Sea Surface Temperature Trends Research Articles

Intensified upwelling: normalized sea surface temperature trends expose climate change in coastal areas

Abstract. Eastern boundary upwelling systems (EBUSs) provide valuable natural resources due to their high primary production. However, there is significant uncertainty in how climate change may affect the mechanisms that sustain these ecosystems in the future. Therefore, assessing the effects of climate change on EBUSs under the current global warming scenario is crucial for efficient ecosystem management. In 1990, Andrew Bakun suggested an increase in the upwelling intensity due to the rise of the ocean–land pressure gradient. Since there is a significant link between thermal gradients and offshore Ekman transport, we use sea level pressure (SLP) and deseasonalized sea surface temperature (SST) data from remote sensing to elucidate this hypothesis and validate it using in situ observations. SST is an indicator of coastal upwelling, and our long-term analysis of monthly and deseasonalized SST records shows that the seasonal and synoptic processes have minimal influence on the SST–upwelling intensity relationship. Upwelling within the same EBUS is not usually evenly distributed along coastlines, leading to upwelling in specific areas, referred to as upwelling centers. We compare the SST trends in the main upwelling centers of the four EBUSs with those in open ocean waters through a new index, αUI, designed to characterize upwelling changes in the EBUS. An a-dimensional number allows us to normalize the trends independently of the upwelling system and compare all of them. Furthermore, we have complemented the SST index with sea level pressure gradient data. This new index (supported by SLP gradient trends) indicates intensification in all the EBUSs, revealing a coherent pattern within EBUSs in the same ocean (i.e., Canarian and Benguela or Californian and Humboldt upwelling systems).

Revisiting the reanalysis-model discrepancy in Southern Hemisphere winter storm track trends

Southern Hemisphere (SH) storminess has increased in the satellite era and recent work suggests comprehensive climate models significantly underestimate the trend. Here, we revisit this reanalysis-model trend discrepancy to better understand the mechanisms underlie it. A comprehensive like-for-like analysis shows reanalysis trends exhibit large uncertainty, and coupled climate model simulations exhibit weaker trends than most but not all reanalyses. However, simulations with prescribed sea surface temperature (SST) exhibit significantly greater storminess trends, particularly in the South Pacific, implying SST trend discrepancies in coupled simulations impact storminess trends. Using pacemaker simulations that correct Southern Ocean and tropical east Pacific SST trend discrepancies, we show that storminess trends in coupled simulations are underestimated because they do not capture the enhanced storminess resulting from Southern Ocean cooling and La-Nina-like teleconnection trends. Our findings emphasize large reanalysis uncertainty in SH circulation trends and the impact of regional SST trend discrepancies on circulation trends.

SST trends in certain areas of the Barents Sea in the winter season and mechanisms of their formation

The climate changes observed over the past few decades are most clearly manifested in the Arctic Ocean. Sea surface temperature (SST) is one of the most reliable indicators of climate change. In this paper we analyze the changes of winter SST for the western, northeastern and southeastern regions of the Barents Sea and examine the relationship of the emerging STS trends with the influence of various external factors. The working data set is represented by average monthly SST values taken from the ERA-5 reanalysis for the period 1949–2023 with a spatial resolution of 0.25×0.25° and average water temperature values on the Kola Meridian section in the 0–50 m layer. Additionally, the Arctic Oscillation (AO), Arctic Dipole (AD) and Atlantic Multidecadal Oscillation (AMO) indices were used as external factors that may affect SST variability. The time series analyzed was divided into three periods: 1949–1969, 1970–1990, 1991–2023, where the variability of the analyzed parameters was different. Thus, in the first period the trend in SST changes was negative, for the second period it was slightly negative or neutral, and for the third period it was positive. It is shown that SST in all the regions of the Barents Sea has undergone significant changes, which were most noticeable in the “warm” period of 1991–2023, when the rate of SST increasing was up to 10·10-2 °C/year in areas under the warm Atlantic water influence. The analysis of SST variability in the Barents Sea shows that the positive anomalies observed in the recent years are most likely associated with the changes in the atmospheric circulation. The Wavelet coherence analysis showed the closest agreement between the changes in the sea surface temperature and the AD index in the winter season, and with the AMO index.

