Seasonal Sea Surface Temperature Research Articles

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

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

Human-induced intensified seasonal cycle of sea surface temperature

Changes in the seasonal cycle of sea surface temperature (SST) have far-reaching ecological and societal implications. Previous studies have found an intensified SST seasonal cycle under global warming, but whether such changes have emerged in historical records remains largely unknown. Here, we reveal that the SST seasonal cycle globally has intensified by 3.9 ± 1.6% in recent four decades (1983–2022), with hotspot regions such as the northern subpolar gyres experiencing an intensification of up to 10%. Increased greenhouse gases are the primary driver of this intensification, and decreased anthropogenic aerosols also contribute. These changes in anthropogenic emissions lead to shallower mixed layer depths, reducing the thermal inertia of upper ocean and enhancing the seasonality of SST. In addition, the direct impacts of increased ocean heat uptake and suppressed seasonal amplitude of surface heat flux also contribute in the North Pacific and North Atlantic. The temperature seasonal cycle is intensified not only at the ocean surface, but throughout the mixed layer. The ramifications of this intensified SST seasonal cycle extend to the seasonal variation in upper-ocean oxygenation, a critical factor for most ocean ecosystems.

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

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

Assessing the effect of coastal upwelling on the air temperature at the south-eastern coast of the Baltic Sea

Coastal upwelling along the SE Baltic Sea coast is a common feature, especially during the warm season. It significantly lowers sea surface temperature (SST) in the coastal areas, and, therefore, may be responsible for modifying meteorological conditions in those coastal areas, where upwelling is most frequently observed. This study aims to assess the effect of coastal upwelling on the air temperature at the south-eastern coast of the Baltic Sea based on long-term period observations (2002–2021) from coastal hydrometeorological stations and satellite data. Overall, our study revealed that due to its high frequency and spatial extent, upwelling is responsible for lowering the mean summer season SST of the SE Baltic Sea coast by about 1°C. And even though upwelling is a short-term event, upwelling-induced SST drop results in cooling air temperatures in the coastal areas, i.e., the mean air temperatures during upwelling are typically 2−4°C lower than before. It was also observed that upwelling is favouring the development of advective fog. Thus, sudden changes in meteorological parameters during upwelling can have versatile effects on various socio-economic activities. The results of this study contribute to the understanding of upwelling feedback onto the lower atmosphere and, therefore, are important for advancing the accuracy of weather forecasts that are needed for coastal communities, including marine and coastal industries.

Interhemispheric propagation of seasonal sea surface temperature fluctuations over the western Pacific in CMIP6

AbstractInterannual sea surface temperature (SST) variability in the western Pacific is a critical research topic in climate change, as it can significantly impact regional and global weather patterns. Previous observational studies have shown that SST in the southwestern Pacific (SWP) can effectively serve as a precursor signal for SST in the western tropical Pacific (WTP). In this study, we evaluate and compare the modelling capabilities of 32 CMIP6 models to simulate the relationship between SWP and WTP SST. The results indicate that while some CMIP6 models can simulate the spatial connection and physical processes between the SWP and WTP, there are significant intermodel differences. Specifically, the models that best simulate the cross‐equatorial propagation of SWP SST anomalies are those that accurately simulate the cross‐equatorial wind anomalies induced by SWP SST anomalies, highlighting the key role of wind‐evaporation‐SST feedback in SST propagation. Further analysis reveals that the intermodel spread in cross‐equatorial SST propagation is attributable to model biases in simulating climatological SST and wind speed. Models with warm climatological equatorial SST and strong wind speeds provide favourable conditions for the cross‐equatorial propagation of SWP‐related SST anomalies towards the north. Warm SST and strong inter‐season wind speeds near the equator facilitate the northward propagation of the SWP warm signal, leading to increased warming in the WTP.

Environmental drivers of global variation in home range size of terrestrial and marine mammals.

