Significant Sea Surface Temperature Research Articles

Equatorial Western–Central Pacific SST Responsible for the North Pacific Oscillation–ENSO Sequence

Abstract El Niño–Southern Oscillation (ENSO), the dominant mode of interannual variability in the tropical Pacific, is well known to affect the extratropical climate via atmospheric teleconnections. Extratropical atmospheric variability may in turn influence the occurrence of ENSO events. The winter North Pacific Oscillation (NPO), as the secondary dominant mode of atmospheric variability over the North Pacific, has been recognized as a potential precursor for ENSO development. This study demonstrates that the preexisting winter NPO signal is primarily excited by sea surface temperature (SST) anomalies in the equatorial western–central Pacific. During ENSO years with a preceding winter NPO signal, which accounts for approximately 60% of ENSO events observed in 1979–2021, significant SST anomalies emerge in the equatorial western–central Pacific in the preceding autumn and winter. The concurrent presence of local convection anomalies can act as a catalyst for NPO-like atmospheric circulation anomalies. In contrast, during other ENSO years, significant SST anomalies are not observed in the equatorial western–central Pacific during the preceding winter, and correspondingly, the NPO signal is absent. Ensemble simulations using an atmospheric general circulation model driven by observed SST anomalies in the tropical western–central Pacific can well reproduce the interannual variability of observed NPO. Therefore, an alternative explanation for the observed NPO–ENSO relationship is that the preceding winter NPO is a companion to ENSO development, driven by the precursory SST signal in the equatorial western–central Pacific. Our results suggest that the lagged relationship between ENSO and the NPO involves a tropical–extratropical two-way coupling rather than a purely stochastic forcing of the extratropical atmosphere on ENSO.

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.

Tropical ocean teleconnections with gross primary productivity of monsoon-Asia

The intricate oceanic climate interactions with terrestrial primary production of Asian ecosystems exert crucial social-economical-environmental repercussions. Yet, a holistic understanding of tropical sea surface temperature (SST) anomalies associated with the gross primary productivity (GPP) variations of monsoon-Asia remains constrained. This study provides a statistical framework demonstrating how SST perturbations in the tropics influence GPP fluctuations in monsoon-Asia by modulating hydrothermal conditions of different climate system components. Observation evidence explicitly illustrated the characteristic anomalous SST signatures of positive and negative GPP anomalies in South and Southeast Asia during June–August. The SST anomalies of the central-eastern tropical Pacific showed a robust negative impact on the GPP variability of South-Asia. The GPP alterations in maritime-Southeast-Asia exhibited strong connections with SST anomalies of the western Pacific (positive) and eastern equatorial Pacific (negative). The oceanic signals in the GPP variability of South-Asia and maritime-Southeast-Asia mirrored canonical El Niño and La Niña patterns. The detected SST–GPP link is feasible through large-scale atmospheric circulation variability and the consequent regional modulation of heat and moisture fluxes. The anomalous strengthening (weakening) of Walker cell enhance (reduce) water available to plants for photosynthesis during La Niña (El Niño) phase of ENSO cycle and thus elevate (lower) GPP in South-Asia and Maritime-southeast-Asia. In contrast, the enhanced GPP anomaly in mainland-Southeast-Asia depicts signs of canonical La Niña and Indian Ocean subtropical dipole (IOSD) teleconnections. The positive impact of IOSD was through the modulation of the Mascarene High and the consequent impact on monsoon. Meanwhile, decreased GPP bears the imprint of El Niño Modoki and warm tropical Indian Ocean SSTs. The atmospheric teleconnections demonstrated the delayed impact of El Niño Modoki on GPP variability through the Indian Ocean capacitor effect. Our findings could be instrumental in forecasting the probable effects on vegetation growth in monsoon-Asia associated with high-frequency tropical oceanic changes.