Tropical and Antarctic sea ice impacts of observed Southern Ocean warming and cooling trends since 1949

Southern Ocean (SO) sea surface temperatures (SSTs) warmed from approximately 1949–1978 and cooled slightly from 1979–2013. We compare the remote impacts of these SO trends using historical coupled model experiments in which the model’s SO SST anomalies are nudged to observations. Compared to the control (no nudging) ensemble, the nudged ensemble shows enhanced SST warming in the tropical southeast Pacific and Atlantic, and greater Antarctic sea ice loss, during the SO warming period: analogous to the impacts of SO cooling but of opposite sign. The SO-driven response in the tropical Pacific (Atlantic) is statistically significant when considering the trend difference between the two periods, and accounts for 34% (59%) of the observed non-radiatively forced trend. Surface heat budget analysis indicates wind-evaporation-SST feedback dominates over shortwave cloud feedback in amplifying the SO-driven SST trends in the tropics during the SO warming period, opposite to that for the SO cooling period.

Long-term responses of phytoplankton biomass to the ocean surface variables in the central parts of the Arabian Sea and the Bay of Bengal

The northern Indian Ocean has been warming steadily for over a half-century, especially the north-western Indian Ocean. It is widely reported that the increasing sea surface temperature in the global oceans decreases phytoplankton biomass and productivity. The impacts of long-term variations in the sea surface properties on the phytoplankton biomass (chlorophyll a) are least studied in the northern Indian Ocean. In this study, we have retrieved satellite, model, and ARGO float data sets to investigate the long-term variations in the distributions and trends of major oceanic variables for a better understanding of the respective changes that occurred in chlorophyll a concentration in the central regions of the Arabian Sea (AS) and the Bay of Bengal (BB). We have selected variables such as sea surface temperature (SST), sea surface salinity (SSS), photosynthetically available radiation (PAR), euphotic depth (ZEU), mixed layer depth (MLD), wind speed, mean sea level anomaly (MSLA), surface currents, etc., to relate with chlorophyll a. We found significant increasing trends in SST and positive-MSLA in both basins, and the chlorophyll a was decreased in the AS but contrastingly increased in the BB. Further data analysis revealed the possible reasons, such as seasonal changes in mean sea level anomaly and meridional currents, for the increasing trend of chlorophyll a in the central Bay of Bengal. The northward flow of the meridional currents during the southwest monsoon (SWM), transports the nutrient-rich water from the coastal upwelling zone of the southwest coast of India to the southern and central BB, and enhances chlorophyll a. Contrastingly, the southward flow of low-saline and nutrient-depleted Bay of Bengal water reduces the chlorophyll a. In addition, the large area of cold-core eddies found during the NEM enhanced the chlorophyll a in the central BB. Though contrasting trends between both basins in chlorophyll a distribution were found, the mean concentration of chlorophyll a in the northern Indian Ocean decreases. The present study signifies the importance of monsoon currents and eddies in regulating the chlorophyll a biomass and primary productivity in the AS and BB.

Time series analysis of sea surface temperature change in the coastal seas of Türkiye

Sea surface temperature (SST) is a crucial geophysical parameter in assessing heat exchange between the air and sea surface. Changes in SST and its accurate prediction play a pivotal role in explaining the global heat balance, determining atmospheric circulations, and constructing global climate models. This work aims to reveal a model for one-month-ahead forecasting of SST time series data along the Türkiye coasts, encompassing the Mediterranean, Aegean, Marmara, and Black Seas, and their long-term future forecast. A long short-term memory (LSTM) neural network and seasonal autoregressive integrated moving average (SARIMA) models are used for this purpose. The ECMWF ERA5 (0.5ox0.5°) monthly SST dataset spanning the years 1970–2023 is used for model development. The results obtained from the LSTM and SARIMA models show that there will be an increasing trend in SSTs along these seacoasts until 2050. The SST measurements of 23.4 °C, 20.2 °C, 17.0 °C, and 16.6 °C recorded along the Mediterranean, Aegean, Marmara, and Black Seas in 2023 are expected to rise to 25.1 °C, 21.9 °C, 18.1 °C, and 18.8 °C, respectively, by 2050. These figures indicate an increase of 7.3%, 8.4%, 6.5%, and 13.3% in the SST values across these coastal seas over the next quarter century.

