Sea Surface Temperature Variability Research Articles

Numerical Modeling of Atmospheric Temperature and Stratospheric Ozone Sensitivity to Sea Surface Temperature Variability

The results of numerical experiments with a chemistry–climate model of the lower and middle atmosphere are presented to study the sensitivity of the polar stratosphere of the Northern and Southern Hemispheres to sea surface temperature (SST) variability, both as a result of interannual variability associated with the Southern Oscillation, and because of long-term increases in SST under global warming. An analysis of the results of model experiments showed that for both scenarios of SST changes, the response of the polar stratosphere for the Northern and Southern Hemispheres is very different. In the Arctic, during the El Niño phase, conditions are created for the polar vortex to become less stable, and in the Antarctic, on the contrary, for it to become more stable, which is expressed in a weakening of the zonal wind in the winter in the Arctic and its increase in the Antarctic, followed by a spring decrease in temperature and concentration of ozone in the Antarctic and their increase in the Arctic. Global warming creates a tendency for the polar vortex to weaken in winter in the Arctic and strengthen it in the Antarctic. As a result, in the Antarctic, the concentration of ozone in the polar stratosphere decreases both in winter (June–August) and, especially, in spring (September–November). Global warming may hinder ozone recovery which is expected as a result of the reduced emissions of ozone-depleting substances. The model results demonstrate the dominant influence of Brewer–Dobson circulation variability on temperature and ozone in the polar stratosphere compared with changes in wave activity, both with changes in SST in the Southern Oscillation and with increases in SST due to global warming.

Logistic curve modelling of sea surface temperature and latent heat flux variability in the Tropical Indian Ocean

The Tropical Indian Ocean (TIO) is one of the most vulnerable regions to climate change due to its unique ocean-atmosphere interactions. The region is characterized by warm temperatures, high evaporation rates, and strong convection, making it particularly vulnerable to greenhouse gases. This susceptibility leads to an overall trend of warming across the Earth's surface and atmosphere, intensifying sea surface temperatures (SST) and increasing evaporation rates, consequently influencing Surface Latent Heat Flux (SLHF). The strong influence of both SST and SLHF on atmospheric circulation and precipitation patterns makes them critical factors in determining the region's climate, particularly in monsoon-dominated regions. Analysis reveals a consistent upward trend in both SST and SLHF in the central region of TIO. To model this, standard Logistic Curve Model (LCM) has been applied to these parameters averaged over the central region of the TIO. The model is run for a period of 20 years from 2001 to 2020, grouped into four lustrums. The LCM-derived SST and SLHF are in good consistent with observed datasets during the above periods with, correlation coefficients ranging from 0.92 to 0.96 for SST and 0.86–0.90 for SLHF. Extending the model spatially across the entire TIO region explains the ability to project fluctuations in SST and SLHF values across different seasons. These findings highlight the model's relevance for capturing short-term, long-term, and seasonal variability of the parameters, providing important insights into regional climate dynamics.

Revealing trends and persistent cycles of non-autonomous systems with autonomous operator-theoretic techniques

An important problem in modern applied science is to characterize the behavior of systems with complex internal dynamics subjected to external forcings. Many existing approaches rely on ensembles to generate information from the external forcings, making them unsuitable to study natural systems where only a single realization is observed. A prominent example is climate dynamics, where an objective identification of signals in the observational record attributable to natural variability and climate change is crucial for making climate projections for the coming decades. Here, we show that operator-theoretic techniques previously developed to identify slowly decorrelating observables of autonomous dynamical systems provide a powerful means for identifying nonlinear trends and persistent cycles of non-autonomous systems using data from a single trajectory of the system. We apply our framework to real-world examples from climate dynamics: Variability of sea surface temperature over the industrial era and the mid-Pleistocene transition of Quaternary glaciation cycles.

