Sea Surface Temperature Research Articles

Paleoclimate proxy records suggest reduced tropical Pacific zonal asymmetry under sustained global warming

Pronounced model-observation discrepancies in the changes of tropical Pacific zonal sea surface temperature gradient during the satellite era imply systematic model deficiencies. However, the relatively short high-quality instrumental record hampers robustly determining the response of tropical Pacific sea surface temperature to greenhouse gas increases. By adopting paleoclimate proxy records along with a series of climate model simulations, here we show that the zonal gradient is likely to decrease under sustained strong forcing. Paleoclimate proxy records indicate an overall increase of the zonal gradient over time, which has been accompanied by global-mean cooling associated with decreasing carbon dioxide concentrations. Model simulations are found to broadly reproduce the distinct contrast between warmer high carbon dioxide climates and the opposite climates, albeit with large inter-model discrepancy. The qualitative agreement among paleoclimate proxy records and modeled representations therefore lends some important credence to the sign of model-projected future tropical Pacific mean state change.

Comparing the influence of Atlantic Multidecadal Variability and spring soil moisture on European summer heat waves

Abstract In this work, we study and compare the influence of the Atlantic Multidecadal Variability (AMV) and spring soil moisture in Southern Europe on the duration and intensity of European summer heat waves. We study heat waves with return times of a few years and also propose a new methodological approach, return time maps, that allows us to study rare heat waves with return times of 10 or 50 years. We use the outputs from three climate models, namely IPSL-CM6A-LR, EC-Earth3, and CNRM-CM6-1, in which North Atlantic sea surface temperatures are restored towards the observed AMV anomalies. The three models give consistent results, with the exception of EC-Earth simulating a much greater influence of soil moisture. Our main conclusion is that spring soil moisture in Southern Europe is a slow driver of greater importance than the AMV for European summer heat waves, both in terms of the extension of the region of influence and in terms of amplitude. While the influence of the AMV concentrates over the very south of Europe, around the Mediterranean Basin, spring soil moisture influence extends over large parts of Europe. As might be expected, a positive AMV phase or low soil moisture generally induces hotter and longer heat waves. For more extreme events, the influences of the AMV and soil moisture increase, according to regional patterns that seem to be the same as for typical heat waves. However, confirming this statement would require datasets with more extreme events.

Evidence of eastern rockhopper penguin feeding on a key commercial arrow squid species

Cephalopods are crucial to the Southern Ocean ecosystem, connecting top predators with mid-trophic organisms, yet their ecology in the Pacific sector is not well understood. This research used stable isotope analysis to explore the habitat and trophic ecology of cephalopods found in the diet of eastern rockhopper penguins (Eudyptes chrysocome filholi) around Campbell Island, a New Zealand sub-Antarctic island. Eastern rockhopper penguins were used as biologic samplers, revealing some differences in cephalopod diversity and ecology between two breeding seasons—1986–87 and 2012–13—, and the squid Nototodarus sloanii, a commercially valuable species, was described for the first time in the 2012–13 season. Stable isotope values (δ13C and δ15N) for the squid species Moroteuthopsis ingens were consistent between seasons, indicating ecological stability, whereas the octopod species Octopus campbelli showed changes, suggesting shifts in habitat and feeding. Warmer oceanic temperatures in 2012–13 may have facilitated the emergence of N. sloanii on the diet of the eastern rockhopper penguins. These findings highlight potential changes in cephalopod biodiversity in the Pacific sector of the Southern Ocean, emphasizing the need for further research on ecological dynamics of this region.

Effect of Ice Number Concentration on the Evolution of Boundary Layer Clouds During Arctic Marine Cold‐Air Outbreaks