Impact of Intra‐Skeletal Calcite on the Preservation of Coral Geochemistry and Implications for Paleoclimate Reconstruction

AbstractThe geochemistry of tropical coral skeletons is widely used in paleoclimate reconstructions. However, sub‐aerially exposed corals may be affected by diagenesis, altering the aragonite skeleton through partial dissolution, or infilling of secondary minerals like calcite. We analyzed the impact of intra‐skeletal calcite on the geochemistry (δ18O, Sr/Ca, Mg/Ca, Li/Mg, Li/Ca, U/Ca, B/Ca, Ba/Ca, and Mn/Ca) of a sub‐aerially exposed Porites sp. coral. Each micro‐milled coral sample was split into two aliquots for geochemistry and X‐ray diffraction (XRD) analysis to quantify the direct impact of calcite on geochemistry. We modified the sample loading technique for XRD to detect low calcite levels (1%–2%; total uncertainty = 0.33%, 2σ) in small samples (∼7.5 mg). Calcite content ranged from 0% to 12.5%, with higher percentages coinciding with larger geochemical offsets. Sr/Ca, Li/Mg, Li/Ca, and δ18O‐derived sea‐surface temperature (SST) anomalies per 1% calcite were +0.43°C, +0.24°C, +0.11°C, and +0.008°C, respectively. A 3.6% calcite produces a Sr/Ca‐SST signal commensurate with local SST seasonality (∼1.5°C), which we propose as the cut‐off level for screening calcite diagenesis in paleo‐temperature reconstructions. Inclusion of intra‐skeletal calcite decreases B/Ca, Ba/Ca, and U/Ca values, and increases Mg/Ca values, and can therefore impact reconstructions of paleoclimate and the carbonate chemistry of the semi‐isolated calcifying fluid in corals. This study emphasizes the importance of quantifying fine‐scale calcite diagenesis to identify coral preservation levels and assure robust paleoclimate reconstructions.

Fingerprinting Mediterranean hurricanes using pre-event thermal drops in seawater temperature

Extreme atmospheric-marine events, known as medicanes (short for “Mediterranean hurricanes”), have affected the Mediterranean basin in recent years, resulting in extensive coastal flooding and storm surges, and have occasionally been responsible for several casualties. Considering that the development mechanism of these events is similar to tropical cyclones, it is plausible that these phenomena are strongly affected by sea surface temperatures (SSTs) during their development period (winter and autumn seasons). In this study, we compared satellite data and the numerical reanalysis of SSTs from 1969 to 2023 with in situ data from dataloggers installed at different depths off the coast of southeastern Sicily as well as from data available on Argo floats on the Mediterranean basin. A spectral analysis was performed using a continuous wavelet transform (CWT) for each SST time series to highlight the changes in SSTs prior to the occurrence of Mediterranean Hurricanes as well as the energy content of the various frequencies of the SST signal. The results revealed that decreases in SST occurred prior to the formation of each Mediterranean hurricane, and that this thermal drop phenomenon was not observed in intense extra-tropical systems. The spectral analyses revealed that high CWT coefficients representing high SST energy contents were observed before the occurrence of a Mediterranean hurricane. This information may provide a useful fingerprint for distinguishing Mediterranean hurricanes from common seasonal storms at the onset of these events.

Effects of interaction of multiple large-scale atmospheric circulations on precipitation dynamics in China

Different scenarios of precipitation, that lead to such phenomena as droughts and floods are influenced by concurrent multiple teleconnection factors. However, the multivariate relationship between precipitation indices and teleconnection factors, including large-scale atmospheric circulations and sea surface temperature signals in China, is rarely explored. Understanding this relationship is crucial for drought early warning systems and effective response strategies. In this study, we comprehensively investigated the combined effects of multiple large-scale atmospheric circulation patterns on precipitation changes in China. Specifically, Pearson correlation analysis and Partial Wavelet Coherence (PWC) were used to identify the primary teleconnection factors influencing precipitation dynamics. Furthermore, we used the cross-wavelet method to elucidate the temporal lag and periodic relationships between multiple teleconnection factors and their interactions. Finally, the multiple wavelet coherence analysis method was used to identify the dominant two-factor and three-factor combinations shaping precipitation dynamics. This analysis facilitated the quantification and determination of interaction types and influencing pathways of teleconnection factors on precipitation dynamics, respectively. The results showed that: (1) the Atlantic Multidecadal Oscillation (AMO), EI Niño-Southern Oscillation (ENSO), East Asia Summer Monsoon (EASM), and Indian Ocean Dipole (IOD) were dominant teleconnection factors influencing Standardized Precipitation Index (SPI) dynamics; (2) significant correlation and leading or lagging relationships at different timescales generally existed for various teleconnection factors, where AMO was mainly leading the other factors with positive correlation, while ENSO and Southern Oscillation (SO) were mainly lagging behind other factors with prolonged correlations; and (3) the interactions between teleconnection factors were quantified into three types: enhancing, independent and offsetting effects. Specifically, the enhancing effect of two-factor combinations was stronger than the offsetting effect, where AMO + NAO (North Atlantic Oscillation) and AMO + AO (Atlantic Oscillation) had a larger distribution area in southern China. Conversely, the offsetting effect of three-factor combinations was more significant than that of the two-factor combinations, which was mainly distributed in northeast and northwest regions of China. This study sheds new light on the mechanisms of modulation and pathways of influencing various large-scale factors on seasonal precipitation dynamics.

