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5 - Indian Ocean Variability and Interactions
- Edited by Carlos R. Mechoso, University of California, Los Angeles
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- Book:
- Interacting Climates of Ocean Basins
- Published online:
- 13 January 2021
- Print publication:
- 26 November 2020, pp 153-185
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Summary
This chapter revisits the variability of the Indian Ocean on interannual to multidecadal timescales. A special focus is given to teleconnections from and to the Indian Ocean and to what extend they modify the Indian Ocean as well as the variability in other oceans. Decadal changes of interannual teleconnections are briefly discussed. Both atmospheric and oceanic pathways for the teleconnections are considered. While the main mode of variability in the Indian Ocean, the basin mode, is mainly externally forced by a teleconnection from ENSO, the second mode of Indian Ocean variability, the Indian Ocean Dipole, is to a large extent an unforced mode of variability. The Indian Ocean can modulate Pacific and, in particular, ENSO variability through oceanic (Indian Ocean Throughflow) and atmospheric (Walker circulation) bridges. The Atlantic Ocean has a modest impact on Indian Ocean interannual variability, mainly in boreal summer. The Indian Ocean is directly connected to the Atlantic Ocean through the Agulhas Current system. At decadal timescales, both Pacific Decadal Variability (Pacific Decadal Oscillation, Interdecadal Pacific Oscillation) and the Atlantic Multidecadal Variability impact the Indian Ocean. While Pacific Decadal Variability influences the Indian Ocean throughout the year, the Atlantic Multidecadal Variability influence is seasonally dependent and strongest in boreal spring season and may have contributed to an accelerated Arabian Sea warming in the recent decades. The Pacific interannual teleconnection to the Indian Ocean shows substantial decadal variations, but further research in this area is necessary and encouraged.
Chapter 14 - On the predictability of flow-regime properties on interannual to interdecadal timescales
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- By Franco Molteni, Abdus Salam International Centre for Theoretical Physics, Trieste, Fred Kucharski, Abdus Salam International Centre for Theoretical Physics, Trieste, Susanna Corti, Institute of Atmospheric Sciences and Climate ISAC-CNR, Bologna
- Edited by Tim Palmer, Renate Hagedorn
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- Book:
- Predictability of Weather and Climate
- Published online:
- 03 December 2009
- Print publication:
- 27 July 2006, pp 365-390
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Summary
Introduction
Atmospheric flow regimes are usually defined as large-scale circulation patterns associated with statistical equilibria in phase space, in which the dynamical tendencies of the large-scale flow are balanced by tendencies due to non-linear interactions of high-frequency transients. The existence of states with such properties can be verified in a rigorous way in numerical simulations with simplified numerical models (as in the pioneering study of Reinhold and Pierrehumbert, 1982, or in the experiments by Vautard and Legras, 1988). By contrast, the existence of flow regimes in the real atmosphere has been strongly debated. The detection of regimes in the observational record of the upper-air field is indeed a complex task, which has been approached by a number of research groups with a variety of sophisticated statistical methods (see Section 14.3).
Although the regime classifications provided by the different observational studies were not identical, a ‘core’ number of regimes were consistently detected in most studies devoted to a specific spatial domain. For example, the three northern-hemisphere clusters found by Cheng and Wallace (1993) were also identified by Kimoto and Ghil (1993a), Corti et al. (1999) and Smyth et al. (1999). However, consistency does not necessarily imply statistical significance, and one may question whether the level of confidence attached to these regime classifications is sufficiently high.
The search for regimes in the real atmosphere is also made complex by the fact that, unlike in simple dynamical models, the sources of energy and momentum at the lower boundary display variations on seasonal, interannual and interdecadal timescales.