AbstractMarine cold‐air outbreaks (MCAOs) are crucial for Arctic Ocean heat loss, featuring convective cloud rolls that transition into convection cells downstream. Understanding factors controlling this transformation is the key for improving MCAO cloud representation in climate models. This study employs large‐eddy simulations to investigate how cloud ice number concentrations () affect cloud evolution using a case from the Cold‐Air Outbreaks in the Marine Boundary Layer Experiment (COMBLE) campaign. The simulations, performed in a Lagrangian framework following an air mass trajectory, are driven by ERA5 reanalysis data. Initially, all simulations produce similar cloud patterns, but higher leads to earlier breakup of cloud rolls. Between 4 and 10 hr, surface precipitation rates are similar across simulations, but precipitation initiates earlier, and the cloud‐base precipitation rates are higher when is higher. The stronger precipitation evaporation leads to increased stability of the boundary layer and reduced intensity of vertical mixing between the surface and cloud layer. An increased sink of cloud layer moisture via precipitation and decreased source through diminished vertical transport result in earlier cloud breakup in higher conditions. Simulations with different sea surface temperatures (SST) indicate that this cloud breakup mechanism remains valid for MCAOs of different strengths, although the cloud organization is more sensitive to SST changes in low environments. This work highlights the importance of accurate representations of ice processes in simulating MCAO clouds and suggests the need for observational constraints of ice nucleating particles and over the mixed‐phase cloud regimes.

Long-Term Prediction of Mesoscale Sea Surface Temperature and Latent Heat Flux Coupling Using the iTransformer Model

Mesoscale air–sea interaction, which is active in Western Boundary Currents (WBCs), has a non-negligible effect on mid-latitude climate variability. The analysis and prediction of the mesoscale air–sea interaction rely on high-resolution observation datasets and mesoscale-resolving climate models, which often require long processing times to estimate future changes and have several limitations. Therefore, in this study, we used a newly developed iTransformer model, which integrates mesoscale sea surface temperature anomaly (SSTa) and latent heat flux anomaly (LHFa) coupling coefficient data to predict future changes in SSTa–LHFa coupling. First, we individually trained the model using data corresponding to 1–15 past winters from ERA5 dataset. Thereafter, we used the trained model to predict SSTa–LHFa coupling coefficient for the next 10 winters. Compared with the predictions using only the coupling coefficient, the prediction yields 3.0% relative improvements when SST data were incorporated. The iTransformer model also showed the ability to reproduce the linear trend and mean value of mesoscale SSTa–LHFa coupling coefficients. Furthermore, we chose the optimal input length for each WBC and used the model to predict changes in mesoscale SSTa–LHFa coupling in the future. The results thus obtained were comparable to those obtained using mesoscale-resolving climate models, indicating that the iTransformer model showed satisfactory prediction performance. Therefore, it provides a novel pathway for exploring mesoscale air–sea interaction variations and predicting future climate change.

Computational analysis of wax deposition in deep-water pipelines using nuclear techniques

Wax deposition in oil pipelines is a problem that affects flow assurance because it restricts production and, in more extreme cases, causes pipeline blockages. This problem occurs more frequently in offshore environments, where most of Brazil's reservoirs are located and where the ocean temperature at great depths is around 5°C. Detecting the wax layer on the inside walls of pipelines at an early stage avoids unscheduled stoppages and major economic losses. Among the various methods and techniques found in the literature for monitoring wax deposition, nuclear techniques are distinguished by the fact that their use does not interfere with the physical integrity of the pipeline, by the non-intrusive and indirect (non-contact) mode of operation and, therefore, does not affect the oil transportation process. This paper presents a computational model using the Monte Carlo N-Particle 6 (MCNP6) code and the gamma radiation transmission profiling technique to detect the presence of wax on the inner walls of pipelines used for deepwater oil transportation. The results of this study show that the model can detect the presence of up to 5% wax (in relation to the internal radius of the pipeline) with an accuracy of 7.4% in pipelines used in deep waters.

Understanding the Relationship Between South Pacific Oscillation and ENSO

AbstractThe boreal summer South Pacific Oscillation (SPO), the dominant mode of atmospheric variability over the South Pacific, has been proposed as a potential precursor to the development of El Niño‐Southern Oscillation (ENSO). However, this study demonstrates that the SPO signal during the developing summer of ENSO events is primarily driven by the concurrent ENSO‐related tropical Pacific sea surface temperature anomalies, challenging its role as an independent predictor of ENSO. We further show that those winter ENSO events preceded by a summer SPO signal begin to develop before the SPO signal in the extratropics appear, and incorporating the summer SPO signal into ENSO persitence model does not add additional information for ENSO hindcast. The observational findings are further corroborated by evidence that the lead relationship of SPO over ENSO in climate models is mainly determined by their simulated ENSO teleconnection to SPO during summer.

