scholarly journals How Predictable is the Indian Ocean Dipole?

2012 ◽  
Vol 140 (12) ◽  
pp. 3867-3884 ◽  
Author(s):  
Li Shi ◽  
Harry H. Hendon ◽  
Oscar Alves ◽  
Jing-Jia Luo ◽  
Magdalena Balmaseda ◽  
...  
Keyword(s):  
Indian Ocean ◽  
Surface Temperature ◽  
Indian Ocean Dipole ◽  
Lead Time ◽  
Research Centre ◽  
Model Errors ◽  
Seasonal Forecasts ◽  
Forecast System ◽  
Predictive Skill ◽  
The Indian Ocean

Abstract In light of the growing recognition of the role of surface temperature variations in the Indian Ocean for driving global climate variability, the predictive skill of the sea surface temperature (SST) anomalies associated with the Indian Ocean dipole (IOD) is assessed using ensemble seasonal forecasts from a selection of contemporary coupled climate models that are routinely used to make seasonal climate predictions. The authors assess predictions from successive versions of the Australian Bureau of Meteorology Predictive Ocean–Atmosphere Model for Australia (POAMA 15b and 24), successive versions of the NCEP Climate Forecast System (CFSv1 and CFSv2), the ECMWF seasonal forecast System 3 (ECSys3), and the Frontier Research Centre for Global Change system (SINTEX-F) using seasonal hindcasts initialized each month from January 1982 to December 2006. The lead time for skillful prediction of SST in the western Indian Ocean is found to be about 5–6 months while in the eastern Indian Ocean it is only 3–4 months when all start months are considered. For the IOD events, which have maximum amplitude in the September–November (SON) season, skillful prediction is also limited to a lead time of about one season, although skillful prediction of large IOD events can be longer than this, perhaps up to about two seasons. However, the tendency for the models to overpredict the occurrence of large events limits the confidence of the predictions of these large events. Some common model errors, including a poor representation of the relationship between El Niño and the IOD, are identified indicating that the upper limit of predictive skill of the IOD has not been achieved.

scholarly journals Mechanisms of asymmetry in sea surface temperature anomalies associated with the Indian Ocean Dipole revealed by closed heat budget

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Mai Nakazato ◽  
Shoichiro Kido ◽  
Tomoki Tozuka
Keyword(s):  
Indian Ocean ◽  
Surface Temperature ◽  
Indian Ocean Dipole ◽  
Heat Budget ◽  
Vertical Mixing ◽  
Sea Surface ◽  
Subsurface Temperature ◽  
Thermocline Feedback ◽  
The Indian Ocean ◽  
Sst Anomalies

AbstractThe Indian Ocean Dipole (IOD) is an interannual climate mode of the tropical Indian Ocean. Although it is known that negative sea surface temperature (SST) anomalies in the eastern pole during the positive IOD are stronger than positive SST anomalies during the negative IOD, no consensus has been reached on the relative importance of various mechanisms that contribute to this asymmetry. Based on a closed mixed layer heat budget analysis using a regional ocean model, here we show for the first time that the vertical mixing plays an important role in causing such asymmetry in SST anomalies in addition to the contributions from the nonlinear advection and the thermocline feedback proposed by previous studies. A decomposition of the vertical mixing term indicates that nonlinearity in the anomalous vertical temperature gradient associated with subsurface temperature anomalies and anomalous vertical mixing coefficients is the main driver of such asymmetry. Such variations in subsurface temperature are induced by the anomalous southeasterly trade winds along the Indonesian coast that modulate the thermocline depth through coastal upwelling/downwelling. Thus, the thermocline feedback contributes to the SST asymmetry not through the vertical advection as previously suggested, but via the vertical mixing.

Examination of interannual variability of sea surface temperature in the Indian Ocean using the physical decomposition dethod

2017 ◽  
Vol 1 (1) ◽  
Author(s):  
Xingrong Chen ◽  
Yi Cai ◽  
Fangli Qiao
Keyword(s):  
Indian Ocean ◽  
Surface Temperature ◽  
Interannual Variability ◽  
Surface Waters ◽  
Indian Ocean Dipole ◽  
Sea Surface ◽  
The Third ◽  
Fourth Term ◽  
The Indian Ocean ◽  
Spatially Varying