As animal home range size (HRS) provides valuable information for species conservation, it is important to understand the driving factors of HRS variation. It is widely known that differences in species traits (e.g. body mass) are major contributors to variation in mammal HRS. However, most studies examining how environmental variation explains mammal HRS variation have been limited to a few species, or only included a single (mean) HRS estimate for the majority of species, neglecting intraspecific HRS variation. Additionally, most studies examining environmental drivers of HRS variation included only terrestrial species, neglecting marine species. Using a novel dataset of 2800 HRS estimates from 586 terrestrial and 27 marine mammal species, we quantified the relationships between HRS and environmental variables, accounting for species traits. Our results indicate that terrestrial mammal HRS was on average 5.3 times larger in areas with low human disturbance (human footprint index [HFI] = 0), compared to areas with maximum human disturbance (HFI = 50). Similarly, HRS was on average 5.4 times larger in areas with low annual mean productivity (NDVI = 0), compared to areas with high productivity (NDVI = 1). In addition, HRS increased by a factor of 1.9 on average from low to high seasonality in productivity (standard deviation (SD) of monthly NDVI from 0 to 0.36). Of these environmental variables, human disturbance and annual mean productivity explained a larger proportion of HRS variance than seasonality in productivity. Marine mammal HRS decreased, on average, by a factor of 3.7 per 10°C decline in annual mean sea surface temperature (SST), and increased by a factor of 1.5 per 1°C increase in SST seasonality (SD of monthly values). Annual mean SST explained more variance in HRS than SST seasonality. Due to the small sample size, caution should be taken when interpreting the marine mammal results. Our results indicate that environmental variation is relevant for HRS and that future environmental changes might alter the HRS of individuals, with potential consequences for ecosystem functioning and the effectiveness of conservation actions.

Predictability of marine heatwaves: assessment based on the ECMWF seasonal forecast system

Abstract. Marine heatwaves (MHWs), defined as prolonged period of extremely warm sea surface temperature (SST), have been receiving a lot of attention in the past decade as their frequency and intensity increase in a warming climate. This paper investigates the extent to which the seasonal occurrence and duration of MHWs can be predicted with the European Centre for Medium-Range Weather Forecast (ECMWF) operational seasonal forecast system. The prediction of the occurrence of MHW events, the number of MHW days per season, and their intensity and spatial extent are derived from seasonal SST forecasts and evaluated against an observation-based SST analysis using both deterministic and probabilistic metrics over the 1982–2021 period. Forecast scores show useful skill in predicting the occurrence of MHWs globally for the two seasons following the starting date. The skill is the highest in the El Niño region, the Caribbean, the wider tropics, the north-eastern extra-tropical Pacific, and southwest of the extra-tropical basins. The skill is not as good for other midlatitude eastern basins nor for the Mediterranean, with the forecast system being able to represent the low-frequency modulation of MHWs but showing poor skill in predicting the interannual variability of the MHW characteristics. Linear trend analysis shows an increase in MHW occurrence at a global scale, which the forecasts capture well.

Trends and drivers of CO2 parameters, from 2006 to 2021, at a time-series station in the Eastern Tropical Atlantic (6°S, 10°W)

The seawater fugacity of CO2 (fCO2) has been monitored hourly at an instrumented mooring at 6°S, 10°W since 2006. The mooring is located in the South Equatorial Current and is affected by the equatorial Atlantic cold tongue. This site is characterized by large seasonal sea surface temperature variations (>4°C). The fCO2 is measured by a spectrophotometric sensor deployed at about 1.5 meters deep. Measurements of seawater fCO2, sea surface temperature (SST) and sea surface salinity (SSS) are used to calculate total dissolved inorganic carbon (TCO2) and pH. Total alkalinity (TA) is calculated using an empirical relationship with SSS determined for this region. Satellite chlorophyll-a concentrations at 6°S, 10°W are low (<0.2 mg m-3) but some peaks over 0.8 mg m-3 are sometimes detected in August. Nevertheless, the site is a permanent source of CO2 to the atmosphere, averaging 4.7 ± 2.4 mmol m-2d-1 over 2006-2021. Despite the weakening of the wind, the CO2 flux increases significantly by 0.20 ± 0.05 mmol m-2d-1 yr-1. This suggests that the source of CO2 is increasing in this region. This is explained by seawater fCO2 increasing faster than the atmospheric increase during 2006-2021. Most of the seawater fCO2 increase is driven by the increase of TCO2, followed by SST. The fCO2 increase leads to a pH decrease of -0.0030 ± 0.0004 yr-1. The SST anomalies (SSTA) at 6°S, 10°W are correlated to the Tropical Southern Atlantic (TSA) index and to the Atlantic 3 region (ATL3) index with a correlation coefficient higher than 0.75. The strong positive phase of both ATL3 and TSA, observed towards the end of the time-series, is likely contributing to the strong increase of seawater fCO2.

