Sea Surface Temperature Difference Research Articles

Climate models disagree on the sign of total radiative feedback in the Arctic

Climate feedbacks have been found to strongly impact the observed amplified Arctic warming. However, Arctic amplification is modeled with a wide spread which partly arises from intermodel differences of the various feedbacks. To explain the spread in modeled Arctic warming, feedback uncertainties and their origins are investigated in 13 climate models in an experiment with abruptly quadrupled CO2. While intermodel differences in the cloud feedback, being strongest in the Tropics, have been found to determine the spread of global mean effective climate sensitivity, we find that in the Arctic the cloud feedback is not responsible for the spread of Arctic warming as its contribution is too small. Instead, the spread of Arctic warming is explained by differing estimates of surface albedo and Planck feedbacks which show the largest intermodel differences. Our results indicate that these uncertainties not only arise from different degrees of simulated Arctic warming but also are partly related to the large differences in initial sea ice cover and surface temperatures which contribute to the increased spread in estimated warming compared to lower latitudes. Further investigations of feedback dependencies to the base state are needed to constrain the impact of initial uncertainties and to obtain robust results. The most significant distinction between models is the sign of the total feedback parameter. While all models investigated here simulate a negative global mean total feedback, only half of them also show negative Arctic feedbacks which implies that Arctic local feedbacks alone suffice to stably adjust Arctic surface temperatures in response to a radiative perturbation. The other half exhibits positive total Arctic feedbacks indicating local runaway systems which need to be balanced by decreased meridional heat transports. Whether or not a model features such a behaviour depends upon the strength of the simulated positive surface albedo versus the negative Planck feedback.

Multiproxy Reduced‐Dimension Reconstruction of Pliocene Equatorial Pacific Sea Surface Temperatures

AbstractA controversial aspect of the Pliocene climate system is a posited permanent sea surface temperature (SST) distribution resembling that during El Niño events, which is largely inferred from sea surface temperatures reconstructed from several sites in the equatorial Pacific. We utilize a reduced‐dimension methodology on a compilation of previously published multiproxy (Mg/Ca, Uk′37, TEX86, and foraminifer assemblages) Pliocene SST records from the equatorial Pacific to reconstruct spatial and temporal snapshots of SST anomalies and a time series of Niño indices from 5 to 1 Ma. The use of multiple proxies increases the number of study sites and thereby improves the robustness of the reconstruction. We find that the early Pliocene equatorial Pacific was characterized by a reduced zonal SST difference due to minimal change in the west and extreme warmth in the east which peaked at 4.3 Ma. The intensity of this mean El Niño‐like SST state then gradually diminished toward modern conditions. We also use the Pliocene Niño 4 time series to estimate the past strength of Indian Summer Monsoon given the modern correlation of it to the Niño 4 index. Results indicate the monsoon was weaker throughout the study interval with weakest conditions (~37% less rainfall than modern) occurring at 4.3 Ma, congruent with regional proxy records. In summation, this reduced‐dimension approach spatially and temporally resolves the warm mean state of the Pliocene equatorial Pacific and has numerous applications to inferences of paleoclimate conditions in distal regions teleconnected to El Niño today.

Influence of global sea‐surface temperature on ultra‐low‐frequency variability in Indian summer monsoon rainfall