An attempt using equatorial waves to predict tropical sea surface temperature anomalies associated with the Atlantic zonal mode

IntroductionThe forecast for anomalous sea surface temperature (SST) events associated with Atlantic zonal mode, also known as Atlantic Niño/Niña, is full of challenge for both statistical and dynamical prediction models. MethodsThis study combines SST, wind and equatorial wave signal to construct a linear model, aiming to evaluate the potential of equatorial waves in extending the lead time of a skilful prediction for Atlantic Niño/Niña events. Wave-induced geopotential simulated by linear ocean models and potential energy flux calculated using a group-velocity-based wave energy flux scheme are involved to capture the signal of equatorial waves in the model establishment. ResultsThe constructed linear prediction model has demonstrated comparable prediction skill for the SST anomaly to the dynamical models of the North American Multimodel Ensemble (NMME) during the test period (1992-2016). Compared with the statistical forecast using SST persistence, the model notably improves the six-month-lead prediction (Anomaly correlation coefficient increases from 0.07 to 0.28), which owes to the conservation of wave energy in the narrow Atlantic basin that the Rossby waves reflected in the eastern boundary will transfer the energy back to the central equatorial basin and again affect the SST there. ConclusionThis study offers a streamlined model and a straightforward demonstration of leveraging wave energy transfer route for the prediction of Atlantic Niño/Niñas.

Impact of stratospheric variability on subseasonal temperature reversals during late winter over the mid-high latitudes of East Asia

Significant phase shifts in winter surface air temperature (SAT) anomalies have successively occurred in East Asia (EA) during recent years, leading to detrimental effects on socio-economic activities. In this study, we identify the fourth principal mode of month-to-month SAT variations over EA in winter (November–February) using the Season-reliant Empirical Orthogonal Function (S-EOF) analysis. The fourth S-EOF mode (S-EOF4) represents subseasonal SAT reversals over the mid-high latitudes of EA during late winter (January–February), with cold (warm) anomalies over Northeastern Asia in January and widespread warm (cold) anomalies over midlatitude EA in February. Results indicate that the cold-to-warm S-EOF4 is associated with a northward shift of the Siberian High in January and a quasi-barotropic low-pressure system over the Ural region in February. The formation of the S-EOF4 is accompanied by stratospheric temperature anomalies over eastern Siberia–Alaska in January. Stratospheric warming corresponds to cold-to-warm transitions over the mid-high latitudes of EA, and vice versa. Further investigation suggests that stratospheric warming would simultaneously lead to a weakened Arctic stratospheric polar vortex (SPV), which mainly stretches into Northern Eurasia and directly influences cold anomalies over Northeastern Asia in January. The delayed impact of stratospheric variability on the reversal of EA SAT anomalies is accomplished by an “ocean bridge” of the midlatitude North Atlantic sea surface temperature (SST) anomaly. The weakened SPV promotes anomalous westerly winds in the midlatitude North Atlantic and generates a significant SST cooling, which then regulates a cyclonic anomaly over the Ural region and results in warm anomalies over the midlatitude EA in February. The bridge role of the North Atlantic SST anomaly is well supported by a linear baroclinic model. In addition, the deepening of the Aleutian Low in December could significantly enhance the climatological wavenumber 1, serving as the tropospheric precursor of stratospheric warming. These findings contribute to an in-depth comprehension of EA subseasonal temperature variability, offering valuable insights for enhancing seasonal prediction strategies.

