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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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Clémentde Boyer Montégut, Jérôme Vialard, S. S. C. Shenoi, D. Shankar, Fabien Durand, Christian Ethé, and Gurvan Madec

heat loss due to lower atmospheric forcing than in the eastern AS. Solar heat flux is smaller because of high cloud cover (about 80% in August) but latent heat flux is also weaker due to lower winds over the bay. The tendency of subsurface vertical processes is negative on the basin scale due to weak upwelling along the east coast of India ( Shetye et al. 1991 ; Shenoi et al. 2002 ), as well as due to the Sri Lanka cold dome ( Vinayachandran and Yamagata 1998 ). The contribution of the vertical

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

; Rosati and Miyakoda 1988 ) with a longitudinal resolution of 0.5°, and a meridional resolution varying from a minimum of 1/3° between 10°S and 10°N to a maximum 0.5° at the northern boundary. The 31 vertical levels are unevenly spaced, with the first 14 levels confined to the upper 450 m. The model is initialized with the ocean at rest, and the climatology of the temperature and salinity taken from winter WOD98. The cloud cover used in the MOM is derived from the climatology cloud cover of the

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Bohua Huang and J. Shukla

increased solar flux and reduced evaporative heat loss at the sea surface due to the reductions of both cloud cover and surface wind speeds during an El Niño event (e.g., Klein et al. 1999 ; Venzke et al. 2000 ). Xie et al. (2002) and Huang and Kinter (2002) also found that the surface warming in the southwestern Indian Ocean at the end of an El Niño year can be caused by an anomalous deepening of the thermocline associated with westward propagating Rossby waves. Before reaching this basinwide

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Jean Philippe Duvel and Jérôme Vialard

perturbations in the Indian Ocean. This shallow thermocline makes cold water readily available to cool the surface by vertical mixing or local upwelling; but, on the other hand, it also limits strongly the depth of the mixed layer, making it more responsive to surface forcing. This surface forcing perturbation itself is due to various physical processes that may have different phasing relative to the maximum convective activity. These physical processes are mainly the screening of the solar heat flux by the

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

Atmosphere Sea Ice Soil (OASIS 2.4; Valcke et al. 2000 ) coupling software package. No measures for flux adjustments are taken in the model. For the AGCM, a semi-Lagrangian transport method ( Rasch and Williamson 1990 ) is used for the advection of cloud water and water vapor, while the parameterization of Tiedtke (1989) is used to represent convection and that of Morcrette (1991) is used for radiation. The horizontal resolution of the OGCM is 2° × 2° cosine (latitude) with an increased meridional

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

Meyers 2003 ). These studies also show that as with ENSO, the depth of the thermocline is largely forced by remote winds, from both the Indian and the Pacific Oceans ( Wijffels and Meyers 2004 ). Both remote forcing and the local wind are factors in the generation of the SST of the eastern pole ( Feng and Meyers 2003 ), so that cool SST anomalies (i.e., positive IOD) develop when the easterly wind is favorable for upwelling along the coast of Java and the thermocline is shallow due to remote forcing

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

scheme for the advection of water vapor and cloud water ( Rasch and Williamson 1990 ). The parameterization of convection is based on the mass flux concept ( Tiedtke 1989 ) modified following Nordeng (1994) . The Morcrette (1991) radiation scheme is used with the insertion of greenhouse gases and a revised parameterization for water vapor and the optical properties of clouds. The vertical turbulent transfer of momentum, mass, water vapor, and cloud water is based on the similarity theory of Monin

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Lisan Yu, Xiangze Jin, and Robert A. Weller

and operational applications. In light of the divergence in existing heat flux estimates for the Indian Ocean, there is a need to perform a general evaluation to assess the degree of divergence–consistency. Six heat flux products are examined in the study, including the newly developed Objectively Analyzed Air–Sea Heat Fluxes (OAFlux) product ( Yu and Weller 2007 ), the net shortwave and longwave radiation results from the International Satellite Cloud Climatology Project (ISCCP; Zhang et al

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Rui-Jin Hu and J. Stuart Godfrey

Satellite Cloud Climatology Project (ISCCP: e.g., Schiffer and Rossow 1983 ) dataset for longwave and shortwave radiation, plus their own, primarily satellite-based estimates of latent and sensible heat loss ( Yu et al. 2004 ). Use of satellite data avoids the data gaps in other products where no merchant ship observations are available. For reasons discussed below another AMNHF product was generated from (2) , using the observed SST from COADS ( Fig. 3b ). It is certainly not a reliable product for

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