Competing impacts of tropical Pacific and Atlantic on Southern Ocean inter-decadal variability

The observed Southern Ocean sea surface temperature (SST) has experienced prominent inter-decadal variability nearly in phase with the Inter-decadal Pacific Oscillation (IPO), but less associated with the Atlantic Multidecadal Variability (AMV), challenging the prevailing view of Pacific-Atlantic synergistic effects. Yet, the mechanisms of distinct trans-hemispheric connections to the Southern Ocean remain indecisive. Here, by individually constraining the observed cold-polarity and warm-polarity IPO and AMV SSTs in a climate model, we show that the IPO is influential in initiating a basin-wide Southern Ocean response, with the AMV secondary. A tropical Pacific-wide cooling triggers a basin-scale Southern Ocean cold episode through a strong Rossby wave response to the north-to-south cross-equatorial weakened Hadley circulation. By contrast, due to the competing role of tropical Pacific cooling, an Atlantic warming partly cools the Southern Ocean via a weak Rossby wave response to the south-to-north cross-equatorial enhanced Hadley circulation. Conversely, tropical Pacific warming leads to a warm Southern Ocean episode. Our findings highlight that properly accounting for the tropical Pacific SST variability may provide a potential for skillful prediction of Southern Ocean climate change and more reliable estimates of climate sensitivity, currently overestimated by the misrepresented Southern Ocean warming.

Global Multiproxy ENSO Reconstruction Over the Past Millennium

AbstractEl Niño‐Southern Oscillation (ENSO) is the leading mode of interannual climate variability that affects climate and society across the world. However, our understanding of ENSO variability is currently lacking due to short instrumental observations, which limit our confidence in predicting its future occurrence and impact. In this study, we use the nested principal component regression method to reconstruct the ENSO index based on a global‐scale proxy network of stable oxygen isotopes (δ18O). We account for the teleconnection changes that influence proxy records corresponding to different ENSO phases by using the isotope‐enabled Community Earth System Model. According to the precipitation δ18O–ENSO relationship, we reconstruct the ENSO index over the last eight hundred years based on the first two leading modes of the selected proxy records. The skill of ENSO reconstruction improves with an increased number of δ18O series distributed over the ENSO‐affected regions. Our new reconstruction shows high consistency with existing ENSO reconstructions during periods of strong ENSO variability, indicating that the global proxy records capture enhanced teleconnection signals during the phase of strong ENSO amplitude. There is a weak El Niño response 1 year after the large volcanic eruptions in our reconstruction, and the amplitude of ENSO is significantly correlated with volcanic intensity. The strengthened energetic interactions between the ocean and atmosphere following large volcanic eruptions result in enhanced sea surface temperature variability.

Quantifying Downstream Climate Impacts of Sea Surface Temperature Patterns in the Eastern Tropical Pacific Using Clustering

El Niño–Southern Oscillation (ENSO) phases and flavors, as well as off-equatorial climate modes, strongly influence sea surface temperature (SST) patterns in the eastern tropical Pacific and downstream climate. Prior studies rely on EOFs (which characterize fractional SST variance) to diagnose climate-scale SST structures, limiting the ability to link individual ENSO flavors with downstream phenomena. Hierarchical and k-means clustering methods are used to construct Eastern Pacific patterns from the ERSST dataset spanning 1950 to 2021. Cluster analysis allows for the direct linkage of individual SST years/seasons to ENSO phase, providing insight into ENSO flavors and associated downstream impacts. In this study, four clusters are revealed, each depicting unique SST patterns influenced by ENSO and Pacific Meridional Mode (PMM) phases. A case study demonstrating the utility of the clusters was also carried out using accumulated cyclone energy (ACE) in the Atlantic and Eastern Pacific basins. Results showed that Eastern Pacific (EP) El Niño suppresses Atlantic tropical cyclone (TC) activity, while Central Pacific (CP) La Niña enhances it. Further, EP El Niño, coupled with positive PMM, amplifies ACE. Ultimately, the methods used herein offer a cleaner analysis tool for identifying dominant SSTA patterns and employing those patterns to diagnose downstream climatic effects.