Future weakening of southeastern tropical Atlantic Ocean interannual sea surface temperature variability in a global climate model

AbstractFuture changes in the southeastern tropical Atlantic interannual sea surface temperature (SST) variability in response to increasing greenhouse gas concentrations are investigated utilizing the global climate model FOCI. In that model, the Coastal Angola Benguela Area (CABA) is among the regions of the tropical Atlantic that exhibits the largest surface warming. Under the worst-case scenario of the Shared Socioeconomic Pathway 5-8.5 (SSP5-8.5), the SST variability in the CABA decreases by about 19% in 2070–2099 relative to 1981–2010 during the model’s peak interannual variability season May–June–July (MJJ). The weakening of the MJJ interannual temperature variability spans the upper 40 m of the ocean along the Angolan and Namibian coasts. The reduction in variability appears to be related to a diminished surface-layer temperature response to thermocline-depth variations, i.e., a weaker thermocline feedback, which is linked to changes in the mean vertical temperature gradient. Despite improvements made by embedding a high-resolution nest in the ocean a significant SST bias remains, which might have implications for the results.

Impact of surface and subsurface-intensified eddies on sea surface temperature and chlorophyll a in the northern Indian Ocean utilizing deep learning

Abstract. Mesoscale eddies, including surface-intensified eddies (SEs) and subsurface-intensified eddies (SSEs), significantly influence phytoplankton distribution in the ocean. Nevertheless, due to the sparse in situ data, understanding of the characteristics of SSEs and their influence on chlorophyll a (Chl a) concentration is still unclear. Consequently, the study utilized a deep learning model to extract SEs and SSEs in the northern Indian Ocean (NIO) from 2000 to 2015, using satellite-derived sea surface height (SSH) and sea surface temperature (SST) data. The analysis revealed that SSEs accounted for 39 % of the total eddies in the NIO, and their SST signatures exhibited opposite behaviour compared to SEs. Furthermore, by integrating ocean colour remote-sensing data, the study investigated the contrasting impacts of SEs and SSEs on Chl a concentration in two basins of the NIO, the Arabian Sea (AS) and the Bay of Bengal (BoB), known for their disparate biological productivity. In the AS, SEs induced Chl a anomalies that were 2 to 3 times higher than those caused by SSEs. Notably, there were no significant differences in Chl a anomalies induced by the same type of eddies between summer and winter. In contrast, the BoB exhibited distinct seasonal variations, where SEs induced slightly higher Chl a anomalies than SSEs during the summer, while substantial differences were observed during the winter. Specifically, subsurface-intensified anticyclonic eddies (SSAEs) led to positive Chl a anomalies, contrasting the negative anomalies induced by surface-intensified anticyclonic eddies (SAEs) with comparable magnitudes. Moreover, while both subsurface-intensified cyclonic eddies (SSCEs) and surface-intensified cyclonic eddies (SCEs) resulted in positive Chl a anomalies during winter in the BoB, the magnitude of SSCEs was only one-third of that induced by SCEs. Besides, subsurface Chl a induced by SSAEs (SSCEs) is ∼0.1 mg m−3 greater (less) than that caused by SAEs (SCEs) in the upper 30 (50) m using Biogeochemical Argo profiles. The distinct Chl a between SEs and SSEs can be attributed to their contrasting subsurface structures revealed by Argo profiles. Compared to SAEs (SCEs), SSAEs (SSCEs) enhance (decrease) production via the convex (concave) of the isopycnals that occur around the mixed layer. The study provides a valuable approach to investigating subsurface eddies and contributes to a comprehensive understanding of their influence on chlorophyll concentration.

Atmospheric bias teleconnections in boreal winter associated with systematic sea surface temperature errors in the tropical Indian Ocean

