scholarly journals Intrinsic precursors and timescale of the tropical Indian Ocean Dipole: insights from partially decoupled numerical experiment

2017 ◽  
Vol 51 (4) ◽  
pp. 1311-1332 ◽  
Author(s):  
Julien Crétat ◽  
Pascal Terray ◽  
Sébastien Masson ◽  
K. P. Sooraj
Keyword(s):  
Indian Ocean ◽  
Numerical Experiment ◽  
Indian Ocean Dipole ◽  
Tropical Indian Ocean

scholarly journals Two Independent Triggers for the Indian Ocean Dipole/Zonal Mode in a Coupled GCM

2005 ◽  
Vol 18 (17) ◽  
pp. 3428-3449 ◽  
Author(s):  
Albert S. Fischer ◽  
Pascal Terray ◽  
Eric Guilyardi ◽  
Silvio Gualdi ◽  
Pascale Delecluse
Keyword(s):  
Indian Ocean ◽  
El Niño ◽  
Indian Ocean Dipole ◽  
El Nino ◽  
Tropical Indian Ocean ◽  
Sea Surface ◽  
Dynamical Response ◽  
Thermocline Depth ◽  
Second Phase ◽  
The Indian Ocean

Abstract The question of whether and how tropical Indian Ocean dipole or zonal mode (IOZM) interannual variability is independent of El Niño–Southern Oscillation (ENSO) variability in the Pacific is addressed in a comparison of twin 200-yr runs of a coupled climate model. The first is a reference simulation, and the second has ENSO-scale variability suppressed with a constraint on the tropical Pacific wind stress. The IOZM can exist in the model without ENSO, and the composite evolution of the main anomalies in the Indian Ocean in the two simulations is virtually identical. Its growth depends on a positive feedback between anomalous equatorial easterly winds, upwelling equatorial and coastal Kelvin waves reducing the thermocline depth and sea surface temperature off the coast of Sumatra, and the atmospheric dynamical response to the subsequently reduced convection. Two IOZM triggers in the boreal spring are found. The first is an anomalous Hadley circulation over the eastern tropical Indian Ocean and Maritime Continent, with an early northward penetration of the Southern Hemisphere southeasterly trades. This situation grows out of cooler sea surface temperatures in the southeastern tropical Indian Ocean left behind by a reinforcement of the late austral summer winds. The second trigger is a consequence of a zonal shift in the center of convection associated with a developing El Niño, a Walker cell anomaly. The first trigger is the only one present in the constrained simulation and is similar to the evolution of anomalies in 1994, when the IOZM occurred in the absence of a Pacific El Niño state. The presence of these two triggers—the first independent of ENSO and the second phase locking the IOZM to El Niño—allows an understanding of both the existence of IOZM events when Pacific conditions are neutral and the significant correlation between the IOZM and El Niño.

Inter-basin and Multi-time Scale Interactions in generating the 2019 Extreme Indian Ocean Dipole

2021 ◽  
pp. 1-39
Author(s):  
Lei Zhang ◽  
Weiqing Han ◽  
Zeng-Zhen Hu
Keyword(s):  
Indian Ocean ◽  
Indian Ocean Dipole ◽  
Intraseasonal Oscillation ◽  
Tropical Indian Ocean ◽  
Forecast Model ◽  
Tropical Pacific ◽  
Boreal Summer ◽  
Indian Ocean Dipole Event ◽  
Easterly Wind ◽  
Western Tropical Pacific

AbstractAn unprecedented extreme positive Indian Ocean Dipole event (pIOD) occurred in 2019, which has caused widespread disastrous impacts on countries bordering the Indian Ocean, including the East African floods and vast bushfires in Australia. Here we investigate the causes for the 2019 pIOD by analyzing multiple observational datasets and performing numerical model experiments. We find that the 2019 pIOD is triggered in May by easterly wind bursts over the tropical Indian Ocean associated with the dry phase of the boreal summer intraseasonal oscillation, and sustained by the local atmosphere-ocean interaction thereafter. During September-November, warm sea surface temperature anomalies (SSTA) in the central-western tropical Pacific further enhance the Indian Ocean’s easterly winds, bringing the pIOD to an extreme magnitude. The central-western tropical Pacific warm SSTA is strengthened by two consecutive Madden Julian Oscillation (MJO) events that originate from the tropical Indian Ocean. Our results highlight the important roles of cross-basin and cross-timescale interactions in generating extreme IOD events. The lack of accurate representation of these interactions may be the root for a short lead time in predicting this extreme pIOD with a state-of-the-art climate forecast model.