Reconstructed seasonality during the Mid Piacenzian Warm Interval and early Pleistocene cooling as recorded by growth temperatures from Mercenaria shells

The Mid Piacenzian Warm Interval (MPWI) has been identified as an analogue for future global warming because it had warmer temperatures and higher atmospheric CO2 levels than today, while subsequent early Pleistocene cooling is more similar to modern climate. However, reconstructions of these intervals lack seasonal-scale temperature reconstructions. Seasonal sea surface temperature (SST) reconstructions from deep-time archives can potentially provide insight into the nature of the climate system on sub-annual scales during critical climate states. Here we compared seasonal variability in growth temperatures during the MPWI and subsequent early Pleistocene cooling to modern climate reconstructed from oxygen isotope ratios recorded by the bivalve Mercenaria. Modern shells were collected from the University of North Carolina's Marine Sanctuary. Fossil shells from the Mid-Atlantic Coastal Plain (North Carolina) were collected from the Duplin Formation (MPWI) and the Waccamaw Formation (early Pleistocene). Oxygen isotope ratios range from −1 to 2.4 ‰ during the MPWI, −1–2.4 ‰ during the early Pleistocene, and −2.2 to 2.3 ‰ in modern shells. Stable carbon isotope ratios ranged from −0.91 to 1.67 ‰ during the MPWI, 0.19–1.87 ‰ during the early Pleistocene, and −2.46 to 0.60 ‰ in modern shells. Average seasonal growth temperature variations for the MPWI (∼11 ± 3 °C) are reduced compared to modern instrument records (∼16 ± 3 °C), while the early Pleistocene (∼14 ± 2 °C) was more similar to today. Modern Mercenaria record dark increment formation during the summer while fossil Mercenaria record dark increment formation during the winter. We hypothesize that this difference is timing of dark increment formation may be due in part to differences in water depth (∼1m for modern shells and ∼20m for fossil shells) or a shift in the location of the boundary between biogeographic zones. A −1.6 ‰ shift in mean stable carbon isotope ratios between fossil (0.92 ± 0.66 ‰) and modern (−0.65 ± 0.44 ‰) shells has been observed and may be a result of the “Suess Effect” and/or influences of estuarine/freshwater relative to marine settings.

Marine resource exploitation and human settlement patterns during the Neolithic in SW Europe: stable oxygen isotope analyses (δ18O) on Phorcus lineatus (da Costa, 1778) from Campo de Hockey (San Fernando, Cádiz, Spain)

In recent decades, investigations in the southern Iberian Peninsula have increased our understanding of the socio-economic impact of the spread of the Neolithic in southwestern Europe, including changes in marine resources exploitation. Nevertheless, considerable uncertainty still exists around the seasonality of such subsistence systems and the putative role of marine fish and shellfish to the evolving agro-pastoral economies. Earlier studies on the European Atlantic coast (including Iberia) have shown that the stable oxygen isotope (δ18O) values from the topshell Phorcus lineatus (da Costa, 1778) can be reliably used to derive seasonal sea surface temperatures (SST) during its lifespan. This information can be used by archaeologists to estimate the seasonality of mollusc collection in the past, and to shed light into settlement and subsistence patterns. This paper presents the results of a stable isotope study on archaeological shells of P. lineatus recovered from the Neolithic settlement of Campo de Hockey (Cádiz, Spain). We analysed shells from both funerary and residential contexts and found that P. lineatus was consumed year-round, but with a stronger preference during winter. Our results therefore contribute to advance our understanding of the role of coastal environments in early farming societies of southwestern Europe.