Testing the reliability of global surface temperature reconstructions of the Last Glacial Cycle with pseudo-proxy experiments

Abstract. Reconstructions of past variations in the global mean surface temperature (GMST) are used to characterise the Earth system response to perturbations and to validate Earth system simulations. Beyond the instrumental period, reconstructions rely on local proxy temperature records and algorithms aggregating these records. Here, we propose to establish standards for evaluating the performance of such reconstruction algorithms. Our framework relies on pseudo-proxy experiments (PPEs). That is, we test the ability of an algorithm to reconstruct a simulated GMST, using artificially generated proxy data created from the same simulation. We apply the framework to an adapted version of the GMST reconstruction algorithm used in Snyder (2016) and the metadata of the synthesis of marine proxy records for the temperature of the last 130 kyr from Jonkers et al. (2020). We use an ensemble of four transient simulations of the Last Glacial Cycle (LGC) or the last 25 kyr for the pseudo-proxy experiments. Given the dataset and the algorithm, we find that the reconstruction is reliable for timescales longer than 4 kyr during the last 25 kyr. However, beyond 40 kyr BP, age uncertainty limits the reconstruction reliability to timescales longer than 15 kyr. For the long timescales, uncertainty on temperature anomalies is caused by a factor that re-scales near-global-mean sea surface temperatures to GMST, the proxy measurements, the specific set of record locations, and potential seasonal biases. Increasing the number of records significantly reduces all sources of uncertainty but the scaling. We also show that a trade-off exists between the inclusion of many records, which reduces the uncertainty on long timescales, and of only records with low age uncertainty, high accumulation rate, and high resolution, which improves the reconstruction of the short timescales. Finally, the method and the quantitative results presented here can serve as a basis for future evaluations of reconstructions. We also suggest future avenues to improve reconstruction algorithms and discuss the key limitations arising from the proxy data properties.

Using a region-specific ice-nucleating particle parameterization improves the representation of Arctic clouds in a global climate model

Abstract. Projections of global climate change and Arctic amplification are sensitive to the representation of low-level cloud phase in climate models. Ice-nucleating particles (INPs) are necessary for primary cloud ice formation at temperatures above approximately −38 °C and thus significantly affect cloud phase and cloud radiative effect (CRE). Due to their complex and insufficiently understood variability, INPs constitute an important modelling challenge, especially in remote regions with few observations, such as the Arctic. In this study, INP observations were carried out at Andenes, Norway, in March 2021. These observations were used as a basis for an Arctic-specific and purely temperature-dependent INP parameterization, which was implemented into the Norwegian Earth System Model (NorESM). This implementation results in an annual average increase in cloud liquid water path (CLWP) of 70 % for the Arctic and improves the representation of cloud phase compared to satellite observations. The change in CLWP in boreal autumn and winter is found to likely be the dominant contributor to the annual average increase in net surface CRE of 2 W m−2. This large surface flux increase brings the simulation into better agreement with Arctic ground-based measurements. Despite the fact that the model cannot respond fully to the INP parameterization change due to fixed sea surface temperatures, Arctic surface air temperature increases by 0.7 °C in boreal autumn. These findings indicate that INPs could have a significant impact on Arctic climate and that a region-specific INP parameterization can be a useful tool to improve cloud representation in the Arctic region.

When Simplification Leads to Ambiguity: A Look at Two Ocean Metrics for the Subpolar North Atlantic

AbstractThe AMOC FINGERPRINT and GYRE INDEX are two widely used metrics by the oceanographic community to assess whether northward ocean heat transport, and consequently temperature variability in the subpolar North Atlantic, is primarily governed by the Atlantic overturning circulation or the horizontal gyre circulation. Although these metrics are presented as distinct measures of subpolar ocean circulation, we contend that they are not unique indicators of the dynamics they are intended to represent. Instead, our analysis demonstrates that both metrics are essentially capturing variability in upper ocean heat content, which can result from a number of mechanisms. This conclusion, corroborated with direct overturning measurements from the OSNAP and RAPID programs, raises concerns about the use of these metrics to infer the dynamics responsible for past and projected changes in subpolar ocean temperatures.