The Impact of Interactive Ocean Dynamics on Atlantic Sea Surface Temperature Variability

Abstract The impact of interactive ocean dynamics on internal variations of Atlantic sea surface temperature (SST) is investigated by comparing preindustrial control simulations of a fully coupled atmosphere–ocean–ice model to the same atmosphere–ice model with the ocean replaced by a motionless slab layer (henceforth slab ocean model). Differences in SST variability between the two models are diagnosed by an optimization technique that finds components whose variance differs as much as possible. This technique reveals that Atlantic SST variability differs significantly between the two models. The two components with the most extreme enhancement of SST variance in the slab ocean model resemble the tripole SST pattern associated with the North Atlantic Oscillation (NAO) and the Atlantic multidecadal variability (AMV) pattern. This result supports previous claims that ocean dynamics are not necessary for the AMV, although ocean dynamics lead to slight increases in the memory of both the AMV and the NAO tripole. The component with the most extreme enhancement of SST variance in the fully coupled model resembles the Atlantic Niño pattern, confirming the ability of our technique to isolate physical modes known to require ocean dynamics. The second component with more variance in the fully coupled model is a mode of subpolar SST variability. Both the reemergence of SST anomalies and changes in ocean heat transport lead to increased SST variance and memory in the subpolar Atlantic. Despite large differences in the mean and variability of SST, atmospheric variability is quite similar between the two models, confirming that most atmospheric variability is generated by internal atmospheric dynamics.

Climatology and variability of sea surface temperature in the Azores region and its relation to climate indices

Daily sea surface temperature (SST) data from the Advanced Very High Resolution Radiometer from 1982 to 2020 were used to study the spatiotemporal variability and climatology of SST in the Azores. In addition, the relationships between the SST anomaly (SSTA) and three climate index time series for the period 1982–2020 were investigated: the Oceanic Niño Index (ONI), the Southern Oscillation Index (SOI) and the North Atlantic Oscillation (NAO) index. The spatiotemporal variability and climatology of the SST were studied by analyzing annual, seasonal, and monthly mean SST time series and climate fields. Relationships between the SSTA and climate index time series were investigated using Pearson's correlation analysis and wavelet coherence analysis. The annual mean SST time series shows a positive linear trend of about 0.027°C per year over the period 1982–2020. The spatial variability of the linear trend shows that the positive trend is consistent throughout the study area, ranging from 0.024 to 0.034°C per year. The spatial variability is not uniform, and high values of the trend are observed in the upper northwestern part and southwestern half of the basin. Seasonal mean SST fields show a positive North-South latitudinal gradient, with higher temperatures in the south, especially in the southwestern basin. In addition, the seasonal mean SST fields show possible coastal upwelling signatures along the coast of the Azores islands in different seasons. The results of Pearson's correlation analysis between basin-averaged, de-trended monthly mean SSTA and climate indices show that SSTA shows a significant positive correlation with SOI and a negative correlation with ONI from 1982 to 2020. NAO shows positive correlation with SSTA for the December-January-February season. Wavelet coherence analysis confirms significant coherences between the Azores SSTA and the climate-ocean indices at certain time scales and periods.

Winter “warm Arctic-cold Eurasia” pattern and its statistical linkages to oceanic precursors during the era of satellite observations

A striking recurrent feature of winter climate variability is the “warm Arctic-cold Eurasia” (WACE) pattern of opposite sign anomalies of surface air temperature (SAT) in the Barents Sea region and midlatitude Eurasia. Its origins and mechanisms are hotly debated, and its predictability remains unknown. This study investigates statistical relationships of the winter WACE dipole with concurrent anomalies of atmospheric circulation and oceanic precursors during the era of satellite observations. The results reveal a high potential for seasonal predictability of not only the WACE dipole but also several related indicators of winter climate variability, including the Arctic and Eurasian SAT anomalies. During subperiods of extreme covariability between the Arctic and Eurasian SATs around the early 1980s and late 2000s, most of the WACE variability is explained by ocean temperature and surface turbulent heat flux anomalies in the Barents Sea region during the preceding months. Anomalies in summer Atlantic water temperature (AWT) and autumnal sea surface temperature (SST) in this region explain about 70–80% of the variance of the following winter WACE variability during all events of strong Arctic-Eurasian SAT covariability. Analysis of SST variability in the Arctic-North Atlantic region suggests that the winter WACE link to the summer AWT anomalies reflects an atmospheric response to a large-scale surface reemergence of ocean temperature anomalies. However, this linkage had been robust only until the early 2000s. Since then, the winter WACE variability has been strongly related to autumnal SST anomalies in the Barents Sea region and the North Pacific.