Trends of maximum annual sea surface temperature in the Eastern China Seas

The increasing ocean warming due to climate change significantly threatens regional marine ecosystems by raising the frequency and severity of extreme temperature events. This study examines patterns and trends of maximum annual sea surface temperature (Tmax) in the Eastern China Seas from 1985 to 2022. The results show a significant warming trend in Tmax, exceeding the global average, with notable differences between southern and northern regions. The northern Tmax warming rate is faster, with occurrence times significantly advancing, while the southern Tmax warming rate is slower, with occurrence times significantly delayed. The southern Tmax and its timing are closely correlated with the annual maximum air temperature and its timing. In the north, Tmax timing is influenced by latent heat flux (QLH); a significant increase in August QLH inhibits the continued rise of SST, causing Tmax to advance. The study also highlights a significant increase in marine heatwaves at Tmax timing, with higher Tmax indicating a higher occurrence probability. By elucidating these Tmax trends and dynamics, our study enhances understanding of regional climate impacts, supporting targeted conservation efforts and adaptive ecosystem management strategies in the Eastern China Seas.

Phytoplankton bloom detection and trends in satellite inherent optical properties over the last two decades in a heterogeneous Patagonian coastal system

ABSTRACT To effectively address ecosystem health risks, it is crucial to use detection methods that efficiently cover vast areas with good spatial resolution. These methods should enhance understanding of how phytoplankton blooms might evolve due to climate change. Satellite Ocean Color sensors are advantageous for detecting and monitoring phytoplankton blooms over time. This study uses the Inherent Optical Properties (IOP) index, which considers light absorption by phytoplankton (Ab_phy) and by detritus plus colored dissolved organic matter (Ab_adg), to detect phytoplankton blooms in six subareas within the San Matías Gulf (SMG; Patagonia, Argentina). The findings reveal a significant increase in bloom alerts over the last 20 years in the northwestern and southwestern subareas. Temporal changes in chlorophyll a (Chla) and sea surface temperature (SST) were observed, both showing an increase over the studied period. Environmental features like the diffusive attenuation coefficient (Kd_490) and Ab_phy also showed positive trends in four of the six subareas. The positive trends in SST and Kd_490 suggest a potential reduction in the euphotic zone depth. Additionally, the presence of phytoplankton biomass, indicated by Chla and Ab_phy, is linked to reduced light penetration in the water column due to absorption by the cells and self-shading. A decrease in Ab_adg was observed, while photosynthetically active radiation (PAR) showed no significant trend over the last two decades. These patterns could significantly impact the frequency and timing of phytoplankton blooms, altering their community composition and phenology. Such changes have profound implications for the entire marine food web and the ecosystem services within the SMG. The results underscore the importance of incorporating optical data for monitoring phytoplankton blooms across multiple areas.

STA-SST: Spatio-temporal time series prediction of Moroccan Sea surface temperature

Global Sea Surface Temperature (SST) trends have garnered significant attention in several ocean-related domains, including global warming, marine biodiversity, and environmental protection. This involves having an accurate and efficient forecast of future SST to ensure early detection and response in time to these events. Deep learning algorithms have become popular in SST prediction recently, although directly obtaining optimal prediction results from historical observation data is not simple. In this paper, we propose STA-SST, a new deep learning approach for forecasting SST, by combining the temporal dependencies of SST using the Bidirectional Long Short-Term Memory (BiLSTM) model, spatial features extracted from the convolution layer, and relevant information from the attention mechanism. To assess how well the Attention-BiLSTM with convolution layer predicts SST, we conducted a case study in the Moroccan Sea, concentrating on five different areas. The proposed model was compared against alternative forecasting models, including LSTM, XGBoost, Support Vector Regression (SVR), and Random Forest (RF). The experimental results show that STA-STT produces noticeably the best prediction results and is a solid choice for field implementation.

