Subsurface influence on SST in the tropical Indian Ocean: structure and interannual variability

2005 ◽  
Vol 39 (1-2) ◽  
pp. 103-135 ◽  
Author(s):  
Suryachandra A. Rao ◽  
Swadhin K. Behera
Keyword(s):  
Indian Ocean ◽  
Interannual Variability ◽  
Tropical Indian Ocean

Interannual variability of the Tropical Indian Ocean mixed layer depth

2012 ◽  
Vol 40 (3-4) ◽  
pp. 743-759 ◽  
Author(s):  
M. G. Keerthi ◽  
M. Lengaigne ◽  
J. Vialard ◽  
C. de Boyer Montégut ◽  
P. M. Muraleedharan
Keyword(s):  
Indian Ocean ◽  
Interannual Variability ◽  
Mixed Layer ◽  
Mixed Layer Depth ◽  
Tropical Indian Ocean ◽  
Ocean Mixed Layer ◽  
Layer Depth ◽  
Ocean Mixed Layer Depth

A Model-Based Assessment and Design of a Tropical Indian Ocean Mooring Array

2007 ◽  
Vol 20 (13) ◽  
pp. 3269-3283 ◽  
Author(s):  
Peter R. Oke ◽  
Andreas Schiller
Keyword(s):  
Indian Ocean ◽  
Interannual Variability ◽  
Time Scales ◽  
Ocean Circulation ◽  
Mixed Layer Depth ◽  
Intraseasonal Variability ◽  
Circulation Model ◽  
Tropical Indian Ocean ◽  
Empirical Orthogonal Functions ◽  
Analysis System

Abstract A series of observing system simulation experiments (OSSEs) are performed for the tropical Indian Ocean (±15° from the equator) using a simple analysis system. The analysis system projects an array of observations onto the dominant empirical orthogonal functions (EOFs) derived from an intermediate-resolution (2° × 0.5°) ocean circulation model. This system produces maps of the depth of the 20°C isotherm (D20), representing interannual variability, and the high-pass-filtered mixed layer depth (MLD), representing intraseasonal variability. The OSSEs are designed to assess the suitability of the proposed Indian Ocean surface mooring array for resolving intraseasonal to interannual variability. While the proposed array does a reasonable job of resolving the interannual time scales, it may not adequately resolve the intraseasonal time scales. A procedure is developed to rank the importance of observation locations by determining the observation array that best projects onto the EOFs used in the analysis system. OSSEs using an optimal array clearly outperform the OSSEs using the proposed array. The configuration of the optimal array is sensitive to the number of EOFs considered. The optimal array is also different for D20 and MLD, and depends on whether fixed observations are included that represent an idealized Argo array. Therefore, a relative frequency map of observation locations identified in 24 different OSSEs is compiled and a single, albeit less optimal, array that is referred to as a consolidated array is objectively determined. The consolidated array reflects the general features of the individual optimal arrays derived from all OSSEs. It is found that, in general, observations south of 8°S and off of the Indonesian coast are most important for resolving the interannual variability, while observations a few degrees south of the equator, and west of 75°E, and a few degrees north of the equator, and east of 75°E, are important for resolving the intraseasonal variability. In a series of OSSEs, the consolidated array is shown to outperform the proposed array for all configurations of the analysis system for both D20 and MLD.

Mechanisms for the Interannual Variability in the Tropical Indian Ocean. Part II: Regional Processes

2007 ◽  
Vol 20 (13) ◽  
pp. 2937-2960 ◽  
Author(s):  
Bohua Huang ◽  
J. Shukla
Keyword(s):  
Indian Ocean ◽  
Interannual Variability ◽  
El Niño ◽  
El Nino ◽  
Tropical Indian Ocean ◽  
Global Ocean ◽  
Trade Wind ◽  
Tropical Ocean ◽  
The Indian Ocean ◽  
Sst Anomalies