Prediction of seasonal sea surface temperature based on temperature and salinity of subsurface ocean using machine learning

AbstractThe sea surface temperature (SST) is not only a crucial external factor in the evolution of the atmosphere, but also a primary factor and premonition signal used in climate prediction. It is challenging to obtain a precise SST for generating accurate initial and boundary conditions in numerical models. This study employs a machine learning approach, that is, a convolutional neural network (CNN) algorithm, to predict SST on a seasonal scale. In particular, the subsurface ocean temperature (OT) and ocean salinity (OS) at depths of 5.02, 15.08, 25.16, 35.28, 45.45 and 76.55 m were used as training factors in developing a CNN prediction model. The results indicate that subsurface OT and OS can persist for 6 months or longer, with a maximum persistence of up to 12 months. Using the CNN prediction model, the SST can be reliably predicted 6 months in advance in most cases. The predicted SST has a mean bias of approximately 0–0.8 K on the globe. The bias is small (below 0.5 K) in the open ocean. The root mean square errors (RMSEs) of hindcasting for Interdecadal Pacific Oscillation, North Atlantic Oscillation (NAO) and Atlantic Multidecadal Oscillation indices are all less than 1.0 K. Specifically, the RMSE for El Niño prediction is less than 0.5 K. This study provides a viable method for establishing initial and boundary conditions for climate prediction.

Understanding Biases in Indian Ocean Seasonal SST in CMIP6 Models

AbstractThe latest generation of climate models continue to exhibit biases in their representation of climatological sea surface temperature (SST), affecting their ability to simulate climate variability including the Indian Ocean Dipole which is typically too strong. Here, we analyze the surface layer heat budget of the Indian Ocean to diagnose the processes leading to biases in climatological SST biases in 20 Coupled Model Intercomparison Project Phase 6 (CMIP6) models, in comparison to a suite of observational and reanalysis products. In the western tropical Indian Ocean, we find that weaker than observed winds reduce the strength of surface currents leading to warm SST bias. In the south‐eastern tropical Indian Ocean, overly strong southeasterly winds are associated with overestimated coastal upwelling that increases cooling across CMIP6 models. In the Arabian Sea, overly strong surface winds increase latent heat loss and leads to cool SST biases. We also analyze other regions like the Bay of Bengal, where a persistent cool bias cannot be explained by seasonal heat budgets, and southern Indian Ocean, where overly strong surface winds are responsible for cool SST biases. These biases in surface processes are supported by intermodel relationships between relevant variables, thus explaining differences in simulating the climatological SSTs across the model ensemble. Our analysis suggests that biases in atmospheric processes in particular surface winds are a primary cause of biases in Indian Ocean SST. Reducing these biases would improve the simulation of climate variability in the Indian Ocean toward more reliable climate projections and predictions.

Glycerol dialkyl glycerol tetraethers in surficial marine sediments across shelf-to-basin depth transects in the East China Sea: Their sources and potential as sea water temperature proxies