Effects of zooplankton abundance on the spawning phenology of winter-spawning Downs herring (Clupea harengus).

We have investigated phenological shifts in autumn- and winter-spawning Atlantic herring (Clupea harengus) in the Eastern English Channel and the Southern North Sea (Downs component), in relation to temperature and the availability of potential zooplanktonic prey (Calanus finmarchicus, Calanus helgolandicus, Temora longicornis). A two-tiered approach building on the monthly distribution of commercial herring landings was developed, which consisted of, (1) calculating the timing and duration of spawning season based on estimated deviations from basic harmonic signals and, (2) analysing their inter-annual variations in relation to biotic (zooplankton abundance) and abiotic (temperature) environmental variables through time series analyses. The start, midpoint and ending of herring spawning season were increasingly delayed over the period 1999-2021, a process which was correlated with the abundance of Calanus finmarchicus. The resulting duration of spawning season slightly decreased. Direct effects of sea temperatures on any phenological metrics could not be clearly evidenced. Different ecological processes were likely involved in the start and ending of spawning season. Additional covariates (including size/age composition, the biotic and abiotic factors other than those examined in our study) could contribute to a better explanation of the phenological drift in Downs herring spawning.

Spatial Distribution of Illex argentinus in Different Life Stages of Mesoscale Eddies in Patagonian Waters

Mesoscale eddies are known to influence the abundance and distribution of oceanic cephalopods. However, little is known about these effects in the southwest Atlantic Ocean. Therefore, this study analyzed the variations in environmental conditions and the resource abundance, spatial distribution, and habitat suitability of Illex argentinus within different life stages of cyclonic (CE) and anticyclonic (AE) eddies in Patagonian waters. From a comparison of squid abundance between CEs and AEs at each life stage, it was found that I. argentinus gradually increased in abundance after eddy formation, that abundance peaked during eddy maturation and that it subsequently decreased during the eddies’ decay phase. Spatially, squid resources in AEs were primarily concentrated in the northwest and southeast peripheral regions of the eddy, while in CEs, resources were more concentrated in the outer regions, on the western side of the eddy. Environmental factor analysis revealed that sea surface temperature (SST) and temperature at 200 m depth (T200m) in both CEs and AEs reached their lowest values during the intensification and maturation phases of the eddies. Chlorophyll a (Chl-a) concentrations were significantly higher in CEs than in AEs from the formation to the maturation phase; however, during eddy decay, Chl-a concentrations were higher in AEs. According to a comparison of the suitability index (SI) for each environmental factor and the habitat suitability index (HSI) model, SISST, SIT200m, and SIChl-a in AEs increased and then decreased with eddy evolution, with optimal SI values occurring during the intensification phase. In CEs, SISST and SIT200m also increased and then decreased, with optimal SISST and SIT200m occurring during the intensification and maturation phases, respectively, with little variation in SIChl-a across the life cycle of CEs. The HSI in both types of eddies gradually increased from the formation phase, reached a peak during maturation, and significantly decreased during eddy decay. Overall, this study indicated that habitat suitability and resource abundance for I. argentinus were highest during the maturation phase of the eddies.

Detection of the Relationship Between the Inverse Variations of Sea Ice in the Okhotsk–Bering Sea During Spring and the 11‐Year Solar Cycle