scholarly journals El Niño-Southern Oscillation and Indian Ocean Dipole Modes: Their Effects on South American Rainfall during Austral Spring

Atmosphere ◽  
2021 ◽  
Vol 12 (11) ◽  
pp. 1437
Author(s):  
Mary T. Kayano ◽  
Wilmar L. Cerón ◽  
Rita V. Andreoli ◽  
Rodrigo A. F. Souza ◽  
Itamara P. Souza ◽  
...  
Keyword(s):  
Indian Ocean ◽  
El Niño ◽  
Indian Ocean Dipole ◽  
El Nino ◽  
Southern Oscillation ◽  
Tropical Indian Ocean ◽  
El Niño Southern Oscillation ◽  
El Nino Southern Oscillation ◽  
Austral Spring ◽  
Precipitation Anomalies

This paper examines the effects of the tropical Pacific Ocean (TPO) and Indian Ocean Dipole (IOD) modes in the interannual variations of austral spring rainfall over South America (SA). The TPO mode refers to the El Niño-Southern Oscillation (ENSO). The isolated effects between IOD and TPO were estimated, events were chosen from the residual TPO (R-TPO) or residual IOD (R-IOD), and the IOD (TPO) effects for the R-TPO (R-IOD) composites were removed from the variables. One relevant result was the nonlinear precipitation response to R-TPO and R-IOD. This feature was accentuated for the R-IOD composites. The positive R-IOD composite showed significant negative precipitation anomalies along equatorial SA east of 55° W and in subtropical western SA, and showed positive anomalies in northwestern SA and central Brazil. The negative R-IOD composite indicated significant positive precipitation anomalies in northwestern Amazon, central–eastern Brazil north of 20° S, and western subtropical SA, and negative anomalies were found in western SA south of 30° S. This nonlinearity was likely due to the distinct atmospheric circulation responses to the anomalous heating sources located in longitudinally distinct regions: the western tropical Indian Ocean and areas neighboring Indonesia. The results obtained in this study might be relevant for climate monitoring and modeling studies.

Atmospheric energetics over the tropical Indian Ocean during Indian Ocean dipole events

2018 ◽  
Vol 52 (9-10) ◽  
pp. 6243-6256 ◽  
Author(s):  
Yuehong Wang ◽  
Jianping Li ◽  
Yazhou Zhang ◽  
Qiuyun Wang ◽  
Jianhuang Qin
Keyword(s):  
Indian Ocean ◽  
Indian Ocean Dipole ◽  
Tropical Indian Ocean ◽  
Atmospheric Energetics

scholarly journals Realism of the Indian Ocean Dipole in CMIP5 Models: The Implications for Climate Projections

2013 ◽  
Vol 26 (17) ◽  
pp. 6649-6659 ◽  
Author(s):  
Evan Weller ◽  
Wenju Cai
Keyword(s):  
Indian Ocean ◽  
Indian Ocean Dipole ◽  
Climate Models ◽  
Tropical Indian Ocean ◽  
Cmip5 Models ◽  
Climate Projections ◽  
Coupled Models ◽  
Austral Spring ◽  
Wide Range ◽  
The Indian Ocean

Abstract An assessment of how well climate models simulate the Indian Ocean dipole (IOD) is undertaken using 20 coupled models that have partaken in phase 5 of the Coupled Model Intercomparison Project (CMIP5). Compared with models in phase 3 (CMIP3), no substantial improvement is evident in the simulation of the IOD pattern and/or amplitude during austral spring [September–November (SON)]. The majority of models in CMIP5 generate a larger variance of sea surface temperature (SST) in the Sumatra–Java upwelling region and an IOD amplitude that is far greater than is observed. Although the relationship between precipitation and tropical Indian Ocean SSTs is well simulated, future projections of SON rainfall changes over IOD-influenced regions are intrinsically linked to the IOD amplitude and its rainfall teleconnection in the model present-day climate. The diversity of the simulated IOD amplitudes in models in CMIP5 (and CMIP3), which tend to be overly large, results in a wide range of future modeled SON rainfall trends over IOD-influenced regions. The results herein highlight the importance of realistically simulating the present-day IOD properties and suggest that caution should be exercised in interpreting climate projections in the IOD-affected regions.

