scholarly journals The relationship between El Niño Southern Oscillation (ENSO) and oceanographic parameters in North Sulawesi waters

2021 ◽  
Vol 9 (1) ◽  
Author(s):  
Astrid Y. Lasut ◽  
Wilhelmina Patty ◽  
Veibe Warouw ◽  
Calvyn A. Sondakh ◽  
Robert A. Bara ◽  
...  
Keyword(s):  
Wind Speed ◽  
Chlorophyll A ◽  
El Niño ◽  
El Nino ◽  
Southern Oscillation ◽  
Sea Surface ◽  
El Niño Southern Oscillation ◽  
El Nino Southern Oscillation ◽  
Fertility Level ◽  
North Sulawesi

Information about oceanographic conditions is important to determine the fertility level of waters. Oceanographic parameters in water can be influenced by global climate factors, one of them is the ENSO (El Niño Southern Oscillation) phenomenon. There have been many studies on the effect of ENSO phenomenon on oceanographic variability, but no studies have been carried out in the waters of North Sulawesi. This study aims to determine the effect of the ENSO phenomenon on the variability distribution of oceanographic parameters in North Sulawesi waters. The data used for this study were Sea Surface Temperature (SST) and chlorophyll-a from the AQUA-MODIS imaging results, wind reanalysis results from ECMWF, and Nino 3.4 index as an indicator of ENSO from NOAA. The data were processed and analyzed using quantitative analysis methods in the form of graphics. The results showed an indirect effect of the ENSO phenomenon on SST parameters and chlorophyll-a. This is because the effect of the ENSO phenomenon occurred in a certain period:  when strong El Niño triggered low temperatures of sea surface and high chlorophyll-a, and when La Niña was strong it triggered high temperatures of sea surface and low chlorophyll-a. Meanwhile, the wind speed pattern showed an insignificant effect because the wind speed was still dominated by the influence of the monsoon pattern.Indonesian title: Hubungan antara El Niño Southern Oscillation (ENSO) dan parameter oseanografi di perairan Sulawesi Utara

scholarly journals A New Picture of the Global Impacts of El Nino-Southern Oscillation

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Jialin Lin ◽  
Taotao Qian
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
El Niño ◽  
El Nino ◽  
Southern Oscillation ◽  
Tropical Pacific ◽  
Sea Surface ◽  
El Niño Southern Oscillation ◽  
El Nino Southern Oscillation ◽  
Global Impacts

AbstractThe El Nino-Southern Oscillation (ENSO) is the dominant interannual variability of Earth’s climate system and plays a central role in global climate prediction. Outlooks of ENSO and its impacts often follow a two-tier approach: predicting ENSO sea surface temperature anomaly in tropical Pacific and then predicting its global impacts. However, the current picture of ENSO global impacts widely used by forecasting centers and atmospheric science textbooks came from two earliest surface station datasets complied 30 years ago, and focused on the extreme phases rather than the whole ENSO lifecycle. Here, we demonstrate a new picture of the global impacts of ENSO throughout its whole lifecycle based on the rich latest satellite, in situ and reanalysis datasets. ENSO impacts are much wider than previously thought. There are significant impacts unknown in the previous picture over Europe, Africa, Asia and North America. The so-called “neutral years” are not neutral, but are associated with strong sea surface temperature anomalies in global oceans outside the tropical Pacific, and significant anomalies of land surface air temperature and precipitation over all the continents.

scholarly journals Evidence from giant-clam <i>δ</i><sup>18</sup>O of intense El Ninõ–Southern Oscillation-related variability but reduced frequency 3700 years ago

2020 ◽  
Vol 16 (2) ◽  
pp. 597-610
Author(s):  
Yue Hu ◽  
Xiaoming Sun ◽  
Hai Cheng ◽  
Hong Yan
Keyword(s):  
Seasonal Variation ◽  
El Niño ◽  
El Nino ◽  
Southern Oscillation ◽  
Sea Surface ◽  
Sea Surface Salinity ◽  
El Niño Southern Oscillation ◽  
El Nino Southern Oscillation ◽  
Giant Clam ◽  
Xisha Islands

Abstract. Giant clams (Tridacna) are the largest marine bivalves, and their carbonate shells can be used for high-resolution paleoclimate reconstructions. In this contribution, δ18Oshell was used to estimate climatic variation in the Xisha Islands of the South China Sea. We first evaluate sea surface temperature (SST) and sea surface salinity (SSS) influence on the modern resampled monthly (r-monthly) resolution of Tridacna gigas δ18Oshell. The results obtained reveal that δ18Oshell seasonal variation is mainly controlled by SST and appears to be insensitive to local SSS change. Thus, the δ18O of Tridacna shells can be roughly used as a proxy of local SST: a 1 ‰ δ18Oshell change is roughly equal to 4.41 ∘C of SST. The r-monthly δ18O of a 40-year-old Tridacna squamosa (3673±28 BP) from the North Reef of the Xisha Islands was analyzed and compared with the modern specimen. The difference between the average δ18O of the fossil Tridacna shell (δ18O =-1.34 ‰) and the modern Tridacna specimen (δ18O =-1.15 ‰) probably implies a warm climate, roughly 0.84 ∘C, 3700 years ago. The seasonal variation 3700 years ago was slightly lower than that suggested by modern instrumental data, and the transition between warm and cold seasons was rapid. Higher amplitudes of reconstructed r-monthly and r-annual SST anomalies imply an enhanced climate variability during this warm period. Investigation of the El Ninõ–Southern Oscillation (ENSO) variation (based on the reconstructed SST series) indicates reduced ENSO frequency but increased ENSO-related variability and extreme El Ninõ winter events 3700 years ago.

scholarly journals An interaction network perspective on the relation between patterns of sea surface temperature variability and global mean surface temperature

2014 ◽  
Vol 5 (1) ◽  
pp. 1-14 ◽  
Author(s):  
A. Tantet ◽  
H. A. Dijkstra
Keyword(s):  
Community Structure ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
El Niño ◽  
El Nino ◽  
Southern Oscillation ◽  
Function Analysis ◽  
Sea Surface ◽  
El Niño Southern Oscillation ◽  
El Nino Southern Oscillation

Abstract. On interannual- to multidecadal timescales variability in sea surface temperature appears to be organized in large-scale spatiotemporal patterns. In this paper, we investigate these patterns by studying the community structure of interaction networks constructed from sea surface temperature observations. Much of the community structure can be interpreted using known dominant patterns of variability, such as the El Niño/Southern Oscillation and the Atlantic Multidecadal Oscillation. The community detection method allows us to bypass some shortcomings of Empirical Orthogonal Function analysis or composite analysis and can provide additional information with respect to these classical analysis tools. In addition, the study of the relationship between the communities and indices of global surface temperature shows that, while El Niño–Southern Oscillation is most dominant on interannual timescales, the Indian West Pacific and North Atlantic may also play a key role on decadal timescales. Finally, we show that the comparison of the community structure from simulations and observations can help detect model biases.

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