The Connection between the Sea Surface Height Anomaly Preceding the Indian Ocean Dipole and Summer Rainfall in China

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.

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On the joint estimation of model and satellite sea surface height anomaly errors

Ocean Modelling ◽

10.1016/s1463-5003(99)00006-2 ◽

1999 ◽

Vol 1 (1) ◽

pp. 39-52 ◽

Cited By ~ 27

Author(s):

R. Tokmakian ◽

P.G. Challenor

Keyword(s):

Sea Surface Height ◽

Joint Estimation ◽

Sea Surface ◽

Height Anomaly ◽

Sea Surface Height Anomaly

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Interannual Variability in Sea Surface Height at Southern Midlatitudes of the Indian Ocean

Journal of Physical Oceanography ◽

10.1175/jpo-d-20-0279.1 ◽

2021 ◽

Vol 51 (5) ◽

pp. 1595-1609

Author(s):

Motoki Nagura ◽

Michael J. McPhaden

Keyword(s):

Indian Ocean ◽

Interannual Variability ◽

Sea Surface Height ◽

Wind Forcing ◽

Sea Surface ◽

The South ◽

South Indian Ocean ◽

Eastern Boundary ◽

South Indian ◽

The Indian Ocean

AbstractThis study examines interannual variability in sea surface height (SSH) at southern midlatitudes of the Indian Ocean (10°–35°S). Our focus is on the relative role of local wind forcing and remote forcing from the equatorial Pacific Ocean. We use satellite altimetry measurements, an atmospheric reanalysis, and a one-dimensional wave model tuned to simulate observed SSH anomalies. The model solution is decomposed into the part driven by local winds and that driven by SSH variability radiated from the western coast of Australia. Results show that variability radiated from the Australian coast is larger in amplitude than variability driven by local winds in the central and eastern parts of the south Indian Ocean at midlatitudes (between 19° and 33°S), whereas the influence from eastern boundary forcing is confined to the eastern basin at lower latitudes (10° and 17°S). The relative importance of eastern boundary forcing at midlatitudes is due to the weakness of wind stress curl anomalies in the interior of the south Indian Ocean. Our analysis further suggests that SSH variability along the west coast of Australia originates from remote wind forcing in the tropical Pacific, as is pointed out by previous studies. The zonal gradient of SSH between the western and eastern parts of the south Indian Ocean is also mostly controlled by variability radiated from the Australian coast, indicating that interannual variability in meridional geostrophic transport is driven principally by Pacific winds.

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Space-based observation of chlorophyll, sea surface temperature, nitrate, and sea surface height anomaly over the Bay of Bengal and Arabian Sea

Advances in Space Research ◽

10.1016/j.asr.2016.08.038 ◽

2017 ◽

Vol 59 (1) ◽

pp. 33-44 ◽

Cited By ~ 6

Author(s):

R.K. Sarangi ◽

K. Nanthini Devi

Keyword(s):

Surface Temperature ◽

Sea Surface Temperature ◽

Bay Of Bengal ◽

Arabian Sea ◽

Sea Surface Height ◽

Sea Surface ◽

Height Anomaly ◽

Sea Surface Height Anomaly

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Dynamics of the seasonal variations in the Indian Ocean from TOPEX/POSEIDON sea surface height and an ocean model

Geophysical Research Letters ◽

10.1029/98gl01401 ◽

1998 ◽

Vol 25 (11) ◽

pp. 1915-1918 ◽

Cited By ~ 32

Author(s):

Jiayan Yang ◽

Lisan Yu ◽

Chester J. Koblinsky ◽

David Adamec

Keyword(s):

Indian Ocean ◽

Seasonal Variations ◽

Sea Surface Height ◽

Ocean Model ◽

Sea Surface ◽

The Indian Ocean

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Seasonality and Predictability of the Indian Ocean Dipole Mode: ENSO Forcing and Internal Variability

Journal of Climate ◽

10.1175/jcli-d-15-0078.1 ◽

2015 ◽

Vol 28 (20) ◽

pp. 8021-8036 ◽

Cited By ~ 49

Author(s):

Yun Yang ◽

Shang-Ping Xie ◽

Lixin Wu ◽

Yu Kosaka ◽

Ngar-Cheung Lau ◽

...

Keyword(s):

Indian Ocean ◽

Indian Ocean Dipole ◽

Internal Variability ◽

Forced Response ◽

Sea Surface ◽

Boreal Summer ◽

Destructive Interference ◽

Indian Ocean Basin Mode ◽

Indian Ocean Dipole Mode ◽

The Indian Ocean

Abstract This study evaluates the relative contributions to the Indian Ocean dipole (IOD) mode of interannual variability from the El Niño–Southern Oscillation (ENSO) forcing and ocean–atmosphere feedbacks internal to the Indian Ocean. The ENSO forcing and internal variability is extracted by conducting a 10-member coupled simulation for 1950–2012 where sea surface temperature (SST) is restored to the observed anomalies over the tropical Pacific but interactive with the atmosphere over the rest of the World Ocean. In these experiments, the ensemble mean is due to ENSO forcing and the intermember difference arises from internal variability of the climate system independent of ENSO. These elements contribute one-third and two-thirds of the total IOD variance, respectively. Both types of IOD variability develop into an east–west dipole pattern because of Bjerknes feedback and peak in September–November. The ENSO forced and internal IOD modes differ in several important ways. The forced IOD mode develops in August with a broad meridional pattern and eventually evolves into the Indian Ocean basin mode, while the internal IOD mode grows earlier in June, is more confined to the equator, and decays rapidly after October. The internal IOD mode is more skewed than the ENSO forced response. The destructive interference of ENSO forcing and internal variability can explain early terminating IOD events, referred to as IOD-like perturbations that fail to grow during boreal summer. The results have implications for predictability. Internal variability, as represented by preseason sea surface height anomalies off Sumatra, contributes to predictability considerably. Including this indicator of internal variability, together with ENSO, improves the predictability of IOD.

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