Sea Surface Temperature Anomalies Research Articles

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.

Indian Ocean temperature anomalies predict long-term global dengue trends

Despite identifying El Niño events as a factor in dengue dynamics, predicting the oscillation of global dengue epidemics remains challenging. Here, we investigate climate indicators and worldwide dengue incidence from 1990 to 2019 using climate-driven mechanistic models. We identify a distinct indicator, the Indian Ocean basin-wide (IOBW) index, as representing the regional average of sea surface temperature anomalies in the tropical Indian Ocean. IOBW is closely associated with dengue epidemics for both the Northern and Southern hemispheres. The ability of IOBW to predict dengue incidence likely arises as a result of its effect on local temperature anomalies through teleconnections. These findings indicate that the IOBW index can potentially enhance the lead time for dengue forecasts, leading to better-planned and more impactful outbreak responses.

The Role of the Subtropical and Extratropical Southern Hemisphere Anomalous Sea Surface Temperature in the Trans‐Seasonal Influence of Southern Annular Mode on Rainfall Over Southeastern South America

AbstractThe current study explores the linkage and possible mechanisms of the Southern Annular Mode (SAM) with rainfall variability over southeastern South America (SESA). The findings indicate that the preceding May SAM can modulate the subsequent rainfall over the SESA region in September‐October‐November (SON), independent of the El Niño‐Southern Oscillation (ENSO) signal. Further analysis suggests that the SAM‐rainfall relationship is mainly due to the response of sea surface temperature (SST) in the subtropical and extratropical Southern Hemisphere to SAM variability via air‐sea interactions. Such SST anomalies persist to the subsequent SON and stimulate an upstream wave train extending into the study region from the South Pacific. Such wave patterns form a cyclone anomaly over SESA, indicating strong subsidence and reduced convection over the region. Meanwhile, the low‐level anomalous cyclone and anticyclone located over the subtropical South Atlantic (on the coast of the study region) are associated with easterly winds to the South (North) of the anomalous cyclone (anticyclone), which advect colder and drier air into the study region due to the cold SST over the subtropical South Atlantic and leading to increased moisture scarcity and decreased rainfall over SESA. Besides, model results based on the joint climate indices (i.e., SAM, ENSO and Indian Ocean Dipole (IOD)) revealed a satisfactory estimate of the SON rainfall compared with either single index, indicating that the SAM can be one of the precursors of the SESA rainfall, besides ENSO and IOD.

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

AbstractA 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.

Downscaling the ocean response to the Madden–Julian Oscillation in the Northwest Atlantic and adjacent shelf seas

AbstractSubseasonal-to-seasonal (S2S) prediction is a global effort to forecast the state of the atmosphere and ocean with lead times between two weeks and a season. This study explores the feasibility of S2S prediction of the ocean using a variety of tools including statistical analysis, a statistical-dynamical mixed layer model, and a regional, high-resolution ocean circulation model based on physical principles. Ocean predictability on S2S timescales is analyzed by compositing winter sea surface temperature (SST) anomalies in the North Atlantic with respect to the state of the Madden–Julian Oscillation (MJO). It is found that statistically significant, large-scale SST changes, particularly along the eastern seaboard of North America, can be related to the MJO. This signal is shown to be driven by anomalous air–sea heat fluxes caused by atmospheric perturbations in response to the MJO. The high-resolution model of the Gulf of Maine and Scotian Shelf is used to downscale the mean ocean response to the MJO. The model is able to capture the observed relationship between the MJO and SST in the northwest Atlantic. It is also shown that the anomalous atmospheric circulation in response to the MJO leads to anomalous upwelling on the Scotian Shelf. Overall, this study demonstrates that it is feasible, and of value, to use regional ocean models for S2S prediction.

Spatial distribution models for the four commercial tuna in the sea of maritime continent using multi-sensor remote sensing and maximum entropy