Tropical eastern Pacific cooling trend reinforced by human activity

It remains unresolved whether the La Niña-like sea surface temperature (SST) trend pattern during the satellite era, featuring a distinct warming in the northwest/southwest Pacific but cooling in the tropical eastern Pacific, is driven by either external forcing or internal variability. Here, by conducting a comprehensive analysis of observations and a series of climate model simulations for the historical period, we show that a combination of internal variability and human activity may have shaped the observed La Niña-like SST trend pattern. As in observations, SSTs in each model ensemble member show a distinct multi-decadal swing between El Niño-like and La Niña-like trend patterns due to internal variability. The ensemble-mean trends for some models are, however, found to exhibit an enhanced zonal SST gradient along the equatorial Pacific over periods such as 1979–2010, suggesting a role of external forcing. In line with this hypothesis, single-forcing large ensemble model simulations show that human-induced stratospheric ozone depletion and/or aerosol changes have acted to enhance the zonal SST gradient via strengthening of Pacific trade winds, although the effect is model dependent. Our finding suggests that the La Niña-like SST trend is unlikely to persist under sustained global warming because both the ozone and aerosol impacts will eventually weaken.

Future warming of the Gulf of Oman: SST trends under contrasting climate scenarios by 2050

This study investigated potential changes in sea surface temperature (SST) within the Gulf of Oman over the next three decades (2020–2050) under contrasting climate scenarios. Monthly SST data from three Coupled Model Intercomparison Project Phase 6 (CMIP6) models were obtained from the Earth System Grid Federation (ESGF) database for a defined spatial grid (0.5° x 0.5°) encompassing the Gulf of Oman. Future changes (2020–2050) in SST were analyzed under two contrasting Shared socioeconomic Pathways (SSPs): SSP245 (optimistic) and SSP585 (pessimistic).A time series analysis employing a weighted average approach across all three models was conducted. This analysis revealed a projected increase in SST for most seasons and months, except for summer. Further trend analysis was performed using the non-parametric Mann-Kendall test and Sen's slope estimator. This analysis indicated a moderate warming trend in the Gulf of Oman's SST over the next 30 years, with an average increase of approximately 1°C. Spatial analysis of SST was also conducted, identifying minimum and maximum temperature values in shallow regions, the Strait of Hormuz, and its connection to the Persian Gulf. The findings of this study suggest a potential for significant warming in the Gulf of Oman over the coming decades, with implications for regional marine ecosystems and weather patterns. Understanding these projected changes is crucial for informing adaptation strategies and mitigating the potential negative impacts of climate change in the region.

Late Triassic (Norian) strontium and oxygen isotopes from the Baoshan block, southwestern China: Possible causes and implications for climate change

The Norian Stage (Late Triassic) has long been regarded as an interval of stable climates, but, in fact, there are only sparse studies of the paleoclimate variations during this longest (>20 Myr) stage of the Phanerozoic. Here, oxygen and strontium isotopes have been measured on conodont apatite from the open-marine shelf succession at the Xiquelin section (Baoshan block, Yunnan Province, China). Magnetostratigraphy linked to conodont biostratigraphy indicates that the succession was deposited during the Sevatian substage, upper Norian. The δ18Oapatite values from conodonts indicate that low-latitude average sea-surface temperatures in eastern Tethys were ∼32 °C during the earliest Sevatian, cooled to ∼25 °C through the middle Sevatian, and then increased again to ∼29 °C by the late Sevatian. The seawater 87Sr/86Sr values maintained a high plateau through the entire Sevatian, with very little variation between inferred warm and cool episodes. The possible explanation for the observed trends in sea-surface temperature and 87Sr/86Sr during Sevatian is an enhanced weathering of silicates exposed during the closure of the Paleo-Tethys Ocean at the zenith of Pangea supercontinent assembly.