 The physical decomposition method suggested by Qian (2012) is used to examine the interannual variability of sea surface temperature (SST) and anomaly (SSTA) in the Indian Ocean (IO) for the period 1945.2003. The monthly mean SSTs taken from the global ocean reanalysis produced by the Simple Ocean Data Assimilation (SODA) are decomposed into four terms. The first term is the zonally averaged monthly climatological SST ([Tt(ϕ)]), which features relatively warm surface waters in the tropical IO and relatively colder surface waters over the southern IO. This term also has a relatively low SST pool between the Equator and 20°N. The SST at the center of the pool in summer is about 1-2°C lower than in spring and autumn. The second term is the spatially-varying monthly climatological SSTA (Tt*(λ,ϕ)), due mainly to the topographic effect and seasonal variation in wind forcing. The values of Tt*(λ,ϕ) are negative over the western coastal waters and positive over the eastern coastal and shelf waters in the tropical and northern IO. The third term is the zonally-averaged transient SSTA([T(ϕ,t)']Y). The largest values of [T(ϕ,t)']Y occur over the subtropical and mid-latitudes of the IO, which differs from the SSTA in the tropical waters of the Pacific Ocean. Time series of zonally and meridionally averaged T(ϕ,t)'Y in the tropical-subtropical IO is strongly correlated with the Indian Ocean basin-wide (IOBW) mode. The fourth term is the spatially-varying transient SSTA (T(λ,ϕ,t)*Y']. The REOF analysis of the fourth term demonstrates that the first REOF is correlated strongly with the South Indian Ocean Dipole (SIOD) mode. The second REOF is correlated strongly with the equatorial Indian Ocean dipole (IOD) mode. The third REOF is highly correlated with the tropical IOBW mode.

The Interdecadal Reverse of the Relationship and Feedback Mechanism between Sea Surface Temperature and Evaporation over the Indian Ocean during Boreal Autumn

2020 ◽  
Vol 33 (23) ◽  
pp. 10205-10219
Author(s):  
Bicheng Huang ◽  
Tao Su ◽  
Yongping Wu ◽  
Guolin Feng
Keyword(s):  
Indian Ocean ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Indian Ocean Dipole ◽  
Interaction Mechanism ◽  
Ocean Basin ◽  
Sea Surface ◽  
Indian Ocean Basin Mode ◽  
Low Level ◽  
The Indian Ocean

AbstractThe linkage between sea surface temperature (SST) and evaporation (EVP) plays an important role in air–sea interactions. In this study, the interaction mechanism of SST and EVP during boreal autumn was studied using correlation analysis, composite analysis, the EVP decomposition method, and singular value decomposition. The results showed that the correlation between SST and EVP in the Indian Ocean was reversed from positive to negative in the late 1990s. The significant positive SST–EVP relationship was attributed to the Indian Ocean basin mode forcing upon EVP during 1980–90. The decrease in wind speed–induced EVP and SST warming led to a significant negative SST–EVP relationship during 2005–15. Moreover, the negative SST–EVP correlation occurred when the Indian Ocean dipole (IOD) and subtropical Indian Ocean dipole (SIOD) exhibited inverse phases. The low-level moisture–EVP–SST feedback dominated the negative SST–EVP correlation in the negative IOD and positive SIOD (nIOD–pSIOD) pattern, whereas the wind–EVP–SST feedback played the leading role in the positive IOD and negative SIOD (pIOD–nSIOD) pattern. The EVP anomalies induced by the low-level anomalous anticyclone and cyclone were the main causes of the SST anomalies with inverse phases of the IOD and SIOD. The correlation between the SST and EVP reversal from positive to negative implies that the effect of the atmosphere on the ocean is as important as the external forcing of the ocean on the atmosphere.

scholarly journals Experimental Forecasts of the Indian Ocean Dipole Using a Coupled OAGCM

2007 ◽  
Vol 20 (10) ◽  
pp. 2178-2190 ◽  
Author(s):  
Jing-Jia Luo ◽  
Sebastien Masson ◽  
Swadhin Behera ◽  
Toshio Yamagata
Keyword(s):  
Indian Ocean ◽  
Real Time ◽  
Indian Ocean Dipole ◽  
Phase Locking ◽  
Western Indian Ocean ◽  
Forecast System ◽  
Ensemble Forecasts ◽  
Socioeconomic Impacts ◽  
The Past ◽  
The Indian Ocean

Abstract The Indian Ocean Dipole (IOD) has profound socioeconomic impacts on not only the countries surrounding the Indian Ocean but also various parts of the world. A forecast system is developed based on a relatively high-resolution coupled ocean–atmosphere GCM with only sea surface temperature (SST) information assimilated. Retrospective ensemble forecasts of the IOD index for the past two decades show skillful scores with up to a 3–4-month lead and a winter prediction barrier associated with its intrinsic strong seasonal phase locking. Prediction skills of the SST anomalies in both the eastern and western Indian Ocean are higher than those of the IOD index; this is because of the influences of ENSO, which is highly predictable. The model predicts the extreme positive IOD event in 1994 at a 2–3-season lead. The strong 1997 cold signal in the eastern pole, however, is not well predicted owing to errors in model initial subsurface conditions. The real-time forecast system with more ensembles successfully predicted the weak negative IOD event in the 2005 boreal fall and La Niña condition in the 2005/06 winter. Recent experimental real-time forecasts showed that a positive IOD event would appear in the 2006 summer and fall accompanied by a possible weak El Niño condition in the equatorial Pacific.

scholarly journals Improved Predictability of the Indian Ocean Dipole Using a Stochastic Dynamical Model Compared to the North American Multimodel Ensemble Forecast