ABSTRACTThe 11‐year solar cycle is a stable external forcing factor for the Earth system. However, its influence on decadal climate variability, including sea ice, remains uncertain. This study statistically analyses spring sea ice concentration (SIC) and annual sunspot numbers (SSNs) from 1960 to 2021, revealing a significant inverse correlation between the 11‐year solar activity cycle and spring sea ice variability in the Okhotsk Sea and Bering Sea. During solar maximum years, sea ice increases in the Okhotsk Sea while decreasing in the eastern Bering Sea. Further analysis shows that the spring sea ice concentration difference (SICD) index correlates closely with the preceding winter Pacific Meridional Mode (PMM) modulated by the 11‐year solar cycle. This suggests that solar activity may influence east–west sea ice variability in the North Pacific during spring through its impact on the winter PMM. Atmospheric circulation and numerical simulation results indicate that during high‐solar‐activity years in winter, changes in stratospheric ozone concentration lead to variations in stratospheric temperatures. This strengthens zonal westerlies in the subtropical stratosphere and troposphere. The propagation of planetary waves from the stratosphere to the mid‐ and high‐latitude troposphere converges over the Bering Sea, creating an easterly anomaly. This convergence stimulates a high pressure and a low pressure to its south, forming a pattern resembling the PMM in the North Pacific during winter. The sea surface temperature (SST) anomalies linked to the winter PMM persist into spring, influencing sea ice at high latitudes in the North Pacific and causing the observed inverse sea ice changes in the Okhotsk and Bering Seas. This study highlights the significant modulating effect of solar activity on sea ice variability, offering insights for understanding Arctic climate change and predicting sea ice changes.

Global biogeography of N2-fixing microbes: nifH amplicon database and analytics workflow

Abstract. Marine dinitrogen (N2) fixation is a globally significant biogeochemical process carried out by a specialized group of prokaryotes (diazotrophs), yet our understanding of their ecology is constantly evolving. Although marine N2 fixation is often ascribed to cyanobacterial diazotrophs, indirect evidence suggests that non-cyanobacterial diazotrophs (NCDs) might also be important. One widely used approach for understanding diazotroph diversity and biogeography is polymerase chain reaction (PCR) amplification of a portion of the nifH gene, which encodes a structural component of the N2-fixing enzyme complex, nitrogenase. An array of bioinformatic tools exists to process nifH amplicon data; however, the lack of standardized practices has hindered cross-study comparisons. This has led to a missed opportunity to more thoroughly assess diazotroph diversity and biogeography, as well as their potential contributions to the marine N cycle. To address these knowledge gaps, a bioinformatic workflow was designed that standardizes the processing of nifH amplicon datasets originating from high-throughput sequencing (HTS). Multiple datasets are efficiently and consistently processed with a specialized DADA2 pipeline to identify amplicon sequence variants (ASVs). A series of customizable post-pipeline stages then detect and discard spurious nifH sequences and annotate the subsequent quality-filtered nifH ASVs using multiple reference databases and classification approaches. This newly developed workflow was used to reprocess nearly all publicly available nifH amplicon HTS datasets from marine studies and to generate a comprehensive nifH ASV database containing 9383 ASVs aggregated from 21 studies that represent the diazotrophic populations in the global ocean. For each sample, the database includes physical and chemical metadata obtained from the Simons Collaborative Marine Atlas Project (CMAP). Here we demonstrate the utility of this database for revealing global biogeographical patterns of prominent diazotroph groups and highlight the influence of sea surface temperature. The workflow and nifH ASV database provide a robust framework for studying marine N2 fixation and diazotrophic diversity captured by nifH amplicon HTS. Future datasets that target understudied ocean regions can be added easily, and users can tune parameters and studies included for their specific focus. The workflow and database are available, respectively, on GitHub (https://github.com/jdmagasin/nifH-ASV-workflow, last access: 21 January 2025; Morando et al., 2024c) and Figshare (https://doi.org/10.6084/m9.figshare.23795943.v2; Morando et al., 2024b).

Coral reef thermal microclimates mapped from the International Space Station

Abstract Satellite sea surface temperature (SST) is critical for describing marine environments. Traditional SST data, such as those provided by the Group for High Resolution Sea Surface Temperature (GHRSST) program, are valuable, but have a relatively coarse spatial resolution for mapping coral reef thermal environments. Hence, fine resolution SST from orbit would be of great utility to the coral reef research community and speed the pathway to an increased understanding of how, when, and where thermal stress afflicts individual reefs. Such data would support adaptive management, especially so for the design of marine protected areas. Flying aboard the International Space Station, the NASA ECOsystem Spaceborne Thermal Radiometer Experiment on Space Station (ECOSTRESS) instrument may already fill this niche with a spatial resolution 204 times finer than GHRSST. To evaluate ECOSTRESS thermal data over reef environments, we deployed 21 temperature loggers over three years across two reef sites in the Red Sea. We compared temperature retrievals from both the coarse resolution GHRSST and the fine resolution, experimental, ECOSTRESS, to this in-situ logger dataset. While temperature data from both orbital platforms correlated strongly with the logger recordings, only ECOSTRESS, with its 70-m pixels, could construct thermal microclimate maps capturing the dynamic temperature fluctuations experienced by our studied reefs. We contend that ECOSTRESS represents a significant advancement in the capability to monitor heat stress on reefs from orbit.