The habitat preference of commercial tuna species based on a daily environmental database approach in the tropical region of the Eastern Indian Ocean off Java-Bali waters

This paper explores the habitat characteristics of commercial tuna species based on daily oceanography parameters in the Eastern Indian Ocean Off Java-Bali Waters. Moreover, more research is needed combining the daily spatial distribution of oceanographic variables of surface and sub-surface data to analyse the habitat characteristics of large pelagic fish, including tuna species. In this study, we used five main daily oceanography parameters: sea surface temperature (SST), sea surface chlorophyll (CHLa), sea surface height (SSH), dissolved oxygen at 100m (DO100), the temperature at 100m (temp100) and the combination of the catch of yellowfin (YFT), albacore (ALT) and bigeye (BET) tuna that use long lines. To analyse the relationship between the environmental database and tuna catch, we utilized Generalized Additive Models (GAMs) from univariate variables until the combination of all variables. The result stated that all the variables influence the existence of all tuna species with P-values <0.001. Temperature is the most critical predictor variable, SST is the most vital predictor for BET and YFT tuna, and temp100 is the most critical for ALT. The second most essential variables were DO100 for BET, Temp 100 for YFT, and SSH for ALT. Moreover, BET and YFT prefer to stay at a lower temp100, and ALT tuna remains at a higher temp100. However, all of them avoid an SST higher than 29 °C. Further assessment of the long-term SST trend specific to tuna species is required to fully account for the effects of global warming on the oceans.

Indian ocean warming, extreme positive Indian Ocean Dipole events, and their impact on monthly Indian Monsoon rainfall from June to November in NMME models

Indian Ocean (IO) warming, the frequency of extreme positive Indian Ocean Dipole (EPIOD) events, and its impact on Indian monsoon rainfall (IMR) are more prominent in the recent era. A proper understanding of the relationship between the EPIOD and IMR is very important because two thirds of the people in India are dependent on agriculture and related economy. The primary focus of this study is on three main aspects: (i) analysing the monthly trend of sea surface temperature (SST) in the IO; (ii) the spatial variability of SST anomalies (SSTA) linked to the EPIOD and its impact on the IMR; and (iii) the factor responsible for the intensification of the EPIOD. These aspects are thoroughly assessed using 12 NMME models, comparing them with observations and reanalysis datasets from 1990 to 2020. The analysis reveals a warming trend in the central IO during June and July, with significant increases observed from August to November. Over the past 31 years, the central IO has experienced an approximate rise of 0.9 to 1 °C from June to November. Among the 12 models scrutinised, GFDL_FLOR_A, FLOR_B, and RSMAS_CCSM4 closely align with observed spatial trends. In contrast, models such as GFDL_SPEAR and NASA_GEOSS tend to overestimate these spatial trends. An increase in easterlies over the equatorial eastern IO was identified as a possible driver for the rising SST in the central IO during October and November. In response to EPIOD on the monthly spatial rainfall distribution over India, all NMME models often underestimate rainfall over the west coast and exhibit wet biases over the leeward side of the Western Ghats. Grid-wise skill scores for accumulated monthly rainfall demonstrated variations among NMME models, with GFDL_SPEAR, RSMAS_CCSM4, and other IC3 models showing higher skill. The interhemispheric pressure gradient (IHPG) has been identified as a precursor to EPIOD events. A positive IHPG from March to June is correlated with EPIOD occurrences from October to December. It is observed that half of the NMME models are capable of simulating a positive relationship between IOD and IHPG, consistent with the observed data.

Potential Near‐Term Wetting of the Southwestern United States if the Eastern and Central Pacific Cooling Trend Reverses

AbstractNear‐term projections of drought in the southwestern United States (SWUS) are uncertain. The observed decrease in SWUS precipitation since the 1980s and heightened drought conditions since the 2000s have been linked to a cooling sea surface temperature (SST) trend in the Equatorial Pacific. Notably, climate models fail to reproduce these observed SST trends, and they may continue doing so in the future. Here, we assess the sensitivity of SWUS precipitation projections to future SST trends using a Green's function approach. Our findings reveal that a slight redistribution of SST leads to a wetting or drying of the SWUS. A reversal of the observed cooling trend in the Central and East Pacific over the next few decades would lead to a period of wetting in the SWUS. It is critical to consider the impact of possible SST pattern trends on SWUS precipitation trends until we fully trust SST evolution in climate models.

