Seasonal Cycle Of Sea Surface Temperature Research Articles

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.

40 years of changes in sea surface temperature along the Western Iberian Coast

Climate change is causing mean sea surface temperatures (SST) to increase worldwide. However, this increase has not been temporally or spatially uniform, with variations observed depending both on the period considered and the geographic region. In this context, this paper aims to quantify relevant changes in SST along the Western Iberian Coast over the last four decades, through the calculation of trends and anomalies of long-term time series of in situ observations and satellite-derived data. Potential drivers of SST changes were considered using atmospheric and teleconnections time series. Changes in the seasonal cycle of SST were also evaluated.We show that SST has increased since 1982, with regional variations between 0.10 and 0.25 °C per decade, with an increase in air temperature appearing to drive the SST trends along the Iberian coast. In the near-shore area, no significant trends or changes in the seasonal cycle of SST were observed, which is likely due to a buffer effect caused by the seasonal upwelling that characterizes the region. Recent decades show a slowdown in the increase rate of SST along the Western Iberian Coast. An upwelling intensification could justify this observation, along with the effect of teleconnections on the regional climate, such as the North Atlantic Oscillation (NAO) and the Western Mediterranean Oscillation Index (WeMOI). Our results suggest that the WeMOI plays a more important role in coastal SST variability than the other teleconnections.The present study quantifies regional changes in SST and enhances knowledge of the role of ocean-atmosphere interactions in regulating climate and weather conditions. Moreover, it provides a relevant scientific context to the development of regional adaptative and mitigation actions in response to climate change.

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.

Understanding CMIP6 biases in the representation of the Greater Horn of Africa long and short rains

The societies of the Greater Horn of Africa (GHA) are vulnerable to variability in two distinct rainy seasons, the March–May ‘long’ rains and the October–December ‘short’ rains. Recent trends in both rainy seasons, possibly related to patterns of low-frequency variability, have increased interest in future climate projections from General Circulation Models (GCMs). However, previous generations of GCMs historically have poorly simulated the regional hydroclimate. This study conducts a process-based evaluation of simulations of the long and short rains in CMIP6, the latest generation of GCMs. Key biases in CMIP5 remain or are worsened, including long rains that are too short and weak and short rains that are too long and strong. Model biases are driven by a complex set of related oceanic and atmospheric factors, including simulations of the Walker Circulation. Biased wet short rains in models are connected with Indian Ocean zonal sea surface temperature (SST) gradients that are too warm in the west and convection that is too deep. Models connect equatorial African winds with the strength of the short rains, though in observations a robust connection is primarily found in the long rains. Model mean state biases in the timing of the western Indian Ocean SST seasonal cycle are associated with certain rainfall timing biases, though both biases may be due to a common source. Simulations driven by historical SSTs (AMIP runs) often have larger biases than fully coupled runs. A path towards using biases to better understand uncertainty in projections of GHA rainfall is suggested.

Planktonic foraminiferal assemblages and particle fluxes at the entrance of the Gulf of California highlight the effects of the strong El Niño 2015–2016

The impacts of El Niño 2015–2016 on planktonic foraminiferal assemblages and particle fluxes (total mass, organic carbon, total nitrogen, and carbonate) were analyzed in a sediment trap record located at the entrance of the Gulf of California from 2015 to 2019. Biweekly data of the sea surface temperature (SST) and sea surface chlorophyll-a (Chl-a) were obtained from satellite images (MODIS-AQUA) during this period. Particle fluxes and planktonic foraminiferal assemblages reflected the seasonal cycles of SST and phytoplankton biomass highlighting the effects of El Niño 2015–2016. During neutral and La Niña conditions, winter-spring upwelling leads to low SST, high Chl-a and particle fluxes, and an assemblage dominated by Globigerina bulloides while the summers are characterized by high SST, low Chl-a and particle fluxes, and a Globorotaloides hexagonus assemblage. In contrast, in normal summers, there is an alternation of G. bulloides and Orbulina universa-Trilobatus sacculifer-Globigerinella siphonifera associations. By late autumn under La Niña conditions, the Globigerinita glutinata assemblage reflects the transition from warm to cold conditions and the beginning of the upwelling season. This general pattern was affected by El Niño during 2015–2016. From late summer 2015 to early winter 2016 (El Niño 2015–2016 maximum intensity), Globigerinoides tenellus dominated, reflecting the intrusion of warm and oligotrophic equatorial waters. These results show the strong influence of El Niño Southern Oscillation (ENSO) on oceanic dynamics and planktonic foraminiferal assemblages at the entrance of the Gulf of California, and allow for a better interpretation of the preservation of these anomalous warm events in the sedimentary record, which can provide a better understanding of the long-term variations and effects of ENSO.