To better understand the compositions and sources of glycerol dialkyl glycerol tetraethers (GDGTs) and their use as proxies in the East China Sea (ECS), we analysed GDGTs in surficial sediments from the ECS outer shelf, slope and Okinawa Trough (OT) in open marine settings between 126°E and 129°E at water depths of either <100 or > 1000 m. The GDGT-0/Cren. values (0.35 ± 0.04) and methane index (MI) (0.17 ± 0.02) were generally low, indicating a negligible contribution of methanogenic Euryarchaeota GDGTs to the open marine settings in the ECS and that isoprenoid GDGTs (isoGDGTs) were mainly derived from marine planktonic Thaumarchaeota. Comprehensive analysis of the degree of cyclisation (DC) (0.34–0.53), #ringstetra (0.53–0.94), and IIIa/IIa (0.54–3.24) indices indicated that branched GDGTs (brGDGTs) may be predominantly produced in situ, with minimal soil contribution in this setting. The TEXH86-derived sea surface temperatures (SST) were closer to the annual SST than the seasonal SST from the World Ocean Atlas (WOA) 2013. The methylation of the branched tetraethers (MBT) index correlated well with the mean annual bottom water temperature (BWT) from WOA 2013. Therefore, we propose that the MBT index from open marine settings in the ECS may reflect BWT changes in marine bottom environments.

Tropical coral reefs in Sri Lanka are threatened due to the fluctuation of seasonal and interannual sea surface temperature.

The thermal stress of oceans causes coral bleaching, which induces loss of life in coral reefs and makes them exposed to other threats which directly and indirectly affect millions of other species that inhabit the reef. However, studies focusing on how those thermal stresses affect Sri Lankan fringing reef ecosystems are scarce. Hence, the patterns of long-term and short-term fluctuations of sea surface temperature (SST) over the shallow reefs around the country were studied by separating them into different zones as the eastern coast (Passikudha, Kayankerni, Adukkuparu, Parrot Rock, and Pigeon Island), the southern coast (Beruwala Barbarian, Hikkaduwa, Unawatuna, Ahangama, Mirissa, Madiha, Polhena, and Devundara), and northern-northwestern coasts (Valiththoondal, Palk Bay, Mannar, Kalpitiya, Thalwila, and Uswatakeiyawa). The 1km Multiscale Ultrahigh Resolution (MUR) Level 4 SST dataset was used to analyze seasonal and interannual SST variability from 2005 to 2021. The data were correlated with the Indian Ocean Dipole (IOD), Ekman velocity, and wind stress curl. The annual, seasonal, and monthly variability of SST on different coasts is significantly different. Higher increasing trends of SST from 0.0324 to 0.0411 ℃/year are observed on different coasts, and most of the time higher positive anomalies are recorded after 2014. The First Inter Monsoon (IM-1) and the month of April are more critical since they reach the maximum SST, and the minimum is in the North West Monsoon (NWM) and January. Significant positive relationships are recorded between the Indian Ocean Dipole (IOD) index and the monthly average SST on different coasts, which was robust on the southern coast. Therefore, tropical coral reefs in Sri Lanka are severely threatened due elevation of SST by global warming and climate variability.

Seasonal and El Niño–Southern Oscillation-related ocean variability in the Panama Bight

Abstract. In the Panama Bight, two different seasonal surface circulation patterns coincide with a strong mean sea level variation, as observed from 27 years of absolute dynamic topography (ADT) and the use of self-organizing maps. From January to April, a cyclonic gyre with a strong southwestward Panama Jet Surface Current (PJSC) dominates the basin circulation, forced by the Panama surface wind jet that also produces upwelling, reducing sea surface temperature (SST), increasing sea surface salinity (SSS) and causing an ADT decrease. From June to December, the Choco surface wind jet enhances SST, precipitation and river runoff, which reduces SSS, causing an ADT rise, which in turn forces a weak circulation in the bight, vanishing the PJSC. Interannual variability in the region is strongly affected by El Niño–Southern Oscillation (ENSO); however this climatic variability does not modify the seasonal circulation patterns in the Panama Bight. In contrast, the positive (negative) ENSO phase increases (decreases) SST and ADT in the Panama Bight, with a mean annual difference of 0.9 ∘C and 9.6 cm, respectively, between the two conditions, while its effect on SSS is small. However, as the strong seasonal SST, SSS and ADT ranges are up to 2.2 ∘C, 2.59 g kg−1 and 28.3 cm, the seasonal signal dominates over interannual variations in the bight.

