The relationship between Indian Ocean sea–surface temperature and East African rainfall

2005 ◽  
Vol 363 (1826) ◽  
pp. 43-47 ◽  
Author(s):  
Emily Black
Keyword(s):  
Indian Ocean ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Southern Oscillation ◽  
Sea Surface ◽  
East African ◽  
African Rainfall ◽  
The Pacific ◽  
The Indian Ocean ◽  
The Relationship

Knowledge of the processes that control East African rainfall is essential for the development of seasonal forecasting systems, which may mitigate the effects of flood and drought. This study uses observational data to unravel the relationship between the Indian Ocean Dipole (IOD), the El Niño Southern Oscillation (ENSO) and rainy autumns in East Africa. Analysis of sea–surface temperature data shows that strong East African rainfall is associated with warming in the Pacific and Western Indian Oceans and cooling in the Eastern Indian Ocean. The resemblance of this pattern to that which develops during IOD events implies a link between the IOD and strong East African rainfall. Further investigation suggests that the observed teleconnection between East African rainfall and ENSO is a manifestation of a link between ENSO and the IOD.

scholarly journals The Years of El Niño, La Niña, and Interactions with the Tropical Indian Ocean

2007 ◽  
Vol 20 (13) ◽  
pp. 2872-2880 ◽  
Author(s):  
Gary Meyers ◽  
Peter McIntosh ◽  
Lidia Pigot ◽  
Mike Pook
Keyword(s):  
Indian Ocean ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
El Niño ◽  
El Nino ◽  
Southern Oscillation ◽  
Sea Surface ◽  
El Nino Southern Oscillation ◽  
La Nina ◽  
The Indian Ocean

Abstract The Indian Ocean zonal dipole is a mode of variability in sea surface temperature that seriously affects the climate of many nations around the Indian Ocean rim, as well as the global climate system. It has been the subject of increasing research, and sometimes of scientific debate concerning its existence/nonexistence and dependence/independence on/from the El Niño–Southern Oscillation, since it was first clearly identified in Nature in 1999. Much of the debate occurred because people did not agree on what years are the El Niño or La Niña years, not to mention the newly defined years of the positive or negative dipole. A method that identifies when the positive or negative extrema of the El Niño–Southern Oscillation and Indian Ocean dipole occur is proposed, and this method is used to classify each year from 1876 to 1999. The method is statistical in nature, but has a strong basis on the oceanic physical mechanisms that control the variability of the near-equatorial Indo-Pacific basin. Early in the study it was found that some years could not be clearly classified due to strong decadal variation; these years also must be recognized, along with the reason for their ambiguity. The sensitivity of the classification of years is tested by calculating composite maps of the Indo-Pacific sea surface temperature anomaly and the probability of below median Australian rainfall for different categories of the El Niño–Indian Ocean relationship.

scholarly journals THE VULNERABILITY STUDY OF LEMURU (SARDINELLA LEMURU) FISH RESOURCES SUSTAINABILITY IN BALI STRAIT IN CORELLATION WITH ENSO AND IOD

2017 ◽  
Vol 11 (2) ◽  
pp. 140
Author(s):  
Candra Saputra ◽  
I Wayan Arthana ◽  
I Gede Hendrawan
Keyword(s):  
Indian Ocean ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
El Niño ◽  
Strong Influence ◽  
El Nino ◽  
Southern Oscillation ◽  
Sea Surface ◽  
Fish Catch ◽  
The Relationship

The aim of this research is to know the relationship between lemuru fish catch to Sea Surface Temperature (SST), El-Nino Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD) phenomenon in Bali Strait. The results showed, that in the period 2007 – 2016. fluctuations of catches lemuru tends to decline. Sea Surface Temperature (SST) distribution with the lowest temperature 25,28oC at 24,53oC - 27,16oC and the highest temperature is 29,31oC in the range of 28,730C – 30,490C. The lowest temperature occurred in July - September while the highest temperature occurred in January - April. Based on the calculation there is a linkage and relationship between catch and SST as shown on the value of determination and correlation reached 50,0% and 70,73%. Most of the catches occurred in the west season and then the transition II, transition I and East Season. The relationship of ENSO phenomenon to the catch during the El-Nino phase of lemuru catch will increase while in the phase of La-Nina the catch of lemuru will decrease, because time of El-Nino phase of the sea surface temperature (SST) relative low which results in the chlorophyll-a mean case which is a food sources of lemuru fish. Based on Trenberth's theory, (1997), the rise and fall of the ENSO Index of less than six months is not stated in ENSO. From the calculation results during the research of 2007 - 2016 happened three times ENSO phenomenon that is in 2009, 2010 and 2015. At the time of the IOD phenomenon, the IOD (+) phase will result in a decrease in catch while the normal IOD phase and (-) will increase the catch. From the results of this study can also be observed, in the year 2007 - 2011 phenomenon ENSO and IOD have a strong influence on the catch while in the year 2012 - 2016 the influence of the phenomenon of ENSO and IOD has no strong influence caused by the quantity of lemuru fish that have been over exploitation that resulted in the current Bali Strait on Over Fishing status.   Keywords : Fish Catch; El-Nino Southern Oscillation (ENSO); Indian Ocean                    Dipole (IOD)