The dynamic of marine environmental parameters affects the distribution of commercial tuna in the sea of the maritime continent. Hence, the objectives of this study are to develop spatial distribution models for the four main tuna species in the Maritime continent's sea with reasonable accuracy, identify their correlation with marine environmental parameters, and investigate areas of interaction between those tuna species. The study develops the distribution models for albacore (Thunnus alalunga), bigeye (Thunnus obesus), yellowfin (Thunnus albacares), and skipjack (Katsuwonus pelamis) tuna species, utilizing multi-sensor satellite remote sensing and maximum entropy. The results show models have good performance, focusing on environmental factors such as sea surface temperature (SST), chlorophyll-a (CHL), and sea surface height anomalies (SSHA), combined with eddy kinetic energy (EKE). Seasonal variations in potential tuna habitats are revealed, emphasizing the influence of those marine environmental conditions. From December to May, the four commercial tuna species were distributed in conditions characterized by SST of 26–31.5 °C, CHL levels of 0–3 mg/l, SSHA of −0.3 to 0.2 m, and EKE of 0–1 m2/s2, while from June to November, they experienced SST of 23–31 °C, CHL levels of 0–4 mg/l, SSHA of −0.5 to 0.3 m, and EKE of 0–1.1 m2/s2. The spatial persistence of the four tuna species emerged mainly around the south sea of Java, with skipjack being the most common species found in the sea of the maritime continent. With sufficient and evenly distributed tuna presence records, the results indicate the potential for extrapolation beyond the training data to estimate habitat suitability for the four commercial tuna distributions. The results also suggest potential competition between tuna species sharing ecological niches and highlight possible overlapping areas where different tuna species interact with the same fishing gear.

Joint influence of the North Atlantic sea surface temperature and the Barents sea-ice concentration on the dipole pattern of Eurasian surface air temperature in March

In recent decades, an increase in the frequency of extreme events in early spring across Eurasia has resulted in significant impacts on crop yields and socio-economic development. However, the variations of March surface air temperature (SAT) over Eurasia and mechanisms are still unclear. This study aims to investigate the dominant mode of the March surface air temperature (SAT) over Eurasia during 1979–2022, and its relationship with sea surface temperature (SST) and sea ice concentration (SIC). The results reveal the prevalence of a dipole mode of the Eurasian SAT anomalies (SATAs) in March characterized by positive SATAs in northern (50°N–80°N) Eurasia and negative ones in southern (10°N–45°N) region. Further analyses demonstrate that this dipole mode of Eurasian SATAs shows significant relationships with a positive phase of the North Atlantic tripole SST anomalies (NAT SSTAs), as well as with the decline of Barents Sea SIC anomalies (SICAs). Associated with the NAT SSTAs and the Barents Sea SICAs during March, two Rossby wave trains propagate towards Eurasia through different ways, one is propagating eastwards from the mid-latitude of the North Atlantic to Eurasia, and another one spreads from the polar region to Eurasia. Modulated by these two wave trains, anomalous near-surface southwesterly (northeasterly) wind induces more (less) warm air towards northern Eurasia, while more (less) cloud emerges in southern Eurasia and causes less (more) solar radiation reaching southern Eurasia, leading to the dipole mode of the Eurasian SATAs in March. These results are further confirmed by numerical experiments from the version 5 of the Community Atmosphere Model forced by the above mentioned SSTAs and SICAs.

Asian-Australian monsoon as a mediator on North American surface air temperature anomalies

The Asian-Australian monsoon (AAM) significantly shapes global weather and climate patterns, yet existing research has primarily focused on regional monsoon subsystems rather than adopting a comprehensive global perspective on the AAM. This study addresses this gap by elucidating the interannual variability of the AAM during boreal summer and underscoring the pivotal mediating role of AAM precipitation anomalies as a driving force behind surface air temperature anomalies (SATA) over central and southern North America (CSNA). To investigate AAM characteristics, we employ an empirical orthogonal function analysis to identify the primary mode of the AAM. The corresponding principal component serves as a representative measure for the AAM. Our findings reveal a distinct ‘wet (dry) Maritime Continent-dry (wet) Western North Pacific (WNP)’ dipole pattern in strong (weak) AAM years. Vertical motion anomalies emerge as the dominant contributors to these precipitation anomalies. Both observed data and model results indicate that the sea surface temperature anomalies (SSTA) in the central and eastern Pacific (CEP) play a crucial role in explaining the vertical motion anomalies. This explanation is facilitated through two key systems: the east–west Walker circulation-like anomaly and the anomalous equatorially symmetric anticyclonic pair in the Pacific. AAM precipitation anomalies act as a mediator between SSTA in the CEP and SATA over the CSNA. These generate Rossby wave source over the WNP, triggering Rossby waves that propagate to CSNA along a great circle path. This process results in upper-level positive geopotential height anomalies, thereby influencing SATA positively over the CSNA, as illustrated by the linear baroclinic model. These findings not only deepen our understanding of the AAM but also offer novel insights into the mechanisms influencing SATA formation over North America.