Abstract. Coupled climate models suffer from significant sea surface temperature (SST) biases in the tropical Indian Ocean (TIO), leading to errors in global climate predictions. In this study, we investigate the local and remote effects of the TIO SST bias on the simulated atmospheric circulation and spatio-temporal variability – bias teleconnections. A set of century-long simulations forced by idealized SST perturbations, which resemble various (monopolar or dipolar, positive or negative) TIO SST biases in coupled climate models, are conducted with an intermediate-complexity atmospheric model. Bias teleconnections with a focus on boreal wintertime are analysed using the normal-mode function (NMF) decomposition, which can differentiate between balanced and unbalanced flows across spatial scales. The results show that the atmospheric circulation biases caused by the TIO SST bias have the Gill–Matsuno-type pattern in the tropics and Rossby-wave-train structure in the extratropics, similar to the steady-state response to tropical heating perturbations. The teleconnections between the tropical and extratropical biases are set up by Rossby wave activity flux emanating from the subtropics. Over 90 % of the bias variance (i.e. the square of the bias amplitude) is contained in zonal wavenumbers k≤5. The northward shift of the SST bias away from the Equator weakens the amplitude but does not change the spatial structure of the atmospheric response. Besides, the positive SST bias produces stronger bias teleconnections than the negative one of the same size and magnitude. In the NMF framework, the change in the spatial variance of the time-mean state (i.e. energy) is equal to the sum of the bias variance and the covariance between the circulation bias and the reference state (i.e. bias covariance). Due to the TIO SST biases, the global unbalanced zonal-mean (k=0) flow energy decreases, whereas its balanced counterpart increases. These changes primarily arise from the strong bias covariance. For k>0, both the global unbalanced and the tropical balanced energies increase in the case of a monopolar SST bias and decrease in the case of a dipolar SST bias. The increase appears mainly as the bias variance, whereas the decrease is associated with a strong negative bias covariance at k=1 and 2. In contrast, the extratropical balanced wave energy decreases (increases) when the TIO SST bias is positive (negative), which is mainly associated with the bias covariance at k=1. The change in the interannual variance (IAV) is contingent upon the sign of the TIO SST bias. A positive bias reduces, whereas a negative one increases, the IAV in both balanced and unbalanced flows. Geographically, large IAV changes are observed in the tropical Indo-West Pacific region, Australia, South and Northeast Asia, the Pacific-North America region, and Europe, where the background IAVs are strong.

Capturing episodic impacts of environmental signals

Environmental scientists frequently rely on time series of explanatory variables to explain their impact on an important response variable. However, sometimes, researchers are less interested in raw observations of an explanatory variable than in derived indices induced by episodes embedded in its time series. Often these episodes are intermittent, occur within a specific limited memory, persist for varying durations, at varying levels of intensity, and overlap important periods with respect to the response variable. We develop a generic, parametrised, family of weighted indices extracted from an environmental signal called IMPIT indices. To facilitate their construction and calibration, we develop a user-friendly app in Shiny R referred to as IMPIT−a. We construct examples of IMPIT indices extracted from the Southern Oscillation Index and sea surface temperature signals. We illustrate their applications to two fished species in Queensland waters (i.e., snapper and saucer scallop) and wheat yield in New South Wales.

The abnormal track of super typhoon Hinnamnor (2022) and its interaction with the upper ocean

The upper ocean response and feedback to super typhoon Hinnamnor (2022) were systematically investigated considering multi-satellite, Array for Real-time Geostrophic Oceanography (Argo) float and reanalysis data. Hinnamnor experienced three main stages: a rapid intensification (RI) stage with a high moving speed along a westward track, a rapid weakening (RW) stage with a low moving speed along a northward sudden-turning track and a re-intensification (Re-I) stage with a moderate speed along a northward track. At the westward straight-line stage, despite the thin warm water layer (D26 < 40 m) and shallow mixed layer depth (MLD) (<20 m), its fast movement (∼8.1 m/s) tended to generate weaker sea surface temperature (SST) cooling (approximately 1 °C) and shorter cooling exposure. Consequently, the negative feedback decreased (negative feedback factor FSST:approximately−0.47to−0.20), causing Hinnamnor's rapid intensification (25 knots/6 h). Although the MLD was deeper (approximately 30 m) and the warm water layer was thicker (approximately 60 m) at the sudden-turning stage, the low translation speed (<2 m/s) tended to generate stronger SST cooling (approximately 5.6 °C) and longer cooling exposure, both of which intensified the negative feedback (FSST:approximately−0.8to−0.4), causing Hinnamnor's rapid weakening (−22 knots/6 h). At the northward stage, Hinnamnor re-intensified under a weak warm eddy with a moderate moving speed (3.6–5.4 m/s). An intriguing leftward bias in SST cooling occurred due to the preexisting cold eddy (CE) on the left side of the track. Analysis of the Argo floats in the RI and RW regions showed that the enhanced upwelling and vertical mixing yielded more significant SST cooling in the CE region at the RW stage due to the CE and low translation speed (<2 m/s). The differences between the RI and RW regions were remarkable when using the Hybrid Coordinate Ocean Model (HYCOM) global ocean model output.