Linkage between Southeast and South Asian summer monsoons: Relative roles of the Pacific-Japan pattern and the El Niño-Southern Oscillation

Abstract The various regional summer monsoons over Asia have been known to be highly interactive, but their interrelationships are still under debate. The current study investigates the linkage between the South Asian summer monsoon (SASM) and the Southeast Asian summer monsoon (SEASM) and the involved physical mechanisms. A robust positive correlation is found between the first Empirical Orthogonal Function (EOF) modes of SASM and SEASM precipitations. However, asymmetric features emerge between the mutually-enhanced (ME) and mutually-weakened (MW) SEASM-SASM cases. Apparent Pacific-Japan (PJ) pattern occurs in the ME SEASM-SASM cases under a relatively weak sea surface temperature (SST) background, causing a southwest-northeast precipitation dipole with a positive center over the northern Bay of Bengal and a negative center over the eastern Arabian Sea and southern India induced by westerly anomalies with anticyclonic curvature associated with the anomalous heating over the tropical western North Pacific and cooling over the Maritime Continent. While in the MW SEASM-SASM cases, the El Niño-Southern Oscillation related SST anomalies (i.e. a transition from the equatorial eastern Pacific warming in winter to cooling in summer) are substantial, which cause simultaneous weakening of the first modes of SEASM and SASM through anomalous western North Pacific anticyclone induced by the Pacific SST anomalies and the capacitor effects of other tropical oceans. In addition, intensified diabatic heating over the Maritime Continent driven by the anomalous zonal circulation related to the eastern Pacific cooling can enhance the precipitation over the eastern Arabian Sea and southern India via the westward-propagating Rossby wave.

Sea Surface Temperature Forecasting Using Foundational Models: A Novel Approach Assessed in the Caribbean Sea

Sea surface temperature (SST) plays a pivotal role in air–sea interactions, with implications for climate, weather, and marine ecosystems, particularly in regions like the Caribbean Sea, where upwelling and dynamic oceanographic processes significantly influence biodiversity and fisheries. This study evaluates the performance of foundational models, Chronos and Lag-Llama, in forecasting SST using 22 years (2002–2023) of high-resolution satellite-derived and in situ data. The Chronos model, leveraging zero-shot learning and tokenization methods, consistently outperformed Lag-Llama across all forecast horizons, demonstrating lower errors and greater stability, especially in regions of moderate SST variability. The Chronos model’s ability to forecast extreme upwelling events is assessed, and a description of such events is presented for two regions in the southern Caribbean upwelling system. The Chronos forecast resembles SST variability in upwelling regions for forecast horizons of up to 7 days, providing reliable short-term predictions. Beyond this, the model exhibits increased bias and error, particularly in regions with strong SST gradients and high variability associated with coastal upwelling processes. The findings highlight the advantages of foundational models, including reduced computational demands and adaptability across diverse tasks, while also underscoring their limitations in regions with complex physical oceanographic phenomena. This study establishes a benchmark for SST forecasting using foundational models and emphasizes the need for hybrid approaches integrating physical principles to improve accuracy in dynamic and ecologically critical regions.

Movement behavior of a blue whale between the Galapagos Archipelago and the Frontal System off Baja California Peninsula

AbstractThe movement behavior of blue whales in the Eastern Tropical Pacific (ETP) is not well understood, especially regarding the migration of Northeast (NEP) and Southeast (SEP) Pacific populations. This study presents tracking data from a satellite‐tagged blue whale recorded between the Galapagos Islands and the Baja California Frontal System. A Bayesian state‐space model (BSAM) estimated the whale's movement trajectory, and a hidden Markov model (HMM) classified behavioral states. Environmental factors like sea surface temperature, chlorophyll‐a concentration, primary productivity, and mesoscale eddies were analyzed to identify ecological drivers. The whale displayed foraging behavior in areas with lower temperatures, higher productivity, and elevated chlorophyll levels, with movements influenced by cyclonic and anticyclonic eddies. These findings improve understanding of blue whale migration and the potential overlap between NEP and SEP populations in key tropical regions. They suggest that areas like the Galapagos and Costa Rica Thermal Dome may serve as ecological corridors, influenced by eddies.

