Interannual sea level variability in the tropical Pacific Ocean from 1993 to 2006

Lu, Qi; Zuo, Juncheng; Li, Yanfang; Chen, Meixiang

doi:10.1016/j.gloplacha.2013.04.008

Cited by 7 publications

(3 citation statements)

References 46 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The locations and boundaries are comparable with the existing literature [37,38]. The significance of the Indian Ocean changes in this El Niño event, which cannot be directly seen and extracted from the original and decomposed components, has already been proved in the literature [39]. The D4 components are slightly different from the D5 components.…”

Section: Evaluations By Tracking the 1997-1998 El Niño Evolutionsupporting

confidence: 80%

Exploratory Method for Spatio-Temporal Feature Extraction and Clustering: An Integrated Multi-Scale Framework

Luo

Xiao

et al. 2015

IJGI

View full text Add to dashboard Cite

This paper presents an integrated framework for exploratory multi-scale spatio-temporal feature extraction and clustering of spatio-temporal data. The framework combines the multi-scale spatio-temporal decomposition, feature identification, feature enhancing and clustering in a unified process. The original data are firstly reorganized as multi-signal time series, and then decomposed by the multi-signal wavelet. Exploratory data analysis methods, such as histograms, are used for feature identification and enhancing. The spatio-temporal evolution process of the multi-scale features can then be tracked by the feature clusters based on the data adaptive Fuzzy C-Means Cluster. The approach was tested with the global 0.25° satellite altimeter data over a period of 21 years from 1993 to 2013. The tracking of the multi-scale spatio-temporal evolution characteristics of the 1997-98 strong El Niño were used as validation. The results show that our method can clearly reveal and track the spatio-temporal distribution and evolution of complex geographical phenomena. Our approach is efficient for global scale data analysis, and can be used to explore the multi-scale pattern of spatio-temporal processes.

show abstract

Section: Evaluations By Tracking the 1997-1998 El Niño Evolutionsupporting

confidence: 80%

Exploratory Method for Spatio-Temporal Feature Extraction and Clustering: An Integrated Multi-Scale Framework

Luo

Xiao

et al. 2015

IJGI

View full text Add to dashboard Cite

show abstract

“…Forget and Ponte [36] used the ECCO reanalysis to investigate the partitioning of steric and barystatic sea level and inferred their complementary impact on sea level changes, with the former dominating low-frequency variability (>1 year) and the latter more prominent at high frequencies (<3 months). At the regional scale, advection and diffusion also play an important role, and surface heating may induce significant variations as well, especially in the tropical regions [64]. The redistribution of water mass may be further identified as the predominant process for regional sea level decadal changes [65], although regional exceptions (e.g., in the western tropical Pacific and eastern tropical Indian oceans) exist.…”

Section: Using Reanalyses To Partition Causes Of Sea Level Variabilitymentioning

confidence: 99%

Steric Sea Level Changes from Ocean Reanalyses at Global and Regional Scales

Storto

Bonaduce

Feng

et al. 2019

Water

View full text Add to dashboard Cite

Sea level has risen significantly in the recent decades and is expected to rise further based on recent climate projections. Ocean reanalyses that synthetize information from observing networks, dynamical ocean general circulation models, and atmospheric forcing data offer an attractive way to evaluate sea level trend and variability and partition the causes of such sea level changes at both global and regional scales. Here, we review recent utilization of reanalyses for steric sea level trend investigations. State-of-the-science ocean reanalysis products are then used to further infer steric sea level changes. In particular, we used an ensemble of centennial reanalyses at moderate spatial resolution (between 0.5 × 0.5 and 1 × 1 degree) and an ensemble of eddy-permitting reanalyses to quantify the trends and their uncertainty over the last century and the last two decades, respectively. All the datasets showed good performance in reproducing sea level changes. Centennial reanalyses reveal a 1900–2010 trend of steric sea level equal to 0.47 ± 0.04 mm year−1, in agreement with previous studies, with unprecedented rise since the mid-1990s. During the altimetry era, the latest vintage of reanalyses is shown to outperform the previous ones in terms of skill scores against the independent satellite data. They consistently reproduce global and regional upper ocean steric expansion and the association with climate variability, such as ENSO. However, the mass contribution to the global mean sea level rise is varying with products and its representability needs to be improved, as well as the contribution of deep and abyssal waters to the steric sea level rise. Similarly, high-resolution regional reanalyses for the European seas provide valuable information on sea level trends, their patterns, and their causes.