AbstractA multidecadal or ultra‐low‐frequency mode of variability in Indian summer monsoon rainfall (ISMR) with a spectral peak at nearly 67 years is identified using a nonparametric approach, namely, singular spectrum analysis. Not only does this mode modulate the seasonal mean rainfall over India, but also frequent occurrences of excess or below normal rainfall over India are favored by the phases of this mode. We show that 80% of all droughts occur during the negative phase of this mode, compared with 60% of all floods during its positive phase. Although the existence of this mode was reported in many previous studies, proper understanding of its exact nature and driving mechanism, and how it relates to global sea‐surface temperature (SST), is still not clear. Here, we show that the 67‐year variability in ISMR is associated with a SST mode of similar periodicity, which primarily exhibits a hemispheric SST difference, with the strongest signals over the northern Pacific and Atlantic. The positive phase of this SST mode induces low surface pressure over the northern Arabian Sea. Changes in surface pressure over the northern Arabian Sea govern changes in ISMR. The bridge between the SST mode and central Asian circulation is possibly established through the North Pacific Oscillation. The positive phase of this mode enhances the meridional temperature gradient over India, which acts to strengthen the tropical easterly jet, and subsequently the low‐level westerly jet over India. These lead to a negative surface pressure anomaly over the Indian subcontinent and an associated anomalous cyclonic circulation. The environment thus created is conducive to increased seasonal mean monsoon rainfall over India. The phase of the SST mode is remarkably similar to, and leading by 2–3 years, that of the multidecadal mode in ISMR up to the 1990s. However, the relationship weakens after the early 1990s.

Seasonal Rainfall Variability in Ethiopia and Its Long-Term Link to Global Sea Surface Temperatures

Investigating the influence of sea surface temperatures (SSTs) on seasonal rainfall is a crucial factor for managing Ethiopian water resources. For this purpose, SST and rainfall data were used to study a wide range of inhomogeneous areas in Ethiopia with uneven distribution of rainfall for both summer (1951–2015) and spring (1951–2000) seasons. Firstly, a preliminary subdivision of rainfall grid points into zones was applied depending on spatial homogeneity and seasonality of rainfall. This introduced new clusters, including nine zones for summer rainfall peak (July/August) and five zones for spring rainfall peak (April/May). Afterward, the time series for each zone was derived by calculating the rainfall averaged over grid points within the zone. Secondly, the oceanic regions that significantly correlated with the Ethiopian rainfall were identified through cross-correlations between rainfalls averaged over every homogeneous zone and the monthly averaged SST. For summer rainfall as a main rainy season, the results indicated that the Gulf of Guinea and southern Pacific Ocean had a significant influence on rainfall zones at a lag time of 5–6 and 6–7 months. Besides, for summer rainfall zones 8 and 9 at lag time 5–6 months, the common SST regions of the southern Pacific Ocean showed the opposite sense of positive and negative correlations. Thus, the difference in SSTs between the two regions was more strongly correlated (r ≥ 0.46) with summer rainfall in both zones than others. For the spring season, the results indicated that SST of the northern Atlantic Ocean had a strong influence on spring rainfall zones (3 and 5) at a lag time 6–7 months, as indicated by a significant correlation (r ≥ −0.40). Therefore, this study suggests that SSTs of southern Pacific and northern Atlantic oceans can be used as effective inputs for prediction models of Ethiopian summer and spring rainfalls, respectively.

Significant SST differences between peak MIS5 and MIS1 along the low-latitude western North Pacific margin

The peak period of marine isotope stage 5 (MIS5e) is the most recent warm period largely comparable to the present interglacial, marine isotope stage 1 (MIS1). The spatial variations in sea surface temperature (SST) between MIS5e and MIS1 can reveal the important differences in the effects of insolation and oceanographic conditions between the two warm periods, which in turns help refine global climate models. In order to quantify the differences, this study calculated the SST for the peak periods of MIS5e (c. 128-113 ka BP) and MIS1 (c. 8-3 ka BP) along the low-latitude western North Pacific margin (18 oN to 26 oN). Together with the previously published data from the South China Sea (9 oN to 19 oN), the results indicate a generally northwards decreasing trend in the two interglacial periods. This latitudinal SST trend in both peak MIS 1 and MIS 5e can be attributed to the strong influence of ocean currents in the studied region. Secondly, the average SST of peak MIS5e is 1.3 ± 0.2 °C higher than that of peak MIS1, suggesting a higher level of insolation during the previous interglacial. However, the above general pattern is complicated by the near-shore and offshore difference in the effects of winter monsoon on oceanic conditions around 20–22 oN. The coastal upwelling near 26 oN during peak MIS5e reduced the SST, whilst the SST was raised as the upwelling ceased during peak MIS1. Finally, the SSTs of the two warm periods are significantly higher than the present SST from 20 oN northwards, implying the influence of winter monsoon cold current in the Taiwan Strait.