Diagnosing the Factors That Contribute to the Intermodel Spread of Climate Feedback in CMIP6

Abstract The global surface temperature climate feedback parameter λ varies significantly across climate models, and its real-world value remains uncertain. Studies have found that the sea surface temperature (SST) response pattern and atmospheric model physics can each affect the climate feedback parameter in historical and idealized warming simulations. In this study, we design and analyze a series of the targeted atmospheric global climate model (AGCM) experiments to quantify how much the SST (both the warming pattern and the base climatology) and atmospheric model physics contributes to the intermodel spread of the climate feedback parameter and cloud feedback in phase 6 of the Coupled Model Intercomparison Project (CMIP6). We use three AGCMs, HiRAM, AM2.5, and AM4, developed in the Geophysical Fluid Dynamics Laboratory (GFDL), which span a wide range of feedbacks in response to uniform surface warming. The three GFDL models indicate that historical patterns of SST change systematically alter λ, supporting the hypothesized role for a “pattern effect” in historical climate sensitivity. However, we found that forcing one AGCM with the different CO2-induced SST warming patterns or model SST climatology from a suite of climate models from CMIP6 can only reproduce ∼10% the intermodel spread of CO2-induced λ, while the atmospheric model used determines the magnitude of λ (∼45%). This underscores the role of atmospheric model physics in altering λ, particularly the cloud-related schemes. In addition, we demonstrate that the nonlinear interaction between SST and AGCM has a nonnegligible role in affecting λ.

Spatiotemporal distribution of chlorophyll-a concentration in the south China sea and its possible environmental regulation mechanisms.

In this paper, the spatial and temporal distribution of chlorophyll-a (Chl-a) concentration in the South China Sea (SCS) and its major environmental regulator mechanisms were studied by using satellite remote sensing data sea surface temperature (SST), sea surface wind (SSW), and aerosol optical depth (AOD) spanning from January 2000 to December 2022. The results show that Chl-a in the SCS exhibit notable spatio-temporal variations: they peak in winter (∼0.234mgm-3) and autumn (∼0.156mgm-3), and decline in spring (∼0.144mgm-3) and summer (∼0.136mgm-3). Spatially, Chl-a near the coast and in upwelling areas are generally higher than those in offshore areas. A monthly average time series correlation analysis across the entire SCS shows that Chl-a significantly correlate with SST (R=-0.78, P<0.01) and SSW (R=0.78, P<0.01), and moderately correlate with AOD (R=0.29, P<0.01). The regulator of environmental factors also shows seasonal differences: during the winter monsoon period, Chl-a has the highest partial correlation with SSW (R=0.73, P<0.01), followed by SST (R=-0.55, P<0.01), and no significant partial correlation with AOD (R=0.14, P>0.05); during the summer monsoon period, Chl-a has the highest partial correlation with SST (R=-0.63, P<0.01), followed by AOD (R=0.40, P<0.01), and no significant partial correlation with SSW (R=0.12, P>0.05). A comprehensive analysis indicates that the mixing and upwelling processes regulated by the winter monsoon and SST exert a greater influence on nutrient variations. The enhanced mixing caused by the winter monsoon and the cold environment promote the growth of phytoplankton, leading to higher Chl-a concentrations in winter compared to other seasons. In contrast, the increased temperature in the summer monsoon period significantly weakens the mixing effect of wind speed and nutrients influx from deep layers to surface layers. Consequently, the external nutrient sourced from aerosol becomes crucial in determining Chl-a distribution, especially in oligotrophic regions near the southern SCS and the basin. However, in regions where other nutrient sources significantly contribute, such as the coastal areas influenced by seasonal upwelling, the contribution of aerosols is negligible.