type of ENSO define two distinct regimes of different behaviour of anomalous NEM rainfall in Malaysia East Malaysia and West Malaysia regions. During the BO-type of ENSO East Malaysia region is mostly affected while during the LF-type of ENSO the impacts are mostly confined in West Malaysia region. Keywords singular value decomposition covariability northeast monsoon rainfall sea surface temperature 1. INTRODUCTION The singular value decomposition SVD is a commonly used technique in meteorological and oceanographic data analysis 1-4 . It can be thought of as a generalization to the square symmetric matrix .