scholarly journals The Pacific–Indian Ocean associated mode in CMIP5 models

Ocean Science ◽  
2020 ◽  
Vol 16 (2) ◽  
pp. 469-482 ◽  
Author(s):  
Minghao Yang ◽  
Xin Li ◽  
Weilai Shi ◽  
Chao Zhang ◽  
Jianqi Zhang
Keyword(s):  
Indian Ocean ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Climate Models ◽  
Southern Oscillation ◽  
Sea Surface ◽  
Cmip5 Models ◽  
Future Climate Change ◽  
The Pacific ◽  
Basin Scale

Abstract. The Pacific–Indian Ocean associated mode (PIOAM), defined as the first dominant mode (empirical orthogonal function, EOF1) of sea surface temperature anomalies (SSTAs) in the Pacific–Indian Ocean between 20∘ S and 20∘ N, is the product of the tropical air–sea interaction at the cross-basin scale and the main mode of ocean variation in the tropics. Evaluating the capability of current climate models to simulate the PIOAM and finding the possible factors that affect the simulation results are beneficial in the pursuit of more accurate future climate change prediction. Based on the 55-year Hadley Centre Global Sea Ice and Sea Surface Temperature (HadISST) dataset and the output data from 21 Coupled Model Intercomparison Project (CMIP) phase 5 (CMIP5) models, the PIOAM in these CMIP5 models is assessed. Instead of using the time coefficient (PC1) of the PIOAM as its index, we chose to utilize the alternative PIOAM index (PIOAMI), defined with SSTA differences in the boxes, to describe the PIOAM. It is found that the explained variance of the PIOAM in almost all 21 CMIP5 models is underestimated. Although all models reproduce the spatial pattern of the positive sea surface temperature anomaly in the eastern equatorial Pacific well, only one-third of these models successfully simulate the El Niño–Southern Oscillation (ENSO) mode with the east–west inverse phase in the Pacific Ocean. In general, CCSM4, GFDL-ESM2M and CMCC-CMS have a stronger capability to capture the PIOAM than the other models. The strengths of the PIOAM in the positive phase in less than one-fifth of the models are slightly greater, and very close to the HadISST dataset, especially CCSM4. The interannual variation of the PIOAM can be measured by CCSM4, GISS-E2-R and FGOALS-s2.

scholarly journals Short-Term Variation of the Surface Flow Pattern South of Lombok Strait Observed from the Himawari-8 Sea Surface Temperature

2019 ◽  
Vol 11 (12) ◽  
pp. 1491 ◽  
Author(s):  
Naokazu Taniguchi ◽  
Shinichiro Kida ◽  
Yuji Sakuno ◽  
Hidemi Mutsuda ◽  
Fadli Syamsudin
Keyword(s):  
Indian Ocean ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Surface Flow ◽  
Sea Surface ◽  
Surface Velocity ◽  
Thermal Plume ◽  
Short Term ◽  
Flow Variation ◽  
The Indian Ocean

Spatial and temporal information on oceanic flow is fundamental to oceanography and crucial for marine-related social activities. This study attempts to describe the short-term surface flow variation in the area south of the Lombok Strait in the northern summer using the hourly Himawari-8 sea surface temperature (SST). Although the uncertainty of this temperature is relatively high (about 0.6 ∘ C), it could be used to discuss the flow variation with high spatial resolution because sufficient SST differences are found between the areas north and south of the strait. The maximum cross-correlation (MCC) method is used to estimate the surface velocity. The Himawari-8 SST clearly shows Flores Sea water intruding into the Indian Ocean with the high-SST water forming a warm thermal plume on a tidal cycle. This thermal plume flows southward at a speed of about 2 m / s . The Himawari-8 SST indicates a southward flow from the Lombok Strait to the Indian Ocean, which blocks the South Java Current flowing eastward along the southern coast of Nusa Tenggara. Although the satellite data is limited to the surface, we found it useful for understanding the spatial and temporal variations in the surface flow field.

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