Determining sea-level rise in the Caribbean: A shift from temperature to mass control

Tropical Small Island Developing States (SIDS), such as those in the Caribbean, are among the most vulnerable to the impacts of climate change, most notably sea-level rise. The current sea-level rise in the Caribbean is 3.40 ± 0.3 mm/year (1993–2019), which is similar to the 3.25 ± 0.4 mm/year global mean sea-level (GMSL) rise (1993–2018). Throughout the year, Caribbean seasonal sea-level variability is found to respond to sea surface temperature variability. Over the past few decades, the trend in Caribbean Sea-level rise is also found to be variable. Satellite altimetry and steric sea-level records of the Caribbean region reveal a shift in the late 2003-early 2004, which separates two distinct periods of sea-level rise. Thermal expansion dominates the sea-level trend from 1993–2003. Following this period, there is an increased trend in sea-level rise, with a dominance of mass changes from 2004–2019, as confirmed by GRACE data. During this period, the sea-level trend is 6.15 ± 0.5 mm/year, which is 67% faster than the most recent estimates of global mean sea-level rise provided by the Intergovernmental Panel on Climate Change (3.69 ± 0.5 mm/year for the period 2006–2018). Despite its reduced importance, increasing temperatures contribute greatly to sea-level rise in the Caribbean region through thermal expansion of ocean water, hence there is a need to limit the current trend of global warming.

Impacts of Atmospheric Internal Variations on the Variability of Sea Surface Temperature Based on the Hydra‐SINTEX Model

AbstractOcean–atmosphere interactions largely control the variabilities of the climate system on Earth. However, how much atmospheric internal signals contribute to climate variabilities remains uncertain over many parts of the globe. Here, we develop an interactive ensemble coupled model (called Hydra‐SINTEX) to investigate the influences of atmospheric internal variations (AIVs) on the mean‐states and variability of the climate system. The results show that, while climatological mean‐states are little affected, the AIVs can largely influence climate variabilities over the globe. We pay particular attention to two regions, that is, the tropical eastern Indian Ocean, which is the key area of the Indian Ocean Dipole (IOD), and the subtropical North Pacific. We found that sea surface temperature (SST) variabilities in these two regions are much reduced without the AIVs but with distinct mechanisms. Without the AIVs, the intensity of the IOD is largely reduced in association with weakened air–sea coupling in the tropics. This indicates the importance of atmospheric noise forcing on the development of the IOD. In contrast, the reduction of SST variability in the subtropical North Pacific is caused by the absence of the AIVs that are generated by both mid‐latitude atmospheric processes and weakened remote influence of the tropical SST in accordance with the reduced SST signals there.

On the Mechanisms Driving Latent Heat Flux Variations in the Northwest Tropical Atlantic

AbstractThe Northwest Tropical Atlantic (NWTA) is a region of complex surface ocean circulation. The most prominent feature is the North Brazil Current (NBC) and its retroflection at 8°N, which leads to the formation of numerous mesoscale eddies known as NBC rings. The NWTA also receives the outflow of the Amazon River, generating freshwater plumes that can extend up to 100,000 km2. We show that these two processes influence the spatial variability of the region's surface latent heat flux (LHF). On the one hand, the presence of surface freshwater modifies the vertical stratification of the ocean, the mixed layer heat budget, and thus the air‐sea heat exchanges. On the other hand, NBC rings create a highly heterogeneous mesoscale sea surface temperature (SST) field that directly influences the near‐surface atmospheric circulation. These effects are illustrated by observations from the ElUcidating the RolE of Cloud‐Circulation Coupling in ClimAte ‐ Ocean Atmosphere (EUREC4A‐OA) and Atlantic Tradewind Ocean‐Atmosphere Interaction Campaign (ATOMIC) experiments, satellite and reanalysis data. We decompose the LHF budget into several terms controlled by different atmospheric and oceanic processes to identify the mechanisms leading to LHF changes. We find LHF variations of up to 160 W m2, of which 100 W m2 are associated with wind speed changes and 40 W m2 with SST variations. Surface currents or heat release associated with stratification changes remain as second‐order contributions with LHF variations of less than 10 W m2 each. This study highlights the importance of considering these three components to properly characterize LHF variability at different spatial scales, although it is limited by the scarcity of collocated observations.

