Humboldt penguins outmanoeuvring El Nino

2000 ◽  
Vol 203 (15) ◽  
pp. 2311-2322 ◽  
Author(s):  
B. Culik ◽  
J. Hennicke ◽  
T. Martin
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Chlorophyll A ◽  
Wind Direction ◽  
El Niño ◽  
El Nino ◽  
Southern Oscillation ◽  
Dive Duration ◽  
Sea Surface ◽  
Day Length

We satellite-tracked five Humboldt penguins during the strong 1997/98 El Nino Southern Oscillation (ENSO) from their breeding island Pan de Azucar (26 degrees 09′S, 70 degrees 40′W) in Northern Chile and related their activities at sea to satellite-derived information on sea surface temperature (SST), sea surface temperature anomaly (SSTA), wind direction and speed, chlorophyll a concentrations and statistical data on fishery landings. We found that Humboldt penguins migrated by up to 895 km as marine productivity decreased. The total daily dive duration was highly correlated with SSTA, ranging from 3.1 to 12.5 h when the water was at its warmest (+4 degrees C). Birds travelled between 2 and 116 km every day, travelling further when SSTA was highest. Diving depths (maximum 54 m), however, were not increased with respect to previous years. Two penguins migrated south and, independently of each other, located an area of high chlorophyll a concentration 150 km off the coast. Humboldt penguins seem to use day length, temperature gradients, wind direction and olfaction to adapt to changing environmental conditions and to find suitable feeding grounds. This makes Humboldt penguins biological in situ detectors of highly productive marine areas, with a potential use in the verification of trends detected by remote sensors on board satellites.

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 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 Indian Ocean Dipolelike Variability in the CSIRO Mark 3 Coupled Climate Model

2005 ◽  
Vol 18 (10) ◽  
pp. 1449-1468 ◽  
Author(s):  
Wenju Cai ◽  
Harry H. Hendon ◽  
Gary Meyers
Keyword(s):  
Indian Ocean ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
El Niño ◽  
Climate Models ◽  
Rossby Waves ◽  
Climate Model ◽  
El Nino ◽  
Southern Oscillation ◽  
Sea Surface

Abstract Coupled ocean–atmosphere variability in the tropical Indian Ocean is explored with a multicentury integration of the Commonwealth Scientific and Industrial Research Organisation (CSIRO) Mark 3 climate model, which runs without flux adjustment. Despite the presence of some common deficiencies in this type of coupled model, zonal dipolelike variability is produced. During July through November, the dominant mode of variability of sea surface temperature resembles the observed zonal dipole and has out-of-phase rainfall variations across the Indian Ocean basin, which are as large as those associated with the model El Niño–Southern Oscillation (ENSO). In the positive dipole phase, cold SST anomaly and suppressed rainfall south of the equator on the Sumatra–Java coast drives an anticyclonic circulation anomaly that is consistent with the steady response (Gill model) to a heat sink displaced south of the equator. The northwest–southeast tilting Sumatra–Java coast results in cold sea surface temperature (SST) centered south of the equator, which forces anticylonic winds that are southeasterly along the coast, which thus produces local upwelling, cool SSTs, and promotes more anticylonic winds; on the equator, the easterlies raise the thermocline to the east via upwelling Kelvin waves and deepen the off-equatorial thermocline to the west via off-equatorial downwelling Rossby waves. The model dipole mode exhibits little contemporaneous relationship with the model ENSO; however, this does not imply that it is independent of ENSO. The model dipole often (but not always) develops in the year following El Niño. It is triggered by an unrealistic transmission of the model’s ENSO discharge phase through the Indonesian passages. In the model, the ENSO discharge Rossby waves arrive at the Sumatra–Java coast some 6 to 9 months after an El Niño peaks, causing the majority of model dipole events to peak in the year after an ENSO warm event. In the observed ENSO discharge, Rossby waves arrive at the Australian northwest coast. Thus the model Indian Ocean dipolelike variability is triggered by an unrealistic mechanism. The result highlights the importance of properly representing the transmission of Pacific Rossby waves and Indonesian throughflow in the complex topography of the Indonesian region in coupled climate models.