Influencing factors in the stagnation of the Baiu front that induced heavy rainfall in July 2020 over Kyushu, Japan

The influencing factors of the long-term stagnation of the Baiu front that induced heavy rainfall in July 2020 over Kyushu, Japan, were examined. In July 2020, the position of the Baiu front from a weather chart at 130° E remained stationary over Kyushu for 20 days, and that was the longest from 2002 to 2021. By examining a certain index of the Yellow Sea High (YSH), which is a necessary condition for Baiu front stagnation near Kyushu, it was confirmed that in 2020, a positive high-pressure anomaly persisted over the Yellow Sea until the end of July. The YSH maintenance was due to the significant negative sea surface temperature (SST) anomaly over the Yellow Sea. The significant negative SST anomalies in the Yellow Sea were due to vertical mixing in ocean mixed layer in response to the strong winds of the extratropical cyclones. A rapid SST decrease ranging from 0.5 to 1.5 °C/day was repeatedly occurred by ocean mixed layer deepening in association with the passage of the extratropical cyclones. The anomalous long-term stagnation of YSH due to the negative SST anomalies could have caused the Baiu front to remain stagnant over Kyushu until the end of July.

Air-sea flux and SST variability associated with atmospheric rivers in the southeast Indian Ocean

A previous study demonstrated that atmospheric rivers (ARs) generate substantial air-sea fluxes in the northeast Pacific. Since the southeast Indian Ocean is one of the active regions of ARs, similar air-sea fluxes could be produced. However, the spatial pattern of sea surface temperature (SST) in the southeast Indian Ocean, especially along the west coast of Australia, is different from that in the northeast Pacific because of the poleward flowing Leeuwin Current, which may cause different air-sea fluxes. This study investigates AR-associated air-sea fluxes in the southeast Indian Ocean and their relation with SST variability. The large-scale spatial pattern of latent heat flux (evaporation) associated with ARs in the southeast Indian Ocean is similar to that in the northeast Pacific. A significant difference is however found near the coastal area where relatively warm SSTs are maintained in all seasons. While AR-induced latent heat flux is close to zero around the west coast of North America where the equatorward flowing coastal current and upwelling generate relatively cold SSTs, a significant latent heat flux induced by ARs is evident along the west coast of Australia due to the relatively warm surface waters. Temporal variations of coastal air-sea fluxes associated with landfalling ARs are investigated based on the composite analysis. While the moisture advection reduces the latent heat during landfalling, the reduction of air humidity with strong winds enhances large evaporative cooling (latent heat flux) after a few days of the landfalling. A significant SST cooling along the coast is found due to the enhanced latent heat flux.

Warming trends of southwestern Atlantic SST and the summer's warmest SST's impact on South American climate

AbstractSeveral atmospheric variables are directly influenced by oceanic conditions, mainly the sea surface temperature (SST). SST trends and variability over the southwestern Atlantic (SWA) have affected the South American climate, principally the monsoonal period (austral summer). This study analysed the SST trends over the SWA for all seasons. In addition, possible large‐scale triggers of the austral summer's warmest SST over the SWA and the straight impacts of these warmest SSTs on the South American climate were investigated. The results showed a significant positive SST trend of approximately 0.02°C·year−1 over the SWA for all seasons. Since 2000, positive SST anomalies have increased in frequency in all seasons, with the seven warmest summers occurring during the 2010s. The highest SST summers over the SWA have been related to four leading causes: (i) planetary waves triggered by warm anomalies over the subtropical South Pacific; (ii) an omega‐type blocking configuration over the South Atlantic; (iii) a Southern Annular Mode positive phase; and (iv) a strengthening of the Hadley Cell, responding to warm SST over tropical North Atlantic. They all reflected on intensification of the South Atlantic Subtropical High and the western boundary current, heating the SWA. The summer's warmest SST led to positive air temperature anomalies extending in almost all of eastern South America, with significantly highest temperatures over southeastern Brazil, northern Argentina and western Paraguay. Clouds decrease strengthen the incident shortwave in southeastern Brazil, warming the region. Significant reduction of cloudiness and precipitation indicate a low performance of the South Atlantic Convergence Zone. The comparison of the warmest summers in 1980s–1990s in the SWA ratified the role of SST intensification. In conclusion, the positive SST trends over the SWA are related to the summer's warmest SST after 2000s, causing heating and dryness in eastern South America, mainly over southeastern Brazil.