The relationship between monsoon and sea surface temperature in the western part of Aceh Waters, Indonesia

The western part of Aceh waters is part of the eastern Indian Ocean. This waters is a dynamic region where there is differences in sea surface temperature (SST) and significant chlorophyll a concentrations between the southwest (SW) monsoon (June-September) and the northeast (NE) monsoon (December-February). Analysis of SST and chlorophyll-a concentration were used to determine upwelling events in the region. We found that SST in the NE monsoon is lower than that of in the SW monsoon.

A Definition of Rapid Weakening for Tropical Cyclones Over the Western North Pacific

AbstractThe statistical characteristics of rapid weakening (RW) tropical cyclones over the western North Pacific are explored from 1988 to 2017. The RW is defined as approximately the 95th percentile of all 24‐hr over‐water weakening rates, corresponding to a 40 kt (20.6 m/s) or greater decrease in the maximum surface wind over a 24‐hr period. Statistical analysis suggests that RW tropical cyclones tend to possess higher intensities and faster translation than non‐RW tropical cyclones. Relative to the non‐RW cases, the RW cases occur in regions with a stronger meridional sea surface temperature (SST) gradient and smaller SST. The SST difference between RW and non‐RW cases is amplified during the weakening phase. Strong vertical wind shear plays a crucial role in leading to the RW events, while the contribution of midlevel dry‐air intrusion is found to be not statistically important in the western North Pacific basin.

Regional patterns in shallow water invertebrate assemblages on offshore oil and gas platforms along the Pacific continental shelf

We explored biogeographical and local patterns in the composition of shallow water (≤18 m depth) invertebrate assemblages inhabiting California offshore oil and gas platforms using multivariate analysis of diver- conducted photographic data collected from 23 platforms in 2013–2014. We evaluated the potential importance of sea surface temperature (SST) and other physical and biological factors in driving observed patterns in these assemblages. Prior to this analysis, platforms were grouped into four regions based on local differences in annual mean SST. The composition of invertebrate assemblages varied significantly among the four regions, reflecting differences in the relative abundances of certain anemone, bryozoan, sponge, and bivalve taxa. However, invertebrate assemblages varied idiosyncratically among platforms within a region. Variation in platform assemblages was associated with SST across regions; however, assemblages of platforms in the southeast Santa Barbara Channel were distinct due to the high cover of a non-native bryozoan, Watersipora subatra (Ortmann, 1890). The existence of geographical patterns in the composition of platform invertebrate assemblages and the colonization of one platform by a native bryozoan with southern affinities during elevated SST of 2014–2015 suggest that these assemblages may be useful over broad spatial scales as barometers of short- and longer-term changes in ocean climate. However, over smaller spatial scales, the idiosyncratic differences in invertebrate assemblages among platforms within regions indicates that these assemblages would have to be considered on a platform-by-platform basis under various decommissioning scenarios.

Prediction of Sea Surface Temperature in the South China Sea by Artificial Neural Networks

Sea surface temperature (SST) significantly affects the processes of air–sea interactions, and, thus, forms an important indicator of climate changes. In SST predictions, the approach of artificial neural networks (ANNs) is data-driven, unlike that of the numerical models, which are physics-based. In this letter, Operational SST and Ice Analysis (OSTIA) data set were used for training ANN models and verifying prediction results. Typically, time series SST data of a certain period were directly used for ANN’s training. To reduce the prediction errors caused by SST variations, the authors propose to separate SST time series data into climatological monthly mean and monthly anomaly data sets and construct two neural network models. The combination of these two models gives the final SST prediction results. This method was used for 12-month lead time SST prediction in the South China Sea. The average bias and standard deviation between the predicted SST and OSTIA SST are −0.16 °C and 0