2020 ◽  
Vol 35 (2) ◽  
pp. 379-399 ◽  
Author(s):  
Sen Zhao ◽  
Malte F. Stuecker ◽  
Fei-Fei Jin ◽  
Juan Feng ◽  
Hong-Li Ren ◽  
...  
Keyword(s):  
Indian Ocean ◽  
North American ◽  
Indian Ocean Dipole ◽  
Dynamical Model ◽  
False Alarms ◽  
Lead Times ◽  
Multimodel Ensemble ◽  
Predictive Skill ◽  
The Indian Ocean ◽  
North American Multimodel Ensemble

Abstract This study assesses the predictive skill of eight North American Multimodel Ensemble (NMME) models in predicting the Indian Ocean dipole (IOD). We find that the forecasted ensemble-mean IOD–El Niño–Southern Oscillation (ENSO) relationship deteriorates away from the observed relationship with increasing lead time, which might be one reason that limits the IOD predictive skill in coupled models. We are able to improve the IOD predictive skill using a recently developed stochastic dynamical model (SDM) forced by forecasted ENSO conditions. The results are consistent with the previous result that operational IOD predictability beyond persistence at lead times beyond one season is mostly controlled by ENSO predictability and the signal-to-noise ratio of the Indo-Pacific climate system. The multimodel ensemble (MME) investigated here is found to be of superior skill compared to each individual model at most lead times. Importantly, the skill of the SDM IOD predictions forced with forecasted ENSO conditions were either similar or better than those of the MME IOD forecasts. Moreover, the SDM forced with observed ENSO conditions exhibits significantly higher IOD prediction skill than the MME at longer lead times, suggesting the large potential skill increase that could be achieved by improving operational ENSO forecasts. We find that both cold and warm biases of the predicted Niño-3.4 index may cause false alarms of negative and positive IOD events, respectively, in NMME models. Many false alarms for IOD forecasts at lead times longer than one season in the original forecasts disappear or are significantly reduced in the SDM forced by forecasted ENSO conditions.

scholarly journals The Influence of Indian Ocean Dipole on Production of Tembang Fishing (Sardinella fimbriata) at Sunda Strait Indonesia

2020 ◽  
pp. 51-58
Author(s):  
Delima Mentari Amara ◽  
Yuniar Mulyani ◽  
Alexander M. A. Khan ◽  
Herman Hamdani
Keyword(s):  
Indian Ocean ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Indian Ocean Dipole ◽  
Pelagic Fish ◽  
Sea Surface ◽  
Dipole Mode ◽  
Dipole Mode Index ◽  
Mode Index ◽  
The Indian Ocean

Tembang is a pelagic fish which is important in Indonesia and the development on the Sunda Strait. The Indian Ocean Dipole could affect oceanography and at the same time will affect the population of fishes. The aim of this study was to determine the effect of IOD and oceanographic factors on the catch of Tembang fish. This research was conducted in the Sunda Strait waters by looking at the Dipole Mode Index (DMI) and oceanographic ocean conditions such as sea surface temperature and chlorophyll as well as the production of fish catches for 11 years from 2008-2018. IOD affects the catch of Tembang fish by 35.8%. Temperature influences the catch of Tembang fish in the Sunda Strait by 9.48%. Klorofil-a influences the catch of Tembang fish in Sunda Strait by 38.6%. DMI, Temperature, and Chlorophyll affect fish catches by 26.9%.

scholarly journals Analysis of Drought-Sensitive Areas and Evolution Patterns through Statistical Simulations of the Indian Ocean Dipole Mode

Water ◽  
2019 ◽  
Vol 11 (6) ◽  
pp. 1302 ◽  
Author(s):  
Qing-Gang Gao ◽  
Vonevilay Sombutmounvong ◽  
Lihua Xiong ◽  
Joo-Heon Lee ◽  
Jong-Suk Kim
Keyword(s):  
Indian Ocean ◽  
Indian Ocean Dipole ◽  
Diagnostic Techniques ◽  
Eastern Coast ◽  
Indochina Peninsula ◽  
Indian Ocean Dipole Mode ◽  
Sensitive Areas ◽  
The Indian Ocean ◽  
Long Term Trend

In this study, we investigated extreme droughts in the Indochina peninsula and their relationship with the Indian Ocean Dipole (IOD) mode. Areas most vulnerable to drought were analyzed via statistical simulations of the IOD based on historical observations. Results of the long-term trend analysis indicate that areas with increasing spring (March–May) rainfall are mainly distributed along the eastern coast (Vietnam) and the northwestern portions of the Indochina Peninsula (ICP), while Central and Northern Laos and Northern Cambodia have witnessed a reduction in spring rainfall over the past few decades. This trend is similar to that of extreme drought. During positive IOD years, the frequency of extreme droughts was reduced throughout Vietnam and in the southwestern parts of China, while increased drought was observed in Cambodia, Central Laos, and along the coastline adjacent to the Myanmar Sea. Results for negative IOD years were similar to changes observed for positive IOD years; however, the eastern and northern parts of the ICP experienced reduced droughts. In addition, the results of the statistical simulations proposed in this study successfully simulate drought-sensitive areas and evolution patterns of various IOD changes. The results of this study can help improve diagnostic techniques for extreme droughts in the ICP.

Sign in / Sign up

Export Citation Format

Share Document