Decadal changes in the relationship between Arctic stratospheric ozone and sea surface temperatures in the North Pacific

Using multi-source observations and ERA-Interim reanalysis data, this study found that the relationship between Arctic stratospheric ozone in March and North Pacific sea surface temperature (SST) in April shows dramatic decadal changes, and it significantly weakens since the 2000s. By enhancing the stratospheric circulations, a decreased Arctic stratospheric ozone favors tropospheric positive Arctic Oscillation (+AO)-like anomaly during PRE eras (1979–1999), with positive geopotential height (GH) anomalies over high-latitude Asia. The stratospheric ozone anomaly also favors the Asian positive GH anomalies via modulating high cloud and its related longwave radiation. According to geostrophic wind relationships, the Asian positive GH anomalies are accompanied by easterly anomalies over midlatitude Asia in late March, which further extend eastward and thereby induce easterly anomalies over the midlatitude North Pacific. The North Pacific easterly anomalies result in negative North Pacific Oscillation (–NPO)-like anomaly via vorticity forcing of zonal wind and the interactions between synoptic-scale eddies and mean flow, forcing significant SST anomalies. However, during POST eras (2000–2019), firstly, the +AO-related positive GH anomalies over high-latitude Asia are relatively weak, accompanied by weak easterly anomalies over midlatitude Asia according to geostrophic wind relations, which induce weak easterly anomalies over the North Pacific. Secondly, a westerly anomaly occurs over the midlatitude North Pacific, which partly offsets the easterly anomalies from Asia, weakening the North Pacific easterly anomalies. The weak easterly anomalies further induce weak –NPO and SST anomalies during the POST eras. Our analysis further indicates that the North Pacific westerly anomalies and weakening of the positive GH anomalies over high-latitude Asia associated with ozone are related to the interference of the westerly phase of quasi-biennial oscillation and the weakened stratospheric ozone anomaly over high-latitude Asia, respectively.

Western Mediterranean Precipitation Extremes, the Result of Quasi-Resonant Sea–Atmosphere Feedbacks

The Mediterranean region has been identified as a climate change hotspot, and 13 case studies of extreme rainfall events (EREs) make it possible to categorize convective systems according to whether they are tropical-like or extratropical cyclones. This study, which focuses on the western Mediterranean basin from 2000 to 2021, is based on the cross-wavelet analysis in the period range of 11.4 to 45.7 days of (1) the height of precipitation at a particular place representative of the deep convective system used as the temporal reference and (2) the amount of precipitation in the western Mediterranean basin, as well as the sea surface temperature (SST) in the Mediterranean, the Adriatic, the Aegean Sea, the Black Sea, the Baltic, the North Sea and the Atlantic Ocean. Extratropical cyclones result from quasi-resonant atmospheric water and SST feedbacks, reflecting the co-evolution of the clustering of lows and the harmonization of thermocline depths and a relative stability of the atmospheric blocking circulation. When the SST anomaly in the western Mediterranean is greater than 0.5 °C, in its paroxysmal phase, the deep convective system is centered both over the southeast of France and the Mediterranean off the French coast. However, when the SST anomaly is weaker, deep convective systems can develop in different patterns, depending on SST anomalies in the peripheral seas. They can produce a low-pressure system extending from the Pyrenees to southern Italy or Sicily when the SST anomaly in the western Mediterranean is in phase opposition with EREs. In some cases, partial clustering of Atlantic and Mediterranean low-pressure systems occurs, producing a large cyclonic system. Tropical-like cyclones develop in the absence of any significant SST anomalies. Like extratropical cyclones, they occur in autumn or even winter, when the thermal gradient between the sea surface and the upper atmosphere is greatest but, this way, non-resonantly. Their return period is around 2 to 3 years. However, due to the gradual increase in the SST of the western Mediterranean in summer resulting from global warming, they can now lead to an ERE as happened on 21 January 2020.