Abstract To understand the mechanisms of the interannual variability in the tropical Indian Ocean, two long-term simulations are conducted using a coupled ocean–atmosphere GCM—one with active air–sea coupling over the global ocean and the other with regional coupling restricted within the Indian Ocean to the north of 30°S while the climatological monthly sea surface temperatures (SSTs) are prescribed in the uncoupled oceans to drive the atmospheric circulation. The major spatial patterns of the observed upper-ocean heat content and SST anomalies can be reproduced realistically by both simulations, suggesting that they are determined by intrinsic coupled processes within the Indian Ocean. In both simulations, the interannual variability in the Indian Ocean is dominated by a tropical mode and a subtropical mode. The tropical mode is characterized by a coupled feedback among thermocline depth, zonal SST gradient, and wind anomalies over the equatorial and southern tropical Indian Ocean, which is strongest in boreal fall and winter. The tropical mode simulated by the global coupled model reproduces the main observational features, including a seasonal connection to the model El Niño–Southern Oscillation (ENSO). The ENSO influence, however, is weaker than that in a set of ensemble simulations described in Part I of this study, where the observed SST anomalies for 1950–98 are prescribed outside the Indian Ocean. Combining with the results from Part I of this study, it is concluded that ENSO can modulate the temporal variability of the tropical mode through atmospheric teleconnection. Its influence depends on the ENSO strength and duration. The stronger and more persistent El Niño events in the observations extend the life span of the anomalous events in the tropical Indian Ocean significantly. In the regional coupled simulation, the tropical mode is still active, but its dominant period is shifted away from that of ENSO. In the absence of ENSO forcing, the tropical mode is mainly stimulated by an anomalous atmospheric direct thermal cell forced by the fluctuations of the northwestern Pacific monsoon. The subtropical mode is characterized by an east–west dipole pattern of the SST anomalies in the southern subtropical Indian Ocean, which is strongest in austral fall. The SST anomalies are initially forced by surface heat flux anomalies caused by the anomalous southeast trade wind in the subtropical ocean during austral summer. The trade wind anomalies are in turn associated with extratropical variations from the southern annular mode. A thermodynamic air–sea feedback strengthens these subtropical anomalies quickly in austral fall and extends their remnants into the tropical ocean in austral winter. In the simulations, this subtropical variability is independent of ENSO.

scholarly journals Internal Variability of Indian Ocean SST

2005 ◽  
Vol 18 (18) ◽  
pp. 3726-3738 ◽  
Author(s):  
Markus Jochum ◽  
Raghu Murtugudde
Keyword(s):  
Indian Ocean ◽  
Interannual Variability ◽  
Indian Monsoon ◽  
Tropical Indian Ocean ◽  
Western Indian Ocean ◽  
Internal Variability ◽  
Ocean Dynamics ◽  
Persistence Time ◽  
The Indian Ocean ◽  
Sst Anomalies

Abstract A 40-yr integration of an eddy-resolving numerical model of the tropical Indian Ocean is analyzed to quantify the interannual variability that is caused by the internal variability of ocean dynamics. It is found that along the equator in the western Indian Ocean internal variability contributes significantly to the observed interannual variability. This suggests that in this location the predictability of SST is limited to the persistence time of SST anomalies, which is approximately 100 days. Furthermore, a comparison with other sources of variability suggests that internal variability may play an important role in modifying the Indian monsoon or preconditioning the Indian Ocean dipole/zonal mode.

The interannual variability in the tropical Indian Ocean as simulated by a CGCM

2003 ◽  
Vol 20 (6) ◽  
pp. 567-582 ◽  
Author(s):  
S. Gualdi ◽  
E. Guilyardi ◽  
A. Navarra ◽  
S. Masina ◽  
P. Delecluse
Keyword(s):  
Indian Ocean ◽  
Interannual Variability ◽  
Tropical Indian Ocean

Effects of Climate Modes on Interannual Variability of Upwelling in the Tropical Indian Ocean

2020 ◽  
Vol 33 (4) ◽  
pp. 1547-1573 ◽  
Author(s):  
Xiaolin Zhang ◽  
Weiqing Han
Keyword(s):  
Wave Propagation ◽  
Indian Ocean ◽  
Interannual Variability ◽  
El Niño ◽  
El Nino ◽  
Tropical Indian Ocean ◽  
Strong Impact ◽  
Central Pacific ◽  
El Niño Events ◽  
El Nino Events

AbstractThis paper investigates interannual variability of the tropical Indian Ocean (IO) upwelling through analyzing satellite and in situ observations from 1993 to 2016 using the conventional Static Linear Regression Model (SLM) and Bayesian Dynamical Linear Model (DLM), and performing experiments using a linear ocean model. The analysis also extends back to 1979, using ocean–atmosphere reanalysis datasets. Strong interannual variability is observed over the mean upwelling zone of the Seychelles–Chagos thermocline ridge (SCTR) and in the seasonal upwelling area of the eastern tropical IO (EIO), with enhanced EIO upwelling accompanying weakened SCTR upwelling. Surface winds associated with El Niño–Southern Oscillation (ENSO) and the IO dipole (IOD) are the major drivers of upwelling variability. ENSO is more important than the IOD over the SCTR region, but they play comparable roles in the EIO. Upwelling anomalies generally intensify when positive IODs co-occur with El Niño events. For the 1979–2016 period, eastern Pacific (EP) El Niños overall have stronger impacts than central Pacific (CP) and the 2015/16 hybrid El Niño events, because EP El Niños are associated with stronger convection and surface wind anomalies over the IO; however, this relationship might change for a different interdecadal period. Rossby wave propagation has a strong impact on upwelling in the western basin, which causes errors in the SLM and DLM because neither can properly capture wave propagation. Remote forcing by equatorial winds is crucial for the EIO upwelling. While the first two baroclinic modes capture over 80%–90% of the upwelling variability, intermediate modes (3–8) are needed to fully represent IO upwelling.

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