Tropical Warming and Intensification of the West African Monsoon During the Miocene Climatic Optimum

AbstractStudying monsoon dynamics during past warm time periods such as the Miocene Climatic Optimum (MCO; ∼16.9–14.5 Ma) could greatly aid in better projecting monsoon intensity, in the context of future greenhouse warming. However, studies on regional MCO temperature change and its effect on the monsoons during this time period are lacking. Here, we present the first high‐resolution, low‐latitude record of sea surface temperature (SST) and paleoceanographic change covering the Miocene Climatic Optimum, in the eastern equatorial Atlantic, at Ocean Drilling Program Site 959, based on TEX86 paleothermometry. SSTs were ∼1.5°C warmer at the onset of the MCO (16.9 Ma) relative to the pre‐MCO (∼18.3–17.7 Ma). This warming was accompanied by a transient increase in %total organic carbon. Prior to the MCO, sediment composition, geochemical proxy data as well as dinoflagellate cyst assemblages imply a productive surface ocean at Site 959. Immediately following the MCO onset (∼16.9–16.5 Ma), we record an intensification of the West African Monsoon (WAM) characterized by higher amplitude variability in all proxy records on precession to obliquity timescales. We interpret increased orbital‐scale SST, biogenic Ba and dinocyst assemblage variability to represent intensification of equatorial upwelling, forced by the WAM strength. Furthermore, higher SSTs during eccentricity maxima correlate to increased relative abundances of the warm and stratification‐favoring dinocyst Polysphaeridium zoharyi, during periods of low WAM intensity. Finally, while long‐term SSTs decline toward the middle Miocene, maximum SSTs and Polysphaeridium zoharyi abundances occur during MCO peak warming at ∼15.6 Ma.

Eastern Boundary Upwelling Systems in Ocean–Sea Ice Simulations Forced by CORE and JRA55-do: Mean State and Variability at the Surface

Abstract In this paper we summarize improvements in climate model simulation of eastern boundary upwelling systems (EBUS) when changing the forcing dataset from the Coordinated Ocean-Ice Reference Experiments (CORE; ∼2° winds) to the higher-resolution Japanese 55-year Atmospheric Reanalysis for driving ocean–sea ice models (JRA55-do, ∼0.5°) and also due to refining ocean grid spacing from 1° to 0.1°. The focus is on sea surface temperature (SST), a key variable for climate studies, and which is typically too warm in climate model representation of EBUS. The change in forcing leads to a better-defined atmospheric low-level coastal jet, leading to more equatorward ocean flow and coastal upwelling, both in turn acting to reduce SST over the upwelling regions off the west coast of North America, Peru, and Chile. The refinement of ocean resolution then leads to narrower and stronger alongshore ocean flow and coastal upwelling, and the emergence of strong across-shore temperature gradients not seen with the coarse ocean model. Off northwest Africa the SST bias mainly improves with ocean resolution but not with forcing, while in the Benguela, JRA55-do with high-resolution ocean leads to lower SST but a substantial bias relative to observations remains. Reasons for the Benguela bias are discussed in the context of companion regional ocean model simulations. Finally, we address to what extent improvements in mean state lead to changes to the monthly to interannual variability. It is found that large-scale SST variability in EBUS on monthly and longer time scales is largely governed by teleconnections from climate modes and less sensitive to model resolution and forcing than the mean state.