Response of the sea surface temperature to heatwaves during the France 2022 meteorological summer

Abstract. The summer of 2022 was memorable and record-breaking, ranking as the second hottest summer in France since 1900, with a seasonal surface air temperature average of 22.7 ∘C. In particular, France experienced multiple record-breaking heatwaves during the meteorological summer. As the main heat reservoir of the Earth system, the oceans are at the forefront of events of this magnitude which enhance oceanic disturbances such as marine heatwaves (MHWs). In this study, we investigate the sea surface temperature (SST) of French maritime basins using remotely sensed measurements to track the response of surface waters to the atmospheric heatwaves and determine the intensity of such feedback. Beyond the direct relationship between SSTs and surface air temperatures, we explore the leading atmospheric parameters affecting the upper-layer ocean heat budget. Despite some gaps in data availability, the SSTs measured during the meteorological summer of 2022 were record-breaking, the mean SST was between 1.3 and 2.6 ∘C above the long-term average (1982–2011), and the studied areas experienced between 4 and 22 d where the basin-averaged SSTs exceeded the maximum recorded basin-averaged SSTs from 1982 to 2011. We found a significant SST response during heatwave periods with maximum temperatures measured locally at 30.8 ∘C in the north-western Mediterranean Sea. Our results show that in August 2022 (31 July to 13 August), France experienced above-average surface solar radiation correlated with below-average total cloud cover and negative wind speed anomalies. Our attribution analysis based on a simplified mixed-layer heat budget highlights the critical role of ocean–atmosphere fluxes in initiating abnormally warm SSTs, while ocean mixing plays a crucial role in the cessation of such periods. We find that the 2 m temperatures and specific humidity that are consistently linked to the advection of warm and moist air masses are key variables across all the studied regions. Our results reveal that the influence of wind on heatwaves is variable and of secondary importance. Moreover, we observe that the incident solar radiation has a significant effect only on the Bay of Biscay (BB) and the English Channel (EC) areas. Our study findings are consistent with previous research and demonstrate the vulnerability of the Mediterranean Sea to the increasing frequency of extreme weather events resulting from climate change. Furthermore, our investigation reveals that the recurring heatwave episodes during the summer of 2022 had an undeniable impact on all the surveyed maritime areas in France. Our study therefore provides valuable insights into the complex mechanisms underlying the ocean–atmosphere interaction and demonstrates the need for an efficient and sustainable operational system combining polar-orbiting and geostationary satellites to monitor the alterations that threaten the oceans in the context of climate change.

Trend of annual and semiannual harmonics of sea surface temperature in the tropical Indian Ocean, 1979–2018

In the Indian Ocean (IO), the annual and semiannual oscillations of the sea surface temperature (SST) contribute more than 80% of the total variance. It is known that the SST in the tropical IO has warmed at a rate of 0.15 °C/decade since 1979. However, such an estimate of the decadal trend of the annual and semiannual harmonics of SST remains unknown, despite being a strong component of the SST signal. Here we use a widely accepted data product (TropFlux) to quantify the annual and semiannual harmonics in the tropical IO for the first time. The northern IO has a distinctly strong semiannual cycle (1–1.8 °C), which is showing an amplifying trend (∼ 0.04 °C/decade) since 1979. Furthermore, a damping trend in annual amplitude exists over much of the IO, except along the northwestern Bay of Bengal, the Seychelles-Chagos thermocline ridge, the Persian Gulf, and the Indonesian throughflow region. The estimated damping of the annual amplitude is highest over the Arabian Sea. In contrast, the southern tropical IO has a predominant annual cycle, the amplitude of which has weakened during 1979–2018. In the north IO, net air-sea heat flux and vertical processes show a dominant semiannual harmonic oscillation similar to SST. Additionally, the annual amplitude is influential over southern IO. Horizontal advection contributes significantly along the boundary-current regions and the western equatorial IO. Our analysis of combined annual and semiannual cycles shows significant warming in the tropical IO during October–November and cooling during July–August owing to the amplification of semiannual oscillation. These changes in the SST can influence air-sea interaction processes such as cyclogenesis and monsoon.