Impact of Monthly Age Model on Coral Paleothermometer Fidelity: Insights From the Northern South China Sea

AbstractThe strontium‐to‐calcium (Sr/Ca) ratio of coral is widely used as a paleothermometer for tropical sea surface temperature (SST) at subannual resolutions. The fidelity of Sr/Ca‐derived SST estimates largely depends on the properties of the monthly age model selected. Here, we develop a revised monthly age model for coral Sr/Ca estimation from the northern South China Sea based on specific tie points and evaluate the impacts of different age models on SST reconstruction. Our results indicate that our revised monthly age model reduces conversion errors by up to nearly 20%–30% relative to previously reported values, thereby improving the precision of seasonal SST estimates and enabling better paleoclimate interpretations, such as El Niño–Southern Oscillation variability. The revised monthly age model provides a generalized approach for developing more robust seasonal resolution Sr/Ca–SST reconstructions in other regions.

Mid-Holocene expansion of the Indian Ocean warm pool documented in coral Sr/Ca records from Kenya

Proxy reconstructions suggest that mid-Holocene East African temperatures were warmer than today between 8 and 5 ka BP, but climate models cannot replicate this warming. Precessional forcing caused a shift of maximum insolation from boreal spring to fall in the mid-Holocene, which may have favored intense warming at the start of the warm season. Here, we use three Porites corals from Kenya that represent time windows from 6.55 to 5.87 ka BP to reconstruct past sea surface temperature (SST) seasonality from coral Sr/Ca ratios in the western Indian Ocean during the mid-Holocene. Although the Indian monsoon was reportedly stronger in the mid-Holocene, which should have amplified the seasonal cycle of SST in the western Indian Ocean, the corals suggest reduced seasonality (mean 3.2 °C) compared to the modern record (mean 4.3 °C). Warming in austral spring is followed by a prolonged period of warm SSTs, suggesting that an upper limit of tropical SSTs under mid-Holocene conditions was reached at the start of the warm season, and SSTs then remained stable. Similar changes are seen at the Seychelles. Bootstrap estimates suggest a reduction in SST seasonality of 1.3 ± 0.22 °C at Kenya and 1.7 ± 0.32 °C at the Seychelles. SST seasonality at Kenya corresponds to present-day SST seasonality at 55° E–60° E, while SST seasonality at the Seychelles corresponds to present day SST seasonality at ~ 65° E. This implies a significant westward expansion of the Indian Ocean warm pool. Furthermore, the coral data suggests that SST seasonality deviates from seasonal changes in orbital insolation due to ocean–atmosphere interactions.

Abrupt Increase in ENSO Variability at 700 CE Triggered by Solar Activity

AbstractThe El Niño–Southern Oscillation (ENSO) is the dominant interannual variability affecting global weather and climate. However, limited observational records hinder our understanding of the evolution of natural ENSO variability and its driving mechanisms. In this study, ENSO variations from 665 to 749 CE (Common Era) were investigated using monthly sea surface temperature (SST) records of the northern South China Sea derived from coral strontium to calcium ratios of sub‐fossil Porites obtained at the Xisha Islands. The results suggested the existence of cold conditions in this period relative to the twentieth century. No change in SST seasonality for the CE was found that is in agreement with the orbitally controlled insolation seasonality at that time. ENSO variability during 665–749 CE was enhanced by 39% than that during 1980–2014 CE and exhibited fluctuations. A persistent dampened ENSO variability with frequent El Niño events from 665 to 700 CE was followed by a rapid increase in variability to a level double that of the present. The frequency of La Niña events increased during this time. The abrupt transformation of ENSO activity at 700 CE was attributed to the increased natural radiative forcing induced by intense solar irradiance and weak volcanism. This paper demonstrates that ENSO variability can be influenced by external forcings, such as changes in solar and volcanic activity, and not only by the internal dynamics of the climate system.

Hydroclimate seasonality from paired coral Sr/Ca and δ18O records of Kikai Island, Southern Japan: Evidence of East Asian monsoon during mid-to late Holocene

The East Asian Monsoon (EAM) modulates the seasonal variability of sea surface temperature (SST), sea surface salinity (SSS), and rainfall in the region. However, seasonal-scale reconstructions showing the hydroclimate response to monsoon intensity shifts in Holocene are limited. We used paired coral Sr/Ca and oxygen isotope (δ18Ocoral) records from modern (1989–2015), 5.7 ka, 4.9 ka, and 3.2 ka corals from Kikai Island, Southern Japan to reconstruct past seasonal variability of hydroclimatic variables. The monthly δ18Ocoral-SSS relationship revealed a statistically significant positive linear correlation (r = 0.63; p < 0.000; n = 310) while the δ18Osw and rainfall showed a statistically significant negative linear correlation (r = 0.55; p < 0.000; n = 93).The large SST and SSS seasonality in 5.7 ka (ΔSSTmax-min = 9.5 °C; Δδ18Omax-min = 1.86‰) and 4.9 ka (ΔSSTmax-min = 10.2 °C; Δδ18Omax-min = 1.45‰) indicate an enhanced seasonal ocean warming which amplified the Western Pacific Subtropical High (WPSH) and the southwesterlies. In contrast, the small SST amplitude in 3.2 ka (ΔSSTmax-min = 7.8 °C; Δδ18Omax-min = 0.98‰) indicates a weakened WPSH and southwesterlies which led to reduced summer rainfall and positive SSS signal. The lower salinity records due to higher rainfall in 7.0 ka, 6.1 ka, 5.7 ka, and 4.9 ka coincide with the strong East Asian summer monsoon (EASM) from 8.2 to 4.7 ka in stacked sediment records. The δ18Ocoral record shows positive SSS driven by weakened summer monsoon rainfall in 4.4 ka, 4.2 ka, 3.8 ka, 3.4 ka, and 3.2 ka.The higher winter SSS (positive δ18Ocoral) and lower winter SST derived from 5.7 ka coral in Kikai Island agree with the strong East Asian winter monsoon (EAWM) intensity from 8.2 to 5.6 ka based on the stacked sediment record. The weak EAWM phase from 5.6 ka to 4.5 ka is consistent with the winter records of warm SST and lower SSS in 4.9 ka. The lower winter SSS and warmer winter SST in 3.2 ka support the evidence of a weak phase around 3.0 ka. The extratropical systems such as the intensified or weakened Siberian High and Aleutian Low have affected the northeasterly EAWM and consequently influenced the variability of winter SST and SSS in subtropical southern Japan in mid- and late Holocene.

Coral Sr/Ca-derived seasonal sea surface temperature variations in the Qiongdong upwelling area of the northern South China Sea during the Medieval Climate Anomaly

Geological records of seasonal sea surface temperature (SST) records are useful for better understanding the past dynamics of coastal upwelling, and for inferring future scenarios. By using Sr/Ca records obtained from Porites lutea corals in the Qiongdong upwelling (QDU) area of the northern South China Sea (SCS), seasonal SST variations were reconstructed for the 1129–1263 CE interval of the Medieval Climate Anomaly (MCA). On an annual scale, summer SST is negatively correlated with the intensity of the East Asian Summer Monsoon (EASM), indicating a dominant role of the EASM on summer SST in the QDU area. The lack of correlation between winter SST and the East Asian Winter Monsoon (EAWM) may result from the dating errors of the climate archives and the low temporal resolution of EAWM records. Winter SST and summer SST played similarly affected the SST seasonality during the MCA. On the centennial scale, the differences in the averages of summer SST and winter SST in the QDU area between the MCA and the Current Warm Period were attributed to the different EASM and EAWM intensities. The consistent variations between the summer QDU and the winter Sumatra-Java upwelling during both climate intervals may imply that the SST variabilities in these two coastal upwelling systems responded to cross-equatorial winds originating from the Indian Ocean.