Multi-century flow reconstruction of the Lhasa River, China

Study regionLhasa River Basin Study focusMulti-century records are needed to characterize flow variability including the magnitude and frequency of occurrence of extreme events. Such long records are not available without integrating well-calibrated hydrological models and climate proxies. To test whether 50–70 years of observations represent the long-term flow variability for water resources management, daily flows (1472–2000) were reconstructed by integrating the Variable Infiltration Capacity (VIC) model with proxy-based precipitation and temperature data for Lhasa River. New hydrological insights for the regionVIC performed well during calibration and validation for 3 gauging stations with the Nash-Sutcliffe coefficient of efficiency (NSE) exceeding 0.52. Proxy-based precipitation, temperature, and reconstructed flow are broadly stationary over the past 529 years, while recent decades show detectable local trends. The inter-annual/decadal variability is aligned with long-term variations in sea surface temperatures and the intensity of south Asian summer monsoon. Moreover, higher long-term average, greater variabilities, and persistent periods of above/below-average flows are detected. The maximum daily flows with small annual recurrence intervals (ARIs) less than 60 years would be overestimated based on observations, and underestimated for ARIs > 60 years. It is the first time to have reconstructed long-term daily flows using hydrological models coupled with proxy-based climate data, and this approach offers invaluable insights into the pre-instrumental flow responses to changing climate conditions in Lhasa River basin.

Transformation of regional vegetation driven by climate change during the last deglacial–early Holocene at Chaohu Lake, eastern China: New pollen insights

Reconstructing the vegetation history of east China during the last glacial–interglacial transition is crucial for understanding the East Asian Summer Monsoon (EASM) evolution. Here, we present a new high-resolution pollen record from Chaohu Lake to determine the detailed process of regional lowland vegetation succession and its response to the EASM changes during the last glacial–Holocene transition (13.9–9.1 cal ka BP) in the lower Yangtze Valley, eastern China. During the Older Dryas (OD, 13.9–13.5 cal ka BP) period, regional forest-steppe indicative of co–dominance of Artemisia, Poaceae, and deciduous Quercus was present under a cool and dry climate. During the Allerød Interstadial (AI, 13.5–12.9 cal ka BP), significant arboreal expansions of deciduous Quercus, Hydrangea type and evergreen Quercus occurred, while herbs retreated significantly, presumably driven by the relatively warm, humid climate. Forest-steppe readvanced during the Younger Dryas (YD) interval, as indicated by increases in Poaceae and Artemisia, suggesting a cool and dry climate. During the early Holocene, extensive oak-pine forest flourished as regional vegetation, responding to pronounced climatic amelioration.Our pollen-based climatic record is closely correlated with stalagmites δ18O records from EASM region and Greenland ice cores δ18O records, indicating the teleconnection between EASM variation and North Atlantic climate during the last deglacial–early Holocene. However, our record indicates an intensified EASM during the early AI and a prolonged onset excursion during the YD, diverging from North Atlantic climate but closely correlated to sea surface temperature (SST) variations in the western tropical Pacific.

Interacciones tierra-mar-tierra, con énfasis en la actividad pesquera en la región norte del Ecosistema Costero Bonaerense, Argentina

[Introduction]: Coastal areas constitute the interface between land and marine environments, connected through multiple natural and socioecological processes that contribute to human well-being. [Objective]: Identify land and marine uses and activities with mutual implications and biophysical processes in the northern region of the Bonaerense Coastal Ecosystem (Argentina), in order to evaluate the degree of compatibility or conflict between these activities, with emphasis on the fishing activity. [Methodology]: The land-sea-land (T-M-T) methodological analysis was applied. Uses and activities (U&A) and biophysical processes of marine and land origin were determined. Interactions between marine-land and biophysical processes T-M-T were identified for further categorization and analysis. [Results]: A total of 121 U&A sea-land-sea (L-S-L) interactions related to fishing were detected. Medium conflicts were mainly caused by competition for space or resources and were associated with the coexistence of U&A (tourism, fishing, and communication activities), both spatially and temporally. Of the total, 68 negative interactions were observed between biophysical processes and U&A L-S-L, which were linked to climatic events and the effects of climate change (variation in sea surface temperature, atmospheric and oceanic circulation, as well as variations in sediment transport and coastal erosion). [Conclusions]: The analysis carried out constitutes an advancement in the study of U&A T-M-T in coastal-marine areas of the Atlantic coast and their interactions, with emphasis on fishing activities, as a contribution to their management with an ecosystemic approach.