Interannual synchronization of the North American summer monsoon and the North Atlantic tropical cyclone genesis frequency

Variations of the North American summer monsoon (NASM) and North Atlantic tropical cyclone (NATC) activities strongly influence climate anomalies in North America, with serious potential risk to life and property. Despite the scientific importance of this topic, the possible linkage between the NASM and the NATC genesis frequency remains unexplored. Here, we aim to examine the relationship between interannual variations of the NASM intensity and the NATC genesis frequency based on observations and Coupled Model Intercomparison Project Phase 6 (CMIP6) models. Our results show a strong association between the NASM intensity and the NATC genesis frequency during the extended boreal summer, with a good synchronization between their interannual variations. In years with stronger (weaker) NASM intensity, the NATC genesis frequency tends to be higher (lower). The observed NASM–NATC synchronization may be explained by two pathways: tropical-ocean-driven pathway and monsoon-heating-driven pathway. In the tropical-ocean-driven pathway, the tropical Pacific and Atlantic interbasin sea surface temperature (SST) anomalies play a critical role in bridging the NASM and NATC, by modulating the cross-Central American wind. Simulations of the tropical Pacific–Atlantic interbasin SST anomalies are critical for CMIP6 models to capture the observed linkage between the NASM and the vertical wind shear over the NATC main development region (MDR). In the monsoon-heating-driven pathway, the heating source due to the rainfall anomalies associated with the NASM can trigger atmospheric circulation anomalies through the Gill-type response, thereby affecting the NATC by changing the vertical wind shear over the MDR. This study demonstrates a connection between interannual variations of the NASM and the NATC genesis frequency, results of which can be used to advance our understanding of the monsoon–TC relationship and increase research focus on the interannual NASM–NATC synchronization in climate prediction.

Weakened western Indian Ocean dominance on Antarctic sea ice variability in a changing climate.

Patterns of sea surface temperature (SST) anomalies of the Indian Ocean Dipole (IOD) exhibit strong diversity, ranging from being dominated by the western tropical Indian Ocean (WTIO) to the eastern tropical Indian Ocean (ETIO). Whether and how the different types of IOD variability patterns affect the variability of Antarctic sea ice is not known, nor is how the impact may change in a warming climate. Here, we find that the leading mode of austral spring Antarctic sea ice variability is dominated by WTIO SST variability rather than ETIO SST or El Niño-Southern Oscillation. WTIO warm SST anomalies excite a poleward-propagating Rossby wave, inducing a tri-polar anomaly pattern characterized by a decrease in sea ice near the Amundsen Sea but an increase in regions on both sides. Such impact has been weakening in the two decades post-2000, accompanied by weakened WTIO SST variability. Under greenhouse warming, climate models project a decrease in WTIO SST variability, suggesting that the reduced impact on Antarctic sea ice from the IOD will likely to continue, facilitating a fast decline of Antarctic sea ice.

The Dynamics of ENSO Phase Locking in a Spatiotemporal Oscillator Model

Abstract The ENSO phase locking to the annual cycle is investigated by applying a spatiotemporal oscillator (STO) model, in which the annual cycle of the climatological thermocline depth and its associated parameter are introduced. It is easy to derive its analytic solution, which demonstrates a harmonic oscillation of a combined variable. The ENSO phase locking can be theoretically proven by discussing the distribution of the calendar months of the peak time of the sea surface temperature anomaly (SSTA) time series. The calendar months of the peak time can be divided into two parts. The first part can evenly distribute in any a month of a year and hence has no phase locking feature whereas the second part, directly associated with the annual cycle, adds an increment onto the first part to make it move toward the phase of the annual cycle to realize the phase locking feature. This is the physical mechanism of the ENSO phase locking. With observed seasonal variation of the climatological thermocline depth, the Niño-3.4 index time series approach to extreme values in November was calculated with higher probability, reproducing the observed phase locking phenomenon quite well. The maximum probability of the calendar month that the ENSO peak time occurs is directly determined by the phase of the annual cycle and the stronger the annual cycle is, the larger the maximum probability is. Significance Statement El Niño–Southern Oscillation (ENSO) events tend to be strongest in the boreal wintertime. This phenomenon is called ENSO phase locking. This study investigates the dynamics of ENSO phase locking to the annual cycle by introducing the annual cycle to a spatiotemporal oscillator (STO) model that can deal with the complex spatial and temporal variations in SSTAs. The analytic solution can be obtained and then the phase locking feature can be theoretically proven and numerically testified. Therefore, the dynamics and the mechanism of ENSO phase locking can be comprehensively understood. It may be beneficial for the community to have a better understanding of this complex phenomenon.

Origins of Biweekly Sea Surface Temperature Variability in the Eastern Equatorial Pacific and Atlantic

AbstractBiweekly sea surface temperature (SST) variability significantly contributes to over 50% of the intraseasonal variability in the eastern equatorial Pacific (EEP) and Atlantic (EEA). Our study investigates this biweekly variability, employing a blend of in–situ and reanalysis data sets. The research identifies biweekly signals in SST, meridional wind, and ocean currents, notably in September–November in EEP and June–August in EEA. Biweekly southerly (northerly) winds drive instantaneous northward (southward) ocean currents in EEP, but with a 1–2‐day phase delay in EEA. Consequently, these currents lead to SST anomalies with a 3–4‐day lag in both EEP and EEA due to the presence of the cold tongue. The study reveals the origin of biweekly wind fluctuations in the western Pacific for EEP and the subpolar Pacific for EEA, connected by atmospheric Rossby waves validated through a linearized non‐divergent barotropic model. This research affirms the influence of subtropical and subpolar atmospheric forcing on equatorial SST.

Distinguishing Impacts on Winter Temperatures in Northern Mid-to-High Latitude Continents during Multi-year and Single-year La Niña Events: A Modeling Study

Abstract Utilizing a 2200-year CESM1 pre-industrial simulation, this study examines the influence of property distinctions between single-year (SY) and multi-year (MY) La Niñas on their respective impacts on winter surface air temperatures across mid-to-high latitude continents in the model, focusing on specific teleconnection mechanisms. Distinct impacts were identified in four continent sectors: North America, Europe, Western Siberia (W-Siberia), and Eastern Siberia (E-Siberia). The typical impacts of simulated SY La Niña events are featured with anomalous warming over Europe and W&E-Siberia and anomalous cooling over North America. Simulated MY La Niña events reduce the typical anomalous cooling over North America and the typical anomalous warming over W&E-Siberia but intensify the typical anomalous warming over Europe. The distinct impacts of simulated MY La Niñas are more prominent during their first winter than during the second winter, except over W-Siberia, where the distinct impact is more pronounced during the second winter. These overall distinct impacts in the CESM1 simulation can be attributed to the varying sensitivities of these continent sectors to the differences between MY and SY La Niñas in their intensity, location, and induced sea surface temperature anomalies in the Atlantic Ocean. These property differences were linked to the distinct climate impacts through the Pacific North America, North Atlantic Oscillation, Indian Ocean-induced wave train, and Tropical North Atlantic-induced wave train mechanisms. The modeling results are then validated against observations from 1900 to 2022 to identify disparities in the CESM1 simulation.

Slow response of surface water temperature to fast atmospheric variability reveals mixing heterogeneity in a deep lake

Slow and long-term variations of sea surface temperature anomalies have been interpreted as a red-noise response of the ocean surface mixed layer to fast and random atmospheric perturbations. How fast the atmospheric noise is damped depends on the mixed layer depth. In this work we apply this theory to determine the relevant spatial and temporal scales of surface layer thermal inertia in lakes. We fit a first order auto-regressive model to the satellite-derived Lake Surface Water Temperature (LSWT) anomalies in Lake Garda, Italy. The fit provides a time scale, from which we determine the mixed layer depth. The obtained result shows a clear spatial pattern resembling the morphological features of the lake, with larger values (7.18± 0.3 m) in the deeper northwestern basin, and smaller values (3.18 ± 0.24 m) in the southern shallower basin. Such variations are confirmed by in-situ measurements in three monitoring points in the lake and connect to the first Empirical Orthogonal Function of satellite-derived LSWT and chlorophyll-a concentration. Evidence from our case study open a new perspective for interpreting lake-atmosphere interactions and confirm that remotely sensed variables, typically associated with properties of the surface layers, also carry information on the relevant spatial and temporal scales of mixed-layer processes.

Influence of Eastern, Central and Mix El Niño on the variability of rainfall in southeastern South America

El Niño/Southern Oscillation (ENSO) plays a very important role in modulating rainfall variability in South America. Although the effects of conventional ENSO are well known, there are significant variations in rainfall patterns when sea surface temperature anomalies manifest over the different regions along the equatorial Pacific, namely, Niño 3 (East), Niño 3 and Niño 4 (Mix), and Niño 4 (Central) ENSO. This work aims to analyze the variability of precipitation in southeastern South America associated with different types of El Niño (EN). For this, composite analyzes of precipitation, winds at low and high levels, vertical velocity and geopotential height were carried out. The results indicate that the rainfall pattern associated with Eastern Pacific (EP) El Niño shows the classic features expected from EN described in previous literature, i.e., a stronger and well-defined positive precipitation anomaly over southeast South America, while Central Pacific (CP) El Niño shows weaker and even an opposite sign over the region. Mix (MX) El Niño events present a spatial pattern of precipitation anomalies similar to EP El Niño events, but with lower intensity in the study area. The heterogeneity of EN-related precipitation effects results from a change in large-scale atmospheric circulation patterns: the Walker cell in the tropics, the Rossby waves in the extratropics, and the circulation of low and high-level jet streams. EP El Niño events feature a configuration similar to the South American Low-Level Jet, the strengthening of the subtropical jet, better structured Rossby waves and the Pacific-South America pattern. These characteristics are observed in MX El Niños, but in a weaker way compared to EP El Niños. CP El Niño events, on the other hand, present a weakening and spatial displacement of the aforementioned conditions, which is reflected in negative precipitation anomalies in most seasons. Thus, more significant rainfall variations are noted between the EP El Niños and CP El Niños, with a predominance of positive and negative rainfall anomalies in the study area, respectively.

Seasonal influence of tropical Pacific and Atlantic sea surface temperature on streamflow variability in the patia river basin

AbstractThis research presents a seasonal analysis of the variability of streamflows in the Patía River Basin (PRB) between 1984 and 2018 and the influence exerted by the large-scale climate variability using non-linear principal component analysis (NLPCA), Pearson's correlation, and composite analysis. The study was conduced during the minimum (July–August–September, JAS) and maximum (October–November–December, OND) streamflow periods. The NLPCA depicted a single significant mode of variability for each season with explained variances greater than 75%. The correlation analysis between the main mode of variability during OND and climate indices showed significant results, mainly with the Pacific Ocean and El Niño-Southern Oscillation (ENSO). In contrast, for JAS, the correlations were significant for the indices linked to the Atlantic Ocean. Finally, the composite analysis indicated that the positive (negative) events during JAS, which show the increase (decrease) of streamflow in PRB, are related to negative (positive) anomalies in the Tropical Northern Atlantic band, including the Caribbean Sea and the Gulf of Mexico. In comparison, the positive (negative) events during OND are related to negative (positive) sea surface temperature (SST) anomalies in the tropical Pacific, corresponding to La Niña (El Niño) events. The results provide evidence of the strong influence of climate indices and tropical Pacific and Atlantic SST on seasonal streamflow in the PRB and establish the foundations for seasonal streamflow modelling, relevant for prevention and risk management as well as for adequate planning and management of water resources in the region.

Dominant contribution of atmospheric nonlinearities to ENSO asymmetry and extreme El Niño events

Extreme El Niño events have outsized impacts and strongly contribute to the El Niño Southern Oscillation (ENSO) warm/cold phase asymmetries. There is currently no consensus on the respective importance of oceanic and atmospheric nonlinearities for those asymmetries. Here, we use atmospheric and oceanic general circulation models that reproduce ENSO asymmetries well to quantify the atmospheric nonlinearities contribution. The linear and nonlinear components of the wind stress response to Sea Surface Temperature (SST) anomalies are isolated using ensemble atmospheric experiments, and used to force oceanic experiments. The wind stress-SST nonlinearity is dominated by the deep atmospheric convective response to SST. This wind-stress nonlinearity contributes to ~ 40% of the peak amplitude of extreme El Niño events and ~ 55% of the prolonged eastern Pacific warming they generate until the following summer. This large contribution arises because nonlinearities consistently drive equatorial westerly anomalies, while the larger linear component is made less efficient by easterly anomalies in the western Pacific during fall and winter. Overall, wind-stress nonlinearities fully account for the eastern Pacific positive ENSO skewness. Our findings underscore the pivotal role of atmospheric nonlinearities in shaping extreme El Niño events and, more generally, ENSO asymmetry.

The new record of drought and warmth in the Amazon in 2023 related to regional and global climatic features

In 2023 Amazonia experienced both historical drought and warm conditions. On October 26th 2023 the water levels at the port of Manaus reached its lowest record since 1902 (12.70 m). In this region, October monthly maximum and minimum temperature anomalies also surpassed previous record values registered in 2015 (+ 3 °C above the normal considering the 1981–2020 average). Here we show that this historical dry and warm situation in Amazonia is associated with two main atmospheric mechanisms: (i) the November 2022–February 2023 southern anomaly of vertical integrated moisture flux (VIMF), related to VIMF divergence and extreme rainfall deficit over southwestern Amazonia, and (ii) the June–August 2023 downward motion over northern Amazonia related to extreme rainfall deficit and warm conditions over this region. Anomalies of both atmospheric mechanisms reached record values during this event. The first mechanism is significantly correlated to negative sea surface temperature (SST) anomalies in the equatorial Pacific (November–February La Niña events). The second mechanism is significantly correlated to positive SST anomalies in the equatorial Pacific, related to the impacts of June–September El Niño on the Walker Circulation. While previous extreme droughts were linked to El Niño (warmer North Tropical Atlantic SST) during the austral summer (winter and spring), the transition from La Niña 2022–23 to El Niño 2023 appears to be a key climatic driver in this record-breaking dry and warm situation, combined to a widespread anomalous warming over the worldwide ocean.

Predicting Summer Precipitation Anomalies in the Yunnan–Guizhou Plateau Using Spring Sea-Surface Temperature Anomalies

By constructing a correlation network between global sea surface temperature anomalies (SSTAs) and summer precipitation anomalies in the Yunnan–Guizhou Plateau, key SST regions influencing summer precipitation anomalies in the Yunnan–Guizhou Plateau were selected. It was found that spring SSTAs in the Bay of Bengal, southwestern Atlantic, and eastern Pacific are crucial for influencing summer precipitation anomalies in the Yunnan–Guizhou Plateau. Setting SSTAs from these three regions as predictor variables 3 months in advance, we constructed multiple linear regression (MLR), ridge regression (RR), and lasso regression (LR) models to predict summer precipitation anomalies over the Yunnan–Guizhou region. The training phase involved data spanning from 1961 to 2005, which aimed to predict precipitation anomalies in the Yunnan–Guizhou Plateau for the period extending from 2006 to 2022. Based on MLR, RR, and LR models, the correlations between predicted values and observed summer precipitation anomalies in Yunnan–Guizhou were 0.48, 0.46, and 0.46, respectively. These values were all higher than the correlation coefficients of the NCC_CSM model’s predicted and observed values. Additionally, its performance in predicting summer precipitation anomalies over the Yunnan–Guizhou region, based on key SST regions, was assessed using performance metrics such as anomaly correlation coefficient (ACC), anomaly sign consistency rate (PC), and trend anomaly comprehensive score (PS score). The average ACC of MLR, RR, and LR models was higher than that of the NCC_CSM model’s predictions. For MLR, RR, LR, and NCC_CSM models, the PCs exceeding 50% of the year were 14, 14, 11, and 10, respectively. Furthermore, the average PS score for predicting summer precipitation anomalies over the Yunnan–Guizhou region using MLR, RR, and LR was approximately 73 points; 8 higher than the average PS score of the NCC_CSM model. Therefore, predicting summer precipitation anomalies over the Yunnan–Guizhou region based on key SST regions is of great significance for improving the prediction skills of precipitation anomalies in this region.

Widespread Coral Bleaching and Mass Mortality of Reef-Building Corals in Southern Mexican Pacific Reefs Due to 2023 El Niño Warming

In May 2023, oceanic and atmospheric anomalies indicated El Niño conditions in the eastern Pacific, followed by coral bleaching in coral communities and reefs of Huatulco. We conducted surveys and sampled coral reef communities from late June to mid–August of 2023 to evaluate the intensity and extent of the changes associated with the warming event. From January of 2023, Huatulco experienced positive sea surface temperature (SST) anomalies; however, beginning in June, the high-temperature anomalies became extreme (>31 °C; ~2 °C above historical records). These high temperatures resulted in extensive coral bleaching in middle–late June and mortality from middle–late July (>50–93%). In addition, the area experienced significant reductions in echinoderm abundance and fish biomass. In 2023, severe bleaching affected coral systems in the Central Mexican Pacific, Gulf of Mexico, and Mexican Caribbean, making this the most devastating marine heatwave event, simultaneously impacting coral reefs across Mexico’s Pacific and Atlantic coasts.