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H. Annamalai, H. Okajima, and M. Watanabe

1. Introduction For short-term global climate prediction, the sea surface temperature (SST) anomalies associated with the El Niño–Southern Oscillation (ENSO) phenomenon are recognized as the most dominant forcing factor (e.g., Wallace et al. 1998 ; Trenberth et al. 1998 ; Lau and Nath 2000 ; Su et al. 2001 ; Annamalai and Liu 2005 ). Of special interest here is the role of El Niño on the Pacific–North American (PNA) pattern defined by Wallace and Gutzler (1981) . From regression analysis

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Tommy G. Jensen

. separate the remote influence of ENSO and positive IOD events on the Southern Hemishere winter storm tracks and the associated reduced rainfall over southern Australia and New Zealand. Annamalai et al. are using ensemble calculations from two AGCMs to show that during El Niño the SSTA in the southwestern Indian Ocean opposes the effects of SSTA in the tropical Pacific over the Pacific–North American region. The next four papers address the heat flux and heat transport in the tropical Indian Ocean. In

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Tomoki Tozuka, Jing-Jia Luo, Sebastien Masson, and Toshio Yamagata

1. Introduction The Indian Ocean dipole (IOD) is an air–sea coupled phenomenon associated with a positive sea surface temperature anomaly (SSTA) to the west and a negative SSTA to the east ( Saji et al. 1999 ; Webster et al. 1999 ). It has turned out that the IOD has a large impact on the climate of both the surrounding and remote regions such as east Asia, Europe, and South America ( Guan and Yamagata 2003 ; Saji and Yamagata 2003 ; Yamagata et al. 2004 ). Thus, understanding, as well as

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Karumuri Ashok, Hisashi Nakamura, and Toshio Yamagata

portion of the south Indian Ocean, a midlatitude Atlantic region off South America, and, importantly, another maritime region off southeastern Australia including Tasmania ( Fig. 5a ). The corresponding partial correlation with 850-hPa is distributed in a similar manner ( Fig. 5c ), but the positive correlation is weaker and less significant to the south of Australia. Figure 6 presents partial correlations between IODMI and zonal winds at the 300-hPa ( Fig. 6a ) and 850-hPa ( Fig. 6b ) levels. As

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Gary Meyers, Peter McIntosh, Lidia Pigot, and Mike Pook

such a long period of time is also likely to be useful in paleoclimate research. 2. ENSO and IOD dynamics: A basis for classifying the years ENSO is a mode of climate variability with strong coupling between the ocean and the atmosphere in the Pacific equatorial cold tongue, a spatial relative minimum of SST that extends along the Pacific equator from the coast of South America to the date line. The cold tongue is maintained by upwelling of cooler water from the thermocline caused by the divergence

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Hae-Kyung Lee Drbohlav, Silvio Gualdi, and Antonio Navarra

, North and South America, and South Africa. Therefore, an understanding of the IODM is critical for the prediction of the Indian summer monsoon system and possibly other regions on a global scale. As the role of the IODM in climate variability has gained attention in recent years, many efforts have been made to explain its formation. Gualdi et al. (2003) analyzed the IODM in a coupled model, and suggested a mechanism for the formation of the IODM in El Niño years. During the developing phase of an

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Annalisa Cherchi, Silvio Gualdi, Swadhin Behera, Jing Jia Luo, Sebastien Masson, Toshio Yamagata, and Antonio Navarra

model (OGCM) with the ORCA2 configuration ( Madec et al. 1998 ). The grid has two poles, one in the Eurasian continent and the other in the North American continent, to avoid the singularity over the North Pole. The horizontal resolution is about 2° × 2° with an increase of the meridional resolution to 0.5° around the equator. In the vertical there are 31 levels with 10 in the upper 100 m. The physics of the model includes a free surface configuration ( Roullet and Madec 2000 ). Vertical eddy

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