Impact of volcanic eruptions on CMIP6 decadal predictions: a multi-model analysis

Abstract. In recent decades, three major volcanic eruptions of different intensity have occurred (Mount Agung in 1963, El Chichón in 1982 and Mount Pinatubo in 1991), with reported climate impacts on seasonal to decadal timescales that could have been potentially predicted with accurate and timely estimates of the associated stratospheric aerosol loads. The Decadal Climate Prediction Project component C (DCPP-C) includes a protocol to investigate the impact of volcanic aerosols on the climate experienced during the years that followed those eruptions through the use of decadal predictions. The interest of conducting this exercise with climate predictions is that, thanks to the initialisation, they start from the observed climate conditions at the time of the eruptions, which helps to disentangle the climatic changes due to the initial conditions and internal variability from the volcanic forcing. The protocol consists of repeating the retrospective predictions that are initialised just before the last three major volcanic eruptions but without the inclusion of their volcanic forcing, which are then compared with the baseline predictions to disentangle the simulated volcanic effects upon climate. We present the results from six Coupled Model Intercomparison Project Phase 6 (CMIP6) decadal prediction systems. These systems show strong agreement in predicting the well-known post-volcanic radiative effects following the three eruptions, which induce a long-lasting cooling in the ocean. Furthermore, the multi-model multi-eruption composite is consistent with previous work reporting an acceleration of the Northern Hemisphere polar vortex and the development of El Niño conditions the first year after the eruption, followed by a strengthening of the Atlantic Meridional Overturning Circulation the subsequent years. Our analysis reveals that all these dynamical responses are both model- and eruption-dependent. A novel aspect of this study is that we also assess whether the volcanic forcing improves the realism of the predictions. Comparing the predicted surface temperature anomalies in the two sets of hindcasts (with and without volcanic forcing) with observations we show that, overall, including the volcanic forcing results in better predictions. The volcanic forcing is found to be particularly relevant for reproducing the observed sea surface temperature (SST) variability in the North Atlantic Ocean following the 1991 eruption of Pinatubo.

The response to ENSO under global warming

This investigation explores the impact of global warming on the El Nio-Southern Oscillation (ENSO), a pivotal climatic phenomenon with far-reaching consequences for worldwide weather patterns and ecosystems. In the context of ongoing endeavors to mitigate climate change, comprehending ENSO's response assumes a position of utmost significance. Current research suggests that the amplitudes of ENSO events may intensify in response to elevated temperatures, linked to non-linear increments in atmospheric water vapor. Furthermore, careful analysis reveals an augmented variability in sea surface temperature (SST) fluctuations during the 21st century compared to prior periods. The research also sheds light on the concurrent existence and interactions of Eastern Pacific (EP) and Central Pacific (CP) ENSO variations in the context of a warming climate. Ongoing investigations are committed to unraveling the intricacies of these phenomena and their implications for future climatic patterns. Nevertheless, uncertainties persist regarding the drivers of CP-type ENSO and heightened amplitudes, with some attributing these changes to global warming while others associate them with multidecadal rhythms.

Auto- and Cross-Correlation Multifractal Analysis of Sea Surface Temperature Variability

In this study, we investigate multiscale auto- and cross-correlation structural characteristics of sea surface temperature (SST) variability using our new methodology, called the multifractal asymmetric cross-correlation analysis (MF-ACCA), incorporating signs of a segment’s detrended covariance and linear trend. SST is greatly affected by air–sea interactions and the advection of water masses with a wide range of spatiotemporal scales. Since these force factors are imprinted on SST variability, their features can be revealed in terms of long-range auto- and cross-correlation structures of SST variability via a multifractal analysis. By applying the MF-ACCA methodology to SST variability in the East/Japan Sea, we have found the following features: (1) the auto- and cross-correlation multifractal features are dependent on several parameters, such as the location, linear trends (rising or falling), level of fluctuations, and temporal scales; (2) there are crossover behaviors that are discrete for small scales (less than 1000 days) but continuous for large scales (more than 1000 days); (3) long-range persistence of auto- and cross-correlations is random for large scales during the falling phase; (4) long-range persistence is stronger during the rising phase than during the falling phase; (5) the degree of asymmetry is greater for large scales than for small scales.