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.

scholarly journals A Verified Estimation of the El Niño Index Niño-3.4 since 1877

2009 ◽  
Vol 22 (14) ◽  
pp. 3979-3992 ◽  
Author(s):  
Lucia Bunge ◽  
Allan J. Clarke
Keyword(s):  
Time Series ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
El Niño ◽  
El Nino ◽  
Southern Oscillation ◽  
Correlation Coefficients ◽  
Sea Surface ◽  
Monthly Time Series ◽  
Sst Anomaly

Abstract Decadal and longer time-scale variabilities of the best known El Niño–Southern Oscillation (ENSO) indexes are poorly correlated before 1950, and so knowledge of interdecadal variability and trend in ENSO indexes is dubious, especially before 1950. To address this problem, the authors constructed and compared physically related monthly ENSO indexes. The base index was El Niño index Niño-3.4, the sea surface temperature (SST) anomaly averaged over the equatorial box bounded by 5°N, 5°S, 170°W, and 120°W; the authors also constructed indexes based on the nighttime marine air temperature over the Niño-3.4 region (NMAT3.4) and an equatorial Southern Oscillation index (ESOI). The Niño-3.4 index used the “uninterpolated” sea surface temperature data from the Second Hadley Centre Sea Surface Temperature dataset (HadSST2), a dataset with smaller uncertainty and better geographical coverage than others. In constructing the index, data at each point for a given month were weighted to take into account the typical considerable spatial variation of the SST anomaly over the Niño-3.4 box as well as the number of observations at that point for that month. Missing monthly data were interpolated and “noise” was reduced by using the result that Niño-3.4 has essentially the same calendar month amplitude structure every year. This 12-point calendar month structure from April to March was obtained by an EOF analysis over the last 58 yr and then was fitted to the entire monthly time series using a least squares approach. Equivalent procedures were followed for NMAT3.4 and ESOI. The new ESOI uses Darwin atmospheric pressure in the west and is based on theory that allows for variations of the atmospheric boundary layer depth across the Pacific. The new Niño-3.4 index was compared with NMAT3.4, the new ESOI, and with a record of δ18O from a coral at Palmyra, an atoll inside the region Niño-3.4 (Cobb et al.). Correlation coefficients between Niño-3.4 and the three monthly indexes mentioned above before 1950 are 0.84, 0.87, 0.73 and 0.93, 0.86, 0.73 for decadal time scales. These relatively high correlation coefficients between physically related but independent monthly time series suggest that this study has improved knowledge of low-frequency variability. All four indexes are consistent with a rise in Niño-3.4 SST and the weakening of the equatorial Pacific winds since about 1970.

Interdecadal Change in Properties of El Niño–Southern Oscillation in an Intermediate Coupled Model

2005 ◽  
Vol 18 (9) ◽  
pp. 1369-1380 ◽  
Author(s):  
Rong-Hua Zhang ◽  
Antonio J. Busalacchi
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
El Niño ◽  
El Nino ◽  
Southern Oscillation ◽  
Coupled Model ◽  
Ocean Model ◽  
Sea Surface ◽  
Subsurface Temperature ◽  
Intermediate Coupled Model

Abstract The role of subsurface temperature variability in modulating El Niño–Southern Oscillation (ENSO) properties is examined using an intermediate coupled model (ICM), consisting of an intermediate dynamic ocean model and a sea surface temperature (SST) anomaly model. An empirical procedure is used to parameterize the temperature of subsurface water entrained into the mixed layer (Te) from sea level (SL) anomalies via a singular value decomposition (SVD) analysis for use in simulating sea surface temperature anomalies (SSTAs). The ocean model is coupled to a statistical atmospheric model that estimates wind stress anomalies also from an SVD analysis. Using the empirical Te models constructed from two subperiods, 1963–79 (T63–79e) and 1980–96 (T80–96e), the coupled system exhibits strikingly different properties of interannual variability (the oscillation period, spatial structure, and temporal evolution). For the T63–79e model, the system features a 2-yr oscillation and westward propagation of SSTAs on the equator, while for the T80–96e model, it is characterized by a 5-yr oscillation and eastward propagation. These changes in ENSO properties are consistent with the behavior shift of El Niño observed in the late 1970s. Heat budget analyses further demonstrate a controlling role played by the vertical advection of subsurface temperature anomalies in determining the ENSO properties.

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