scholarly journals Satellite and Argo Observed Surface Salinity Variations in the Tropical Indian Ocean and Their Association with the Indian Ocean Dipole Mode

2015 ◽  
Vol 28 (2) ◽  
pp. 695-713 ◽  
Author(s):  
Yan Du ◽  
Yuhong Zhang
Keyword(s):  
Indian Ocean ◽  
Ocean Circulation ◽  
Indian Ocean Dipole ◽  
Coastal Upwelling ◽  
Tropical Indian Ocean ◽  
Sea Surface Salinity ◽  
The South ◽  
Surface Salinity ◽  
Indian Ocean Dipole Mode ◽  
The Indian Ocean

Abstract This study investigates sea surface salinity (SSS) variations in the tropical Indian Ocean (IO) using the Aquarius/Satelite de Aplicaciones Cientificas-D (SAC-D) and the Soil Moisture and Ocean Salinity (SMOS) satellite data and the Argo observations during July 2010–July 2014. Compared to the Argo observations, the satellite datasets generally provide SSS maps with higher space–time resolution, particularly in the regions where Argo floats are sparse. Both Aquarius and SMOS well captured the SSS variations associated with the Indian Ocean dipole (IOD) mode. Significant SSS changes occurred in the central equatorial IO, along the Java–Sumatra coast, and south of the equatorial IO, due to ocean circulation variations. During the negative IOD events in 2010, 2013, and 2014, westerly wind anomalies strengthened along the equator, weakening coastal upwelling off Java and Sumatra and decreasing SSS. South of the equatorial IO, an anomalous cyclonic gyre changed the tropical circulation, which favored the eastward high-salinity tongue along the equator and the westward low-saline tongue in the south. An upwelling Rossby wave favored the increase of SSS farther to the south. During the positive IOD events in 2011 and 2012, the above-mentioned processes reversed, although the decrease of SSS was weaker in magnitude.

The Indian Ocean Dipole: A Monopole in SST

2014 ◽  
Vol 28 (1) ◽  
pp. 3-19 ◽  
Author(s):  
Yongjing Zhao ◽  
Sumant Nigam
Keyword(s):  
Indian Ocean ◽  
Indian Ocean Dipole ◽  
A Priori ◽  
Heat Content ◽  
Tropical Indian Ocean ◽  
Spatiotemporal Analysis ◽  
Upper Ocean Heat Content ◽  
Sst Variability ◽  
Dipole Structure ◽  
The Indian Ocean

Abstract The claim for a zonal-dipole structure in interannual variations of the tropical Indian Ocean (IO) SSTs—the Indian Ocean dipole (IOD)—is reexamined after accounting for El Niño–Southern Oscillation’s (ENSO) influence. The authors seek an a priori accounting of ENSO’s seasonally stratified influence on IO SSTs and evaluate the basis of the related dipole mode index, instead of seeking a posteriori adjustments to this index, as common. Scant observational evidence is found for zonal-dipole SST variations after removal of ENSO’s influence from IO SSTs: The IOD poles are essentially uncorrelated in the ENSO-filtered SSTs in both recent (1958–98) and century-long (1900–2007) periods, leading to the breakdown of zonal-dipole structure in surface temperature variability; this finding does not depend on the subtleties in estimation of ENSO’s influence. Deconstruction of the fall 1994 and 1997 SST anomalies led to their reclassification, with a weak IOD in 1994 and none in 1997. Regressions of the eastern IOD pole on upper-ocean heat content, however, do exhibit a zonal-dipole structure but with the western pole in the central-equatorial IO, suggesting that internally generated basin variability can have zonal-dipole structure at the subsurface. The IO SST variability was analyzed using the extended-EOF technique, after removing the influence of Pacific SSTs; the technique targets spatial and temporal recurrence and extracts modes (rather than patterns) of variability. This spatiotemporal analysis also does not support the existence of zonal-dipole variability at the surface. However, the analysis did yield a dipole-like structure in the meridional direction in boreal fall/winter, when it resembles the subtropical IOD pattern (but not the evolution time scale).

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