show abstract

“…Many islands in the WTP region have been reported to be suffering from various influences of prominent sea level rise and variability (Becker et al, 2012; Stammer et al, 2013). There is a paramount demand for improved understanding of the regional sea level variability of the WTP (e.g., Chang et al, 2013; Church et al, 2013; Han et al, 2014, 2017; Lu et al, 2013; Milne et al, 2009; Palanisamy et al, 2015; Stammer et al, 2013). Sea level variability in the WTP is particularly pronounced on interannual timescales, owing to the strong forcing effects of El Niño‐Southern Oscillation (ENSO) (e.g., Antonov et al, 2005; Becker et al, 2012; Cazenave et al, 2008; Chang et al, 2013; Cheng et al, 2008; Duan et al, 2020; Han et al, 2017; Palanisamy et al, 2015).…”

Section: Introductionmentioning

confidence: 99%

Asymmetry of Interannual Sea Level Variability in the Western Tropical Pacific: Responses to El Niño and La Niña

Ren

Zheng

et al. 2020

JGR Oceans

View full text Add to dashboard Cite

The western tropical Pacific (WTP) exhibits pronounced large-scale sea level anomalies (SLAs) during El Niño-Southern Oscillation (ENSO) events with amplitudes of~0.1 m, exerting potential threats to many low-lying islands. It is found that the sea level falling in El Niño condition is evidently stronger than the rising in La Niña condition. This SLA asymmetry in the WTP associated with ENSO is investigated in this study, and the underlying dynamic processes are explored. Such asymmetry is most prominent at around 160°E with the SLA response to El Niño being three times stronger than to La Niña, but it is much inconspicuous near the western boundary. Sensitivity experiments of a simplified ocean model suggest that the different structures of surface wind anomalies between El Niño and La Niña conditions are critical in generating asymmetric SLA responses of the WTP. The El Niño's westerly wind anomaly patch locates more to the east than the La Niña's easterly wind patch during the mature stage, and its upwelling effects are accumulated over a wider longitude range and cause stronger negative SLAs in the WTP. Near the western boundary, however, upwelling effects are attenuated by easterly wind anomalies during the mature stage of El Niño. Further analysis reveals that eastern Pacific-type El Niño events are more favorable for generating asymmetric SLAs in the WTP than the central Pacific-type events. Plain Language Summary El Niño-Southern Oscillation (ENSO) is the most important climate variability phenomenon in the tropical Pacific and causes strong interannual sea level anomalies (SLAs) in the western tropical Pacific (WTP). The El Niño's sea level falling is evidently stronger than the La Niña's sea level rising. This difference is most prominent near 160°E with stronger El Niño's sea level falling but becomes much less evident near the western boundary of the Pacific Basin. The different surface wind anomaly structures between El Niño and La Niña are the primary cause. El Niño's westerly wind anomaly center locates more east than La Niña's easterly wind anomaly center in their mature phase, leading to stronger sea level falling in the WTP through westerly wind anomalies over the wide longitude range. The sea level falling is weakened by easterly wind anomalies generated near the western boundary. By contrast, effect of La Niña's easterly wind anomaly strengthens monotonically from east to west, and the produced sea level rising signatures are mainly confined to the WTP. The wind forcing structure of eastern Pacific-type El Niño is more favorable for generating asymmetric SLAs in the WTP than central Pacific-type events.

show abstract

Interannual sea level variability in the tropical Pacific Ocean from 1993 to 2006

Cited by 7 publications

References 46 publications

Exploratory Method for Spatio-Temporal Feature Extraction and Clustering: An Integrated Multi-Scale Framework

Exploratory Method for Spatio-Temporal Feature Extraction and Clustering: An Integrated Multi-Scale Framework

Steric Sea Level Changes from Ocean Reanalyses at Global and Regional Scales

Asymmetry of Interannual Sea Level Variability in the Western Tropical Pacific: Responses to El Niño and La Niña

Contact Info

Product

Resources

About