Future Amplification of Sea Surface Temperature Seasonality Due To Enhanced Ocean Stratification

AbstractIn many regions the projected future sea surface temperature (SST) response to greenhouse warming is larger in summer than in winter. What causes this amplification of the SST seasonal cycle has remained unclear. To determine robustness of the projected seasonal cycle intensification and ascertain underlying physical mechanisms we analyze a suite of historical and greenhouse warming simulations conducted with 13 coupled general circulation models in the Coupled Model Intercomparison Project Phase 5. In the Representative Concentration Pathway 8.5 scenario, the amplitude of SST seasonal cycle, defined as the difference between climatological maximum and minimum temperature, increases by 30% ± 20% on average by the end of 21st century. Analysis of a simplified mixed layer heat budget demonstrates that the amplification can be attributed to the increasing upper ocean stratification and hence shoaling of the annual‐mean mixed layer. The projected intensification of SST seasonality may have important implications for future changes in marine ecosystems.

Controls on the Boundary Between Thermally and Non‐Thermally Driven pCO2 Regimes in the South Pacific

AbstractRegional and temporal patterns of air–sea carbon exchange are strongly linked to the surface ocean partial pressure of carbon dioxide (pCO2), which varies with sea surface temperature (SST), salinity, dissolved inorganic carbon (DIC), and alkalinity. It is well‐known that temperature controls the pCO2 seasonal cycle in the subtropics, whereas DIC dominates at high latitudes. The balance of mechanisms governing the boundary between these regimes, however, are not well characterized due to lack of year‐round pCO2 data. Here, we use autonomous biogeochemical float measurements from the South Pacific to investigate the processes that control meridional variations in pCO2 seasonality. We find that the transition between pCO2 regimes is linked to the poleward decrease in SST seasonal cycle amplitude, which is closely associated with the northern boundary of deep winter mixed layers. Processes that determine the annual SST range are, therefore, central to the response of oceanic carbon uptake to anthropogenic forcing.

Changing ocean seasonal cycle escalates destructive marine heatwaves in a warming climate

Marine heatwaves (MHWs) can cause various adverse effects on marine ecosystems associated with complicated social ramifications. It has been well established that the gradually rising sea surface temperature (SST) due to anthropogenic carbon emission will cause an increase of the MHW duration and intensity. However, for species with strong adaptation capacity or mobility, MHW changes due to the altered SST variability under greenhouse warming are more crucial but so far remain poorly assessed. Under the high carbon emission scenario, we show that the cumulative duration (intensity) of MHWs, with the effect of secular SST increase excluded, is projected to be 60% (100%) higher by the end of this century than in the 1990s due to an amplified SST seasonal cycle. This increase becomes more evident for stronger MHWs, reaching up to 8 (30) folds for the extreme MHW category. The amplified SST seasonal cycle also causes pronounced seasonality of MHWs, making them more active in summer-autumn than winter-spring. Our results suggest that MHWs are likely to have increasingly devastating impacts on a wide range of marine species in the future without taking effective steps for carbon emission reduction.

Impact of Westerly Wind Bursts on ENSO Based on a Hybrid Coupled Model: Part I – ENSO Simulation

ABSTRACT Westerly wind bursts (WWBs), usually occurring in the tropical Pacific region during the beginning and advancement of El Niño events, play a vital role in El Niño–Southern Oscillation (ENSO). In this study, we use a hybrid coupled model (HCM) for the tropical Pacific Ocean–atmosphere system to investigate the impact of WWBs on ENSO. To achieve this goal, we performed two experiments: first, the standard version of the HCM is integrated for years without prescribed WWBs events; and second, the WWBs are added to the HCM, which are constructed using observational data and WWB parameterization schemes. Results show that when WWBs are added to the HCM not only can a more realistic climatology of sea surface temperature (SST) in both spatial structure and temporal amplitudes be generated but also better ENSO features can be generated than with the HCM alone. The former is mainly reflected in the simulation of the SST seasonal cycle in the eastern Pacific and a reduction in the bias toward the cold tongue in the equatorial eastern Pacific, whereas the latter includes an improvement in a broad spectrum of ENSO features, such as ENSO amplitude, phase locking, asymmetry, and diversity. In particular, when WWBs are added to the HCM, the model can capture central Pacific ENSO events, which are absent in the original HCM. On the other hand, WWBs have little impact on cold events because very few WWBs occur during the cold phase of ENSO. Furthermore, the possible physical mechanisms responsible for these improvements as a result of adding WWBs are discussed.