Long-term climatological trends driving the recent warming along the Angolan and Namibian coasts

The coastal regions off Angola and Namibia are renowned for their highly productive marine ecosystems in the southeast Atlantic. In recent decades, these regions have undergone significant long-term changes. In this study, we investigate the variability of these long-term changes throughout the annual cycle and explore the underlying mechanisms using a 34-year (1982–2015) regional ocean model simulation. The results reveal a clear seasonal dependence of sea surface temperature (SST) trends along the Angolan and Namibian coasts, with alternating positive and negative trends. The long-term warming trend in the Angolan coastal region is mainly explained by a pronounced warming trend in the austral spring and summer (November-January), while the decadal trend off Namibia results from a counterbalance of an austral winter cooling trend and an austral summer warming trend. A heat budget analysis of the mixed-layer temperature variations shows that these changes are explained by a long-term modulation of the coastal currents. The Angolan warming trend is mainly explained by an intensification of the poleward coastal current, which transports more warm equatorial waters towards the Angolan coast. Off Namibia, the warming trend is attributed to a reduction in the northwestward Benguela Current, which advects cooler water from the south to the Namibian coast. These changes in the coastal current are associated with a modulation of the seasonal coastal trapped waves that are remotely-forced along the equatorial waveguide. These long-term changes may have significant implications for local ecosystems and fisheries.

Seasonal patterns and bloom dynamics of phytoplankton based on satellite-derived chlorophyll-a in the eastern yellow sea

Satellite-derived chlorophyll-a concentration (Chl-a) is essential for assessing environmental conditions, yet its application in the optically complex waters of the eastern Yellow Sea (EYS) is challenged. This study refines the Chl-a algorithm for the EYS employing a switching approach based on normalized water-leaving radiance at 555 nm wavelength according to turbidity conditions to investigate phytoplankton bloom patterns in the EYS. The refined Chl-a algorithm (EYS algorithm) outperforms prior algorithms, exhibiting a strong alignment with in situ Chl-a. Employing the EYS algorithm, seasonal and bloom patterns of Chl-a are detailed for the offshore and nearshore EYS areas. Distinct seasonal Chl-a patterns and factors influencing bloom initiation differed between the areas, and the peak Chl-a during the bloom period from 2018 to 2020 was significantly lower than the average year in both areas. Specifically, bimodal and unimodal peak patterns in Chl-a were observed in the offshore and nearshore areas, respectively. By investigating the relationships between environmental factors and bloom parameters, we identified that major controlling factors governing bloom initiation were mixed layer depth (MLD) and suspended particulate matter (SPM) in the offshore and nearshore areas, respectively. Additionally, this study proposed that the recent decrease in the peak Chl-a might be caused by rapid environmental changes such as the warming trend of sea surface temperature (SST) and the limitation of nutrients. For example, external forcing, phytoplankton growth, and nutrient dynamics can change due to increased SST and limitation of nutrients, which can lead to a decrease in Chl-a. This study contributes to understanding phytoplankton dynamics in the EYS, highlighting the importance of region-specific considerations in comprehending Chl-a patterns and bloom dynamics.

