Regional Sea Surface Temperature Research Articles

Climate-driven shifts in decapod larvae assemblages in a temperate estuary

The study examines the complex impact of climatic patterns, driven by the North Atlantic Oscillation (NAO), on regional climate, hydrology, and sea surface temperatures. Focused on the period from 2003 to 2012, the research specifically investigates the influence of thermal variability on decapod larval communities. Monthly zooplanktonic sampling conducted at the Mondego Estuary, Portugal, entrance over a decade revealed the prevalence of Carcinus maenas, Diogenes pugilator, and Pachigrapsus marmoratus larvae. These assemblages displayed notable interannual and seasonal fluctuations, often corresponding with changes in sea surface temperatures. Significant system shifts around 2007, instigated by the large-scale NAO, led to subsequent modifications in sea surface temperature and decapod larvae communities' dynamics. Post-2007, there was an upward trajectory in both species’ abundance and richness. Phenologically during the former period, the community exhibited two abundance peaks, with the earlier peak occurring sooner, attributed to heightened temperatures instead of the unique peak exhibited before 2007. The research further elucidated the occurrences of Marine Heatwaves (MHW) in the region, delving into their temporal progression influenced by the NAO. Although water temperature emerged as a crucial factor influencing decapod larvae communities annually and seasonally, the study did not observe discernible impacts of MHW events on these communities. These communities represent essential trophic links and are crucial for the survival success of adult decapods. Given the rapid pace of climate change and increasing temperatures, it is imperative to assess whether these environmental shifts, particularly in thermal conditions, affect these meroplanktonic communities.

Heat waves in Poland: The relations to atmospheric circulation and Arctic warming

AbstractFrom the beginning of the 21st century, the heat waves in Europe have become more frequent, severe and longer lasting, especially in the southern region. The longer duration of heat waves may be partly attributed to wave‐amplification, high‐amplitude waves in the mid‐latitudes, favouring the longer‐lasting blocking systems. The primary objective of the paper was to examine the long‐term changes of hot days and heat wave events and to identify the atmospheric circulation condition that prevails its occurrence. The other object was to investigate the correlations between hot days' occurrence in Poland and sea‐ice cover and sea surface temperature changes in the Arctic and its surroundings. Over the past few decades, Central and Southern Poland have experienced a considerable rise in maximum temperatures, which has led to an increase in the number of hot days. This increase is particularly prominent during the summer months (June, July and August) but also in May and September, which extends the hot season. Although heat waves have become more frequent and persistent since 2006, their mean intensity has remained unchanged. During all heat waves in Poland, the high‐pressure centre was located over the country or its close neighbourhood, mainly in the eastern sector but also in the south, southwest or over Scandinavia. The blocking systems were mainly related to the extended ridge of the Azores High, but also to strong blocking over the North Pole and Greenland reaching Scandinavia or anomalous high pressure in the East Arctic. The longest‐lasting heat waves were usually preceded by air masses advection from the Atlantic, but the highest potential temperature along the trajectories was observed for the southern direction of inflow. The growing number of hot days is statistically significantly related to the decreasing sea‐ice cover and increasing sea surface temperature in Arctic and Subarctic regions.

Impact of atmospheric forcing on SST biases in the LETKF-based ocean research analysis (LORA)

In the previous study, the authors have produced an eddy-resolving ocean ensemble analysis product called the local ensemble transform Kalman filter (LETKF)-based ocean research analysis (LORA) over the western North Pacific and Maritime Continent regions using an ocean data assimilation system driven by the Japanese operational atmospheric reanalysis dataset known as the JRA-55. However, the LORA includes warm biases in sea surface temperatures (SSTs) in coastal regions during the boreal winter. In this study, we perform sensitivity experiments with atmospheric forcing using an ocean forcing dataset known as the JRA55-do, which adjusts the JRA-55 to high-quality reference datasets to reduce biases and uncertainties. The results show that the nearshore warm SST biases are significantly improved by the JRA55-do. During the boreal autumn, the improvement comes from mainly two factors: (i) enhancement of surface cooling by latent heat releases caused by removing contamination of weak winds at the land grid cells, and (ii) weakening surface heating by downward shortwave radiation through the adjustment in the JRA55-do.During the boreal winter, enhanced cooling by the analysis increments suppresses the growth of the warm SST biases when the JRA55-do is used. However, if the JRA-55 dataset is used, the adaptive observation error inflation (AOEI) scheme acts negatively to keep the nearshore SST biases in winter. Based on the innovation statistics, the AOEI inflates the observation errors when the differences between the squared observation-minus-forecast innovations and the squared forecast ensemble spreads are larger than the prescribed observation error variance, and improves the accuracy in the open ocean, especially around the frontal regions. However, when substantial warm SST biases are formed in the previous season, AOEI's observation error inflation makes the analysis increments smaller and cannot suppress the warm biases.We also validate the analysis accuracy using various data such as sea surface height and horizontal velocities and find that the JRA55-do has significant advantages. Therefore, continuous maintenance and development of ocean forcing datasets are essential for ocean modeling and data assimilation.

Relative prevalence of top-down versus bottom-up control in planktonic ecosystem under eutrophication and climate change: A comparative study of typical bay and estuary

Eutrophication and climate change may affect the top-down versus bottom-up controls in aquatic ecosystems. However, the relative prevalence of the two controls in planktonic ecosystems along the eutrophication and climate gradients has rarely been addressed. Here, using the field surveys of 17 years in a typical bay and estuary, we test two opposite patterns of trophic control dominance and their response to regional temporal eutrophication and climate fluctuations. It was found that trophic control of planktonic ecosystems fluctuated between the dominance of top-down and bottom-up controls on time scales in both the bay and estuary studied. The relative prevalence of these two controls in both ecosystems was significantly driven directly by regional dissolved inorganic nitrogen but, for the estuary, also by the nonlinear effects of regional sea surface temperature. In terms of indirect pathways, community relationships (synchrony and grazing pressure) in the bay are driven by both regional dissolved inorganic nitrogen - soluble reactive phosphorus ratio and sea surface temperature, but this drive did not continue to be transmitted to the trophic control. Conversely, trophic control in estuary was directly related to grazing pressure and indirectly related to synchrony. These findings support the view that eutrophication and climate drive the relative prevalence of top-down versus bottom-up controls at ecosystem and temporal scales in planktonic ecosystems, which has important implications for predicting the potential impacts of anthropogenic and environmental perturbations on the structure and function of marine ecosystems.

Responses of Lower Stratospheric water vapor to Regional Sea Surface Temperature Changes

Abstract The variability of stratospheric water vapor (SWV) plays a crucial role in stratospheric chemistry and the Earth's energy budget, strongly influenced by sea surface temperature (SST). In this study, we systematically investigate the response of low stratospheric water vapor (LSWV) to regional sea surface temperature changes using idealized SST patch experiments within a climate model. The results indicate that LSWV is most sensitive to tropical sea surface temperature, with the strongest response occurring in late autumn and early winter. Warming of the tropical Indian Ocean and western Pacific leads to stratospheric drying, while warming of the tropical Atlantic and eastern Pacific results in stratospheric moistening. The drying impact on LSWV due to warming in the western Pacific Ocean exceeds the wet effect in the Eastern Pacific Ocean by approximately 60%. The variations in tropical SST influence LSWV by modulating the temperature at the tropical tropopause layer especially over the Indo-Pacific Warm Pool through Matsuno-Gill responses. Furthermore, the response of LSWV to tropical SST changes exhibits nonnegligible nonlinearity, which indicates the importance of nonlinearity in determining the LSWV response to global surface warming.

Dansgaard-Oeschger cycles of the penultimate and last glacial period recorded in stalagmites from Türkiye

The last glacial period is characterized by abrupt climate oscillations, also known as Dansgaard-Oeschger (D-O) cycles. However, D-O cycles remain poorly documented in climate proxy records covering the penultimate glacial period. Here we present highly resolved and precisely dated speleothem time series from Sofular Cave in northern Türkiye to provide clear evidence for D-O cycles during Marine Isotope Stage (MIS) 6 as well as MIS 2-4. D-O cycles are most clearly expressed in the Sofular carbon isotope time series, which correlate inversely with regional sea surface temperature (SST) records from the Black Sea. The pacing of D-O cycles is almost twice as long during MIS 6 compared to MIS 2-4, and could be related to a weaker Atlantic Meridional Overturning Circulation (AMOC) and a different mean climate during MIS 6 compared to MIS 2-4, leading most likely to a higher threshold for the occurrence of D-O cycles.

20th Century Warming in the Western Florida Keys Was Dominated by Increasing Winter Temperatures

AbstractLong‐lived Atlantic coral species like Orbicella faveolata are important archives of oceanographic change in shallow, marine environments like the Florida Keys. Not only can coral‐based records extend for multiple centuries beyond the limits of the instrumental record, but they can also provide a more accurate representation of in situ conditions than gridded interpolated sea‐surface temperature (SST) products for nearshore reef environments. We use the coral Sr/Ca paleothermometer to produce a 150‐year (1830–1980 C.E.) monthly SST reconstruction from an O. faveolata colony collected in the Marquesas Keys, FL, USA. An important feature of our record is a significant 20th‐century warming trend in winter SSTs. We hypothesize that the winter warming trend was driven partially by a decrease in upwelling associated cyclonic eddies spinning off the Florida Current. A long‐term weakening of winter Florida Current transport over the 20th century could be responsible for decreased cyclonic eddy formation in the Florida Straits. Another feature of the record is pronounced multidecadal fluctuations of mean annual warming and cooling in the record, which correspond to Atlantic Multidecadal Variability (AMV), with the AMV lagging behind western Florida Keys temperatures by 5–11 years. Strong coherence between coral‐based SST reconstructions in the western Florida Keys with broader scale Atlantic oceanographic trends over the past century suggests a common driver of regional SST variability.

Impacts of projected changes in sea surface temperature on ozone pollution in China toward carbon neutrality

The global sea surface temperatures (SSTs) are expected to change diversely in the future under different climate scenarios, which will affect the near-surface ozone (O3) distribution and concentration by influencing meteorological states and large-scale atmospheric circulation. Many countries have planned to reach carbon neutrality by the mid-21st century. In this study, the impacts of global and regional SST changes on near-surface O3 concentrations in China in the middle of the 21st century under the carbon-neutral scenario (Shared Socioeconomic Pathway 1–1.9), compared with the high-emission scenario (Shared Socioeconomic Pathway 5–8.5), and possible physical and chemical mechanisms are investigated using the Community Earth System Model version 1 (CESM1). Under future climate change, the changes in SSTs in the carbon-neutral scenario relative to the high-emission scenario lead to a dipole change in near-surface O3 concentrations in eastern and western China, with a significant decrease of 0.79 ppbv in the eastern China and a significant increase of 1.05 ppbv in the western China. The cooling of North Pacific Ocean under the carbon-neutral scenario causes a decrease in near-surface O3 concentrations by 0.48 ppbv in eastern China due to the weakened chemical production and an increase by 0.74 ppbv in western China attributed to the enhanced O3 transport from Eurasia. Cooling of Southern Hemisphere oceans leads to anomalous upward air motions over eastern China, which weaken the vertical transport of high-elevation O3 to the surface, resulting in a reduction in near-surface O3 concentrations by 0.58 ppbv in eastern China. Our results suggest that future changes in SSTs in the carbon-neutral scenario will positively benefit O3 air quality improvement in the polluted eastern China, with the North Pacific and Southern Hemisphere oceans playing important roles.

Environmental drivers of persistent humpback whale Megaptera novaeangliae feeding events in a Mexican breeding area

Humpback whales Megaptera novaeangliae typically fast for several months in low-latitude breeding areas. Here we report on persistent feeding events during 5 wintering seasons between 2013 and 2020 in a known upwelling region of Banderas Bay of the mainland Mexico breeding area. In total, there were 76 unique feeding events documented (group size = 1 to ~100 individuals), involving 201 photo-identified whales, of which 18 were documented feeding in multiple years. The most prolific years of documented feeding in 2017 and 2018 (based on number of reports/individuals photo-identified feeding) followed the strongest marine heatwave ever recorded in the North Pacific. Whales documented feeding in Banderas Bay had significantly shorter mean sighting histories (2.3 yr) than a non-feeding sample (8.7 yr) and were reported to be of small size, suggesting they were predominantly younger whales. Most high-latitude recaptures of Banderas Bay feeding whales were in more northern North Pacific feeding grounds (50.8% were resighted in Russia, Alaska, and northern British Colombia, Canada). A binomial general linear model revealed a significant relationship between the probability of whales feeding in Banderas Bay and sea surface temperature (SST). Specifically, feeding consistently occurred in years of lower than average winter SST (<25°C), associated with La Niña years of the El Niño Southern Oscillation (ENSO). We conclude that feeding of humpback whales is now a predictable occurrence in the upwelling region of Banderas Bay in years that ENSO fluctuations lead to lower regional SST. The magnitude of several years of low-latitude feeding events reported here was likely influenced by climate change induced marine heatwaves that occurred during the study period.

Comparative analysis of spatiotemporal trends in sea surface temperature in the major marine protected areas of the Eastern Tropical Pacific

The Eastern Tropical Pacific (ETP) is characterized by complex oceanographic dynamics that affect the regional sea surface temperature (SST), a key parameter driving marine ecosystems. To date no comparative studies have been conducted on the spatial and temporal variations of SST among the several marine protected areas in the ETP. The present study used remote sensing to evaluate the monthly, annual, and decadal variations in SST from 1982 to 2019 in Coiba National Park (Coiba), Cocos Island National Park (Cocos), Malpelo Fauna and Flora Sanctuary (Malpelo), Gorgona Island National Park (Gorgona), Galápagos Marine Reserve (Galápagos) and La Plata Island (La Plata). An overall increasing trend in SST was observed across all study sites, except for West Galápagos. A decrease in SST anomaly was observed from February through April at Malpelo, Coiba, Gorgona and La Plata. These observations are likely in response to the Humboldt Current and upwelling events in the Colombian Pacific Basin. Using a longer SST dataset is recommended to determine if the annual, monthly and decadal trends observed here are driven by local, regional or global processes. Consistent monitoring of SST trends is a strategic practice in understanding and planning for current and projected changes in the marine environment.

Improving Predictions of Tibetan Plateau Summer Precipitation Using a Sea Surface Temperature Analog-Based Correction Method

Boreal summer precipitation over the Tibetan Plateau (TP) is difficult to predict in current climate models and has become a challenging issue. To address this issue, a new analog-based correction method has been developed. Our analysis reveals a substantial correlation between the prediction errors of TP summer precipitation (TPSP) and previous February anomalies of sea surface temperature (SST) in the key regions of tropical oceans. Consequently, these SST anomalies can be selected as effective predictors for correcting prediction errors. With remote-sensing-based and observational datasets employed as benchmarks, the new method was validated using the rolling-independent validation method for the period 1992–2018. The results clearly demonstrate that the new SST analog-based correction method of dynamical models can evidently improve prediction skills of summer precipitation in most TP regions. In comparison to the original model predictions, the method exhibits higher skills in terms of temporal and spatial skill scores. This study offers a valuable tool for effectively improving the TPSP prediction in dynamical models.

The Gulf Stream Front Amplifies Large-Scale SST Feedback to the Atmosphere in North Atlantic Winter

The Gulf Stream (GS) ocean front releases intense moisture and heat to the atmosphere and regulates storm tracks and zonal jets in winter. The large-scale sea surface temperature (SST) anomaly in the central North Atlantic provides important feedback to the atmosphere in winter, but the role played in this feedback by the GS front inside the SST anomaly has not been extensively studied. In this study, two sets of ensemble experiments were conducted using a global community atmosphere model forced by SST in boreal winters from 2000 to 2013. The regional averaged SST and its variation in the experiments were identical, with the only difference being the strength of the SST front in the GS region. The large-scale SST anomaly in the central North Atlantic in our model provides feedback to the atmosphere and excites a wave train that extends across Eurasia. With the inclusion of the strong GS front, the first center of the wave train in the North Atlantic is strengthened by approximately 40%, and the wave activity flux toward downstream is highly intensified. When the large-scale SST anomaly is combined with a strong GS front, greatly increased water vapor is released from the GS region, resulting in a 50% increase in moisture transport toward Western Europe. In this scenario, precipitation and diabatic heating both increase greatly on the western Scandinavian Peninsula. With the release of deep diabatic heating, a strong upward wave activity flux is triggered, and the wave train excited by the large-scale SST variation is significantly intensified. These findings suggest that the strong SST front in the large-scale SST anomaly in the central North Atlantic significantly amplifies its feedback to the atmosphere in winter.

Variability of the Indonesian Throughflow and Australian monsoon across the mid Pleistocene transition (IODP 363, Site U1483)

The Mid-Pleistocene Transition (MPT) between ∼1200 and ∼800 ka was associated with a major shift in global climate and was marked by a change in glacial/interglacial periodicity from ∼41 to ∼100 kyr that resulted in higher-amplitude sea-level variations and intensified glacial cooling. The sensitivity of the Indonesian Throughflow (ITF), and the Asian-Australian Monsoon dynamics to changing MPT climate remains controversial, although its understanding is important to constrain future climate projections. In this study, we analyzed radiolarian assemblages in core top samples retrieved during the RV Sonne Expedition 257 and in downcore samples from International Ocean Discovery Program (IODP) Site U1483 to estimate the variability in regional sea surface temperatures (SSTs), and to explore ITF dynamics in relation to glacio-eustatic sea-level variations and tropical monsoon strength during the MPT. Our results suggest that tropical monsoon strength and glacio-eustatic sea-level change influenced SST variations at Site U1483. Comparisons with SST data from the mid latitudes off Northwest Australia and the South China Sea suggest that SST variations at Site U1483 and in the ITF outflow into the Timor Sea are highly dependent on prevailing climate changes in the source region of the ITF, rather than on southern hemisphere. atmospheric circulation. In addition, comparisons of radiolarian abundances with X-ray fluorescence-scanning elemental data indicate that until ∼980 ka radiolarian productivity was higher during strong interglacial summer monsoons, likely because of the riverine runoff generated by monsoonal precipitation. However, at ∼980 ka pronounced winter monsoon cooling was associated with a re-organization of radiolarian production patterns in the Timor Sea.

Effect of global and regional SST biases on the East Asian Summer Monsoon in the MetUM GA7 and GC3 configurations

Climate-length experiments of the Met Office Unified Model Global Atmosphere 7.0 (GA7) and Global Coupled 3.0 (GC3) configurations are evaluated against observations and reanalyses for the simulation of the East Asian summer monsoon (EASM). The results show systematic model biases, such as overestimated rainfall over southern China and underestimated rainfall over northern China, suggesting a monsoon that does not penetrate northward enough. We evaluate the effects on the EASM of regional errors in sea-surface temperature (SST) conditions in three regions: the Pacific, the Indian, and the Atlantic Oceans. The global SST biases in GC3 configuration substantially shift the EASM seasonal cycle: a late northward progression of the EASM in the early/mid-monsoon season, and an early retreat of the monsoon that also reduces rainfall over most of northern China. The EASM seasonal rainfall bias in the EASM region is linked to changes in the locations and strength of the western North Pacific subtropical high, which is associated with biases in local evaporation and moisture transport towards South China. GC3 biases in the El Niño-Southern Oscillation (ENSO) and the Indian Ocean Dipole (IOD) teleconnection pathways also influence the EASM biases. GC3 biases weaken the ENSO teleconnection to the EASM and cause a strong dry bias in southeast China during developing El Niño.

Separating internal and forced contributions to near term SST predictability in the CESM2-LE

An open question in the study of climate prediction is whether internal variability will continue to contribute to prediction skill in the coming decades, or whether predictable signals will be overwhelmed by rising temperatures driven by anthropogenic forcing. We design a neural network that is interpretable such that its predictions can be decomposed to examine the relative contributions of external forcing and internal variability to future regional sea surface temperature (SST) trend predictions in the near-term climate (2020–2050). We show that there is additional prediction skill to be garnered from internal variability in the Community Earth System Model version 2 Large Ensemble, even in a relatively high forcing future scenario. This predictability is especially apparent in the North Atlantic, North Pacific and Tropical Pacific Oceans as well as in the Southern Ocean. We further investigate how prediction skill covaries across the ocean and find three regions with distinct coherent prediction skill driven by internal variability. SST trend predictability is found to be associated with consistent patterns of decadal variability for the grid points within each region.

Relationship between the North Atlantic sea surface temperature and the summer extreme high temperature in the Beijing-Tianjin-Hebei region, China

Climate change influence on the economy and environment in the Beijing–Tianjin–Hebei (BTH) region. This study examined the variations of extreme high temperature days (EHDs) over the BTH region in summer during 1982 to 2021. The trend and frequency of EHDs has increased significantly during the last 40 years. The spatial and temporal variations of EHDs also indicate a significant increase by using the rotated empirical orthogonal functions (REOF) method. Furthermore, the singular value decomposition (SVD) method and correlation analysis are used to indicate the relationship between the EHDs in June–July-August (JJA) in the BTH region and North Atlantic sea surface temperature anomalies (SSTA) in the March–April-May (MAM) during 1982–2021. The result shows that there was positive relationship between the North Atlantic SSTA in MAM and the EHDs in JJA in the BTH region. Composite analysis suggests that relationship between EHDs and SSTA are connected by associated atmospheric circulation through the wave activity flux.

Wind variability across the North Humboldt Upwelling System

Surface wind is taken as the primary driver of upwelling in the eastern boundary upwelling systems. The fluctuation of momentum flux associated with the variation in wind regulates the nutrient supply to the euphotic surface layer via changing the properties of oceanic mixed layer depth, the coastal and offshore upwelling, and horizontal advection. Here, the spatial and temporal variability of the surface wind field over the last seven decades across the Peruvian upwelling system is investigated. Strong fluctuations in seasonal to decadal timescales are found over the entire upwelling system. A semi-periodic wind fluctuation on an interannual timescale is found, which is closely related to the regional sea surface temperature and can be attributed to the El Niño Southern Oscillation (ENSO). However, the wind anomaly patterns during positive and negative phases of ENSO are not opposite, which suggests an asymmetric response of local wind to ENSO cycles. In addition, a semi-regular fluctuation on the decadal timescale is evident in the wind field, which can be attributed to the Interdecadal Pacific Oscillation (IPO). Our results show that the sea surface temperature over the Humboldt Upwelling System is closely connected to local wind stress and the wind stress curl. The SST wind stress co-variability seems more pronounced in the coastal upwelling cells, in which equatorward winds are very likely accompanied by robust cooling over the coastal zones. Over the past seven decades, wind speed underwent a slightly positive trend. However, the spatial pattern of the trend features considerable heterogeneity with larger values near the coastal upwelling cells.

On dynamical downscaling of ENSO-induced oceanic anomalies off Baja California Peninsula, Mexico: role of the air-sea heat flux

The El Niño Southern Oscillation (ENSO) phenomenon is responsible for important physical and biogeochemical anomalies in the Northeastern Pacific Ocean. The event of 1997-98 has been one of the most intense in the last decades and it had large implications for the waters off Baja California (BC) Peninsula with a pronounced warm sea surface temperature (SST) anomaly adjacent to the coast. Downscaling of reanalysis products was carried out using a mesoscale-resolving numerical ocean model to reproduce the regional SST anomalies. The nested model has a 9 km horizontal resolution that extend from Cabo Corrientes to Point Conception. A downscaling experiment that computes surface fluxes online with bulk formulae achieves a better representation of the event than a version with prescribed surface fluxes. The nested system improves the representation of the large scale warming and the localized SST anomaly adjacent to BC Peninsula compared to the reanalysis product. A sensitivity analysis shows that air temperature and to a lesser extent wind stress anomalies are the primary drivers of the formation of BC temperature anomaly. The warm air-temperature anomalies advect from the near-equatorial regions and the central north Pacific and is associated with sea-level pressure anomalies in the synoptic-scale atmospheric circulation. This regional warm pool has a pronounced signature on sea level anomaly in agreement with observations, which may have implications for biogeochemistry.

The Context of the 2018–20 “Protracted” El Niño Episode: Australian Drought and Terrestrial, Marine, and Ecophysiological Impacts

Abstract A “protracted” El Niño episode occurred from March–April 2018 to April–May 2020. It was manifested by the interlinked Indo-Pacific influences of two components of El Niño phases. Positive Indian Ocean dipoles (IODs) in 2018 and 2019 suppressed the formation of northwest cloud bands and southern Australia rainfall, and a persistent teleconnection, with enhanced convection generated by positive Niño-4 region sea surface temperature (SST) anomalies and strong subsidence over eastern Australia, exacerbated this Australian drought. As with “classical” El Niño–Southern Oscillation (ENSO) events, which usually last 12–18 months, protracted ENSO episodes, which last for more than 2 yr, show a similar pattern of impacts on society and the environment across the Indo-Pacific domain, and often extend globally. The second half of this study puts the impact of the 2018–20 protracted El Niño episode on both the Australian terrestrial agricultural and marine ecophysiological environments in a broader context. These impacts are often modulated not only by the direct effects of ENSO events and episodes, but by interrelated local to region ocean–atmosphere interactions and synoptic weather patterns. Even though the indices of protracted ENSO episodes are often weaker in magnitude than those of major classical ENSO events, it is the longer duration of the former that poses its own set of problems. Thus, there is an urgent need to investigate the potential to forecast protracted ENSO episodes, particularly when the mid-2020 to current 2022 period has been experiencing a major protracted La Niña episode with near-global impacts. Significance Statement The major 2018–20 Australian drought and its terrestrial and marine impacts were caused by a “protracted” El Niño episode, exacerbated by global warming. Indo-Pacific ocean–atmosphere interactions resulted in a persistent positive western Pacific Niño-4 sea surface temperature anomaly during the period 2018–20 and positive Indian Ocean dipoles (IODs) in 2018 and 2019. These suppressed rainfall across eastern Australia and limited northwest Australian cloud band rainfall across southern Australia. Australian agricultural and ecophysiological impacts caused by protracted El Niño–Southern Oscillation (ENSO) episodes permeate, overstress, and expose society, infrastructure, and livelihoods to longer temporal-scale pressures than those experienced during shorter “classical” ENSO events. Thus, there is an urgent need to investigate the potential to forecast protracted ENSO episodes.

Sea surface temperature predictability assessment with an ensemble machine learning method using climate model simulations

Ensemble models, statistical analysis and machine learning (ML) can be used to predict novel conditions in a rapidly changing ocean. Traditionally, ML has been understood as a purely data-driven approach and has been used on both observational and model data to forecast Sea Surface Temperature (SST) anomalies. Here we use ML trained only on climate model simulations to predict regional SST variations, thereby suggesting a novel role for ML as an ensemble model interpolator. We propose a measure of the predictability provided by different ML implementations as well as by standard time series analysis methods. Weighting each forecast by this predictability measure computed on model data only, provides a significant improvement in forecast skill. We demonstrate the performance of this approach for regions around Australia, the Nino3.4 region (central-eastern equatorial Pacific) and in the eastern equatorial Pacific. These analyses show that SST predictability varies as a function of geographical location, area size, seasonality, proximity to the coast and model data quality.