Tropical Pacific Air‐Sea Interaction Processes and Biases in CESM2 and Their Relation to El Niño Development

AbstractCoupled processes and associated subsurface dynamics near the eastern edge of the Indo/western Pacific (WP) Warm Pool are important for air‐sea interactions involved in tropical Pacific dynamics. We seek to shed light on the physical mechanisms governing air‐sea interactions in the region and the impacts of their biases in models. In this study, we use the Ocean ReAnalysis System 5 (ORAS5) to identify mean‐state biases in the National Center for Atmospheric Research Community Earth System Model version 2 (CESM2) with a particular focus on upper ocean properties and air‐sea interaction processes. We show that the CESM2 has warm and fresh surface biases in the tropical Pacific Ocean, a barrier layer that is too thin in the WP, and an isothermal layer depth (ILD) that is too deep in the eastern Pacific (EP). These biases impact air‐sea interaction processes involved in El Niño development. We compare the strong El Niño events in ORAS5 and CESM2 and show that biases in barrier layer thickness in the WP and in ILD in the EP are significant before the onset of the El Niño events. These biases then influence vertical mixing and entrainment processes, resulting in mixed layer cooling biases. Biases in the sea surface temperature seasonal cycle in the CESM2 also influence the development of the El Niño. We emphasize how the El Niño progression in models can be influenced by its sensitivity to the mean state biases in both subsurface ocean structure and seasonal cycle through local as well as the large‐scale physical processes.

Tropical cyclone-induced sea surface cooling over the Yellow Sea and Bohai Sea in the 2019 Pacific typhoon season

Shallow water response and feedback to tropical cyclones (TCs; known as typhoons in the northwest Pacific) play an important role in modulating TCs' landfall intensity. In the 2019 Pacific typhoon season, four TCs, i.e., Danas in July, Lekima in August, Lingling in September and Mitag in October, traversed and influenced the vast shallow waters of the Yellow Sea (YS) and the Bohai Sea (BS). Based on satellite and in situ buoy observed sea surface temperature (SST) datasets and numerical experiments, in this study, we examined and contrasted the SST responses of the YS and BS shallow waters to these four TCs. Compared to the other three TCs, Lekima with relatively weaker intensity, induced the largest (up to 5.5 °C) and most widespread SST cooling over the whole YS basin, which was attributed to the most stratified and sharpest thermal structure in August based on numerical experiments. The model results also suggest an SST cooling limitation in the condition the whole shallow water column has been well mixed. The buoy observations indicate that more than 80% of the TC-induced SST cooling occurred ahead of the TC eye centre approaching. The TC also contributes significantly to the SST seasonal cycle of coastal waters by disrupting the seasonal SST evolution in several hours and lasting for tens of days.

Spatial and temporal variability of sea surface temperature during El-Niño Southern Oscillation and Indian Ocean Dipole in the Strait of Malacca and Andaman Sea

This study examined the long-term trends and the impacts of climate variability caused by El-Niño Southern/Oscillation (ENSO) and Indian Ocean Dipole (IOD) by using 33-year Advanced Very High Resolution Radiometer (AVHRR) sea surface temperature (SST). The data were retrieved from year 1982 to 2014, hence enabled the observation of both ENSO and IOD events based on this long-term SST trends in the Strait of Malacca (SoM) and Andaman Sea. The 4-km resolution of satellite-derived SST data had been gathered from the National Oceanic and Atmospheric Administration (NOAA). Geographical location portrayed that the seasonal cycle of SST in the SoM and Andaman Sea was characterised by the Asian Monsoon. The correlations between monthly SST in regions with wind velocity, SST anomaly, and indices (Oceanic Niño Index (ONI) and Dipole Mode Index (DMI)) were analysed based on wavelet coherence (WTC) analysis. The seasonal SST in SoM revealed that the temperature was above normal trend during the southwest monsoon, wherein the region experienced warmer temperature especially during the ENSO period due to seasonal wind velocity. The results demonstrated that in certain years, such as in 1992, ENSO was dominating while in 1994, IOD was influential. During the strong El-Niño event in 1997, ONI did not correlate with SST trends in the SoM, whereas during positive IOD in 1994 revealed that DMI did not correlate with SST trends in both SoM and Andaman Sea. The warming trend seemed to have significantly increased over the past 33 years, as displayed by the continuous increment in temperature throughout the years in the study region.

Eastern equatorial Pacific SST seasonal cycle in global climate models: from CMIP5 to CMIP6

The sea surface temperature (SST) seasonal cycle in the eastern equatorial Pacific (EEP) plays an important role in the El Nino-Southern Oscillation (ENSO) phenomenon. However, the reasonable simulation of SST seasonal cycle in the EEP is still a challenge for climate models. In this paper, we evaluated the performance of 17 CMIP6 climate models in simulating the seasonal cycle in the EEP and compared them with 43 CMIP5 climate models. In general, only CESM2 and SAM0-UNICON are able to successfully capture the annual mean SST characteristics, and the results showed that CMIP6 models have no fundamental improvement in the model annual mean bias. For the seasonal cycle, 14 out of 17 climate models are able to represent the major characteristics of the observed SST annual evolution. In spring, 12 models capture the 1–2 months leading the eastern equatorial Pacific region 1 (EP1; 5°S–5°N, 110°–85°W) against the eastern equatorial Pacific region 2 (EP2; 5°S–5°N, 140°–110°W). In autumn, only two models, GISS-E2-G and SAM0-UNICON, correctly show that the EP1 and EP2 SSTs vary in phase. For the CMIP6 MME SST simulation in EP1, both the cold bias along the equator in the warm phase and the warm bias in the cold phase lead to a weaker annual SST cycle in the CGCMs, which is similar to the CMIP5 results. However, both the seasonal cold bias and warm bias are considerably decreased for CMIP6, which leads the annual SST cycle to more closely reflect the observation. For the CMIP6 MME SST simulation in EP2, the amplitude is similar to the observed value due to the quasi-constant cold bias throughout the year, although the cold bias is clearly improved after August compared with CMIP5 models. Overall, although SAM0-UNICON successfully captured the seasonal cycle characteristics in the EEP and the improvement from CMIP5 to CMIP6 in simulating EEP SST is clear, the fundamental climate models simulated biases still exist.

Towards an objective assessment of climate multi-model ensembles – a case study: the Senegalo-Mauritanian upwelling region

Abstract. Climate simulations require very complex numerical models. Unfortunately, they typically present biases due to parameterizations, choices of numerical schemes, and the complexity of many physical processes. Beyond improving the models themselves, a way to improve the performance of the modeled climate is to consider multi-model combinations. In the present study, we propose a method to select the models that yield a multi-model ensemble combination that efficiently reproduces target features of the observations. We used a neural classifier (self-organizing maps), associated with a multi-correspondence analysis to identify the models that best represent some target climate property. We can thereby determine an efficient multi-model ensemble. We illustrated the methodology with results focusing on the mean sea surface temperature seasonal cycle in the Senegalo-Mauritanian region. We compared 47 CMIP5 model configurations to available observations. The method allows us to identify a subset of CMIP5 models able to form an efficient multi-model ensemble. The future decrease in the Senegalo-Mauritanian upwelling proposed in recent studies is then revisited using this multi-model selection.

Reconstruction of Large-Scale Sea Surface Temperature and Salinity Fields Using Sub-Regional EOF Patterns From Models

A method for reconstruction of gridded fields of sea surface variables from time-dependent observations, using sub-regional EOF (Empirical Orthogonal Functions) patterns from models, is presented and tested. Covariance fields, calculated from the model results over long enough time span, are used to find EOF modes. The gravest “observational” amplitudes and their first temporal derivatives are determined from the least-square minimization of fitting errors in relation to the observed values. The field is reconstructed by superposition of continuous model-based mode patterns multiplied by observational amplitudes that meet adopted statistical limits. If the observational amplitude exceeds the limits, gridded fields for this and higher modes are not produced. We applied the method in the northeastern Baltic over the model time series 2010-2015. Daily averages of sea surface temperature (SST) and salinity (SSS) from the high-resolution (grid step 0.5 nautical miles) sub-regional HBM model were spatially averaged over bins of 5x5 nautical miles. Three first modes cover 99% of variance of temperature and 61.4% of salinity. As shown by experiments with pseudo-observations (model values at these points reconstructed to the model grid and then compared with the original model data), reconstruction performance depends on the configuration of the observation points in the model domain. Still, a few first modes usually produce acceptable results. When removing the SST seasonal cycle prior to EOF analysis, spatial patterns of leading modes remained practically unchanged, share of variance of the three first modes was reduced to 88,6% and reconstruction errors were reduced by about 25%. Sufficient spatial data coverage of the larger basin with ship-born observations usually takes quite long time – of the order of month; therefore, time correction of the amplitudes using the found temporal derivatives improves the accuracy of reconstruction. The method is compared with the Optimal Interpolation (OI) by using the pseudo-observations. Results show that, for SST reconstruction, the OI method is significantly worse than the EOF method. For SSS, OI is slightly better than EOF. The superiority of EOF is that the remote correlation patterns can be used in the reconstruction, which is important when the observations are sparse.

Analysis of ENSO simulation biases in FIO-ESM version 1.0

As the most significant interannual variability in the climate system, El Niño-Southern Oscillation (ENSO) has critical effects on global weather and climate patterns. To simulate and predict ENSO, coupled general circulation models (CGCMs) have become a key tool. However, the accurate simulation of ENSO is still a challenge for CGCMs. The performance of El Niño simulations conducted through FIO-ESM v1.0 is examined based on the outputs of the Coupled Model Intercomparsion Project phase 5 (CMIP5) historical experiments. The results show that FIO-ESM v1.0 suffers from similar common problems to other CMIP5 models, including an eastward shift in the central locations of El Niño, adopting a regular period of roughly 3 years, addressing excessively high amplitude, spurious eastward propagation of El Niño events, and Aborted El Niño events. El Niño composite and mixed layer heat budget analyses indicate that these simulation biases are mainly associated with the mean state biases, including a warm Sea Surface Temperature (SST) bias for the central-eastern Pacific, a cold SST bias for the western and central Pacific, seasonal cycles of SST of the equatorial eastern Pacific, and weaker trade winds. Weaker SST-cloud-shortwave radiation feedback in La Niña events than in El Niño events is what creates spurious ENSO amplitude symmetry in the model. We suggest that the improvement of El Niño simulations may be realized by focusing on the mean state and SST-cloud-shortwave radiation feedback in the tropical region. Specifically, further incremental improvements in the mean state of the tropical Pacific should constitute the first step to realizing more accurate ENSO simulation.

Light absorption by marine cyanobacteria affects tropical climate mean state and variability

Abstract. Observations indicate that positively buoyant marine cyanobacteria, which are abundant throughout the tropical and subtropical ocean, have a strong local heating effect due to light absorption at the ocean surface. How these local changes in radiative heating affect the climate system on the large scale is unclear. We use the Max Planck Institute Earth System Model (MPI-ESM), include light absorption by cyanobacteria, and find a considerable cooling effect on tropical sea surface temperature (SST) in the order of 0.5 K on a climatological timescale. This cooling is caused by local shading of subtropical subsurface water by cyanobacteria that is upwelled at the Equator and in eastern boundary upwelling systems. Implications for the climate system include a westward shift of the Walker circulation and a weakening of the Hadley circulation. The amplitude of the seasonal cycle of SST is increased in large parts of the tropical ocean by up to 25 %, and the tropical Pacific interannual variability is enhanced by approx. 20 %. This study emphasizes the sensitivity of the tropical climate system to light absorption by cyanobacteria due to its regulative effect on tropical SST. Generally, including phytoplankton-dependent light attenuation instead of a globally uniform attenuation depth improves some of the major model temperature biases, indicating the relevance of taking this biophysical feedback into account in climate models.

Observed Seasonal Variations of the Upper Ocean Structure and Air‐Sea Interactions in the Andaman Sea

AbstractThe Andaman Sea (AS) is a poorly observed basin, where even the fundamental physical characteristics have not been fully documented. Here the seasonal variations of the upper ocean structure and the air‐sea interactions in the central AS were studied using a moored surface buoy. The seasonal double‐peak pattern of the sea surface temperature (SST) was identified with the corresponding mixed layer variations. Compared with the buoys in the Bay of Bengal (BOB), the thermal stratification in the central AS was much stronger in the winter to spring, when a shallower isothermal layer and a thinner barrier layer were sustained. The temperature inversion was strongest from June to July because of substantial surface heat loss and subsurface prewarming. The heat budget analysis of the mixed layer showed that the net surface heat fluxes dominated the seasonal SST cycle. Vertical entrainment was significant from April to July. It had a strong cooling effect from April to May and a striking warming effect from June to July. A sensitivity experiment highlighted the importance of salinity. The AS warmer surface water in the winter was associated with weak heat loss caused by weaker longwave radiation and latent heat losses. However, the AS latent heat loss was larger than the BOB in summer due to its lower relative humidity.

Projected sea surface temperatures over the 21st century: Changes in the mean, variability and extremes for large marine ecosystem regions of Northern Oceans

Global climate models were used to assess changes in the mean, variability and extreme sea surface temperatures (SSTs) in northern oceans with a focus on large marine ecosystems (LMEs) adjacent to North America, Europe, and the Arctic Ocean. Results were obtained from 26 models in the Community Model Intercomparison Project Phase 5 (CMIP5) archive and 30 simulations from the National Center for Atmospheric Research Large Ensemble Community Project (CESM-LENS). All of the simulations used the observed greenhouse gas concentrations for 1976–2005 and the RCP8.5 “business as usual” scenario for greenhouse gases through the remainder of the 21st century. In general, differences between models are substantially larger than among the simulations in the CESM-LENS, indicating that the SST changes are more strongly affected by model formulation than internal climate variability. The annual SST trends over 1976–2099 in the 18 LMEs examined here are all positive ranging from 0.05 to 0.5°C decade–1. SST changes by the end of the 21st century are primarily due to a positive shift in the mean with only modest changes in the variability in most LMEs, resulting in a substantial increase in warm extremes and decrease in cold extremes. The shift in the mean is so large that in many regions SSTs during 2070–2099 will always be warmer than the warmest year during 1976–2005. The SST trends are generally stronger in summer than in winter, as greenhouse gas heating is integrated over a much shallower climatological mixed layer depth in summer than in winter, which amplifies the seasonal cycle of SST over the 21st century. In the Arctic, the mean SST and its variability increases substantially during summer, when it is ice free, but not during winter when a thin layer of ice reforms and SSTs remain near the freezing point.

A model study of the seasonality of sea surface temperature and circulation in the Atlantic North-eastern Tropical Upwelling System

The climatological seasonal cycle of the sea surface temperature (SST) in the north-eastern tropical Atlantic (7-25°N, 26-12°W) is studied using a mixed layer heat budget in a regional ocean general circulation model. The region, which experiences one of the larger SST cycle in the tropics, forms the main part of the Guinea Gyre. It is characterized by a seasonally varying open ocean and coastal upwelling system, driven by the movements of the intertropical convergence zone (ITCZ). The model annual mean heat budget has two regimes schematically. South of roughly 12°N, advection of equatorial waters, mostly warm, and warming by vertical mixing, is balanced by net air-sea flux. In the rest of the domain, a cooling by vertical mixing, reinforced by advection at the coast, is balanced by the air-sea fluxes. Regarding the seasonal cycle, within a narrow continental band, in zonal mean, the SST early decrease (from September, depending on latitude, until December) is driven by upwelling dynamics off Senegal and Mauritania (15°-20°N), and instead by air-sea fluxes north and south of these latitudes. Paradoxically, the later peaks of upwelling intensity (from March to July, with increasing latitude) essentially damp the warming phase, driven by air-sea fluxes. The open ocean cycle to the west, is entirely driven by the seasonal net air-sea fluxes. The oceanic processes significantly oppose it, but for winter north of ~18°N. Vertical mixing in summer-autumn tends to cool (warm) the surface north (south) of the ITCZ, and advective cooling or warming by the geostrophic Guinea Gyre currents and the Ekman drift. This analysis supports previous findings on the importance of air-sea fluxes offshore. It mainly offers quantitative elements on the modulation of the SST seasonal cycle by the ocean circulation, and particularly by the upwelling dynamics. Keywords: SST, upwelling, circulation, heat budget, observations, modeling