Crucial role of sea surface temperature warming patterns in near-term high-impact weather and climate projection

Recent studies indicate that virtually all global climate models (GCMs) have had difficulty simulating sea surface temperature (SST) trend patterns over the past four decades. GCMs produce enhanced warming in the eastern Equatorial Pacific (EPAC) and Southern Ocean (SO) warming, while observations show intensified warming in the Indo-Pacific Warm Pool (IPWP) and slight cooling in the eastern EPAC and SO. Using Geophysical Fluid Dynamics Laboratory’s latest higher resolution atmospheric model and coupled prediction system, we show the model biases in SST trend pattern have profound implications for near-term projections of high-impact storm statistics, including the frequency of atmospheric rivers (AR), tropical storms (TS) and mesoscale convection systems (MCS), as well as for hydrological and climate sensitivity. If the future SST warming pattern continues to resemble the observed pattern from the past few decades rather than the GCM simulated/predicted patterns, our results suggest (1) a drastically different future projection of high-impact storms and their associated hydroclimate changes, especially over the Western Hemisphere, (2) a stronger global hydrological sensitivity, and (3) substantially less global warming due to stronger negative feedback and lower climate sensitivity. The roles of SST trend patterns over the EPAC, IPWP, SO, and the North Atlantic tropical cyclone Main Development Region (AMDR) are isolated, quantified, and used to understand the simulated differences. Specifically, SST trend patterns in the EPAC and AMDR are crucial for modeled differences in AR and MCS frequency, while those in the IPWP and AMDR are essential for differences in TS frequency over the North Atlantic.

Climate change impacts on small pelagic fish distribution in Northwest Africa: trends, shifts, and risk for food security

Climate change is recognised to lead to spatial shifts in the distribution of small pelagic fish, likely by altering their environmental optima. Fish supply along the Northwest African coast is significant at both socio-economic and cultural levels. Evaluating the impacts of climatic change on small pelagic fish is a challenge and of serious concern in the context of shared stock management. Evaluating the impact of climate change on the distribution of small pelagic fish, a trend analysis was conducted using data from 2363 trawl samplings and 170,000 km of acoustics sea surveys. Strong warming is reported across the Southern Canary Current Large Marine Ecosystem (CCLME), extending from Morocco to Senegal. Over 34 years, several trends emerged, with the southern CCLME experiencing increases in both wind speed and upwelling intensity, particularly where the coastal upwelling was already the strongest. Despite upwelling-induced cooling mechanisms, sea surface temperature (SST) increased in most areas, indicating the complex interplay of climatic-related stressors in shaping the marine ecosystem. Concomitant northward shifts in the distribution of small pelagic species were attributed to long-term warming trends in SST and a decrease in marine productivity in the south. The abundance of Sardinella aurita, the most abundant species along the coast, has increased in the subtropics and fallen in the intertropical region. Spatial shifts in biomass were observed for other exploited small pelagic species, similar to those recorded for surface isotherms. An intensification in upwelling intensity within the northern and central regions of the system is documented without a change in marine primary productivity. In contrast, upwelling intensity is stable in the southern region, while there is a decline in primary productivity. These environmental differences affected several small pelagic species across national boundaries. This adds a new threat to these recently overexploited fish stocks, making sustainable management more difficult. Such changes must motivate common regional policy considerations for food security and sovereignty in all West African countries sharing the same stocks.

Decadal Variation in Winter‐Spring Thermal Front to the Zhejiang‐Fujian Coast and Its Mechanism

AbstractOff the east shore of China, thermal front plays a crucial role in modulating coastal biogeochemical environment. Based on multi‐source observational and reanalysis products, decadal variation and regulatory mechanism of Zhejiang‐Fujian coastal front (ZFCF) were investigated. The intensity of ZFCF showed a two‐stage inversed varying trend over past four decades: a downtrend from 1982 to 2002 followed by an uptrend from 2002 to 2022. During 1982–2002, sea surface temperature (SST) experienced more pronounced warming in inshore areas than offshore due to weakening of the southward coastal current, and this primarily led to the downtrend of ZFCF. Within 2002–2022, opposite SST trends were observed on two sides of ZFCF, that is, the ZFCF kept intensifying due to the cooperation of cooling inshore and warming offshore. The enhanced coastal current driven by stronger monsoon and increased Yangtze River discharge cooled the inshore area, then the cooling was further facilitated by intensified heat loss in the upper layer of the plume. Meanwhile, the onshore shift of Kuroshio led to strengthened intrusion of warm water into the East China Sea, heating the offshore side of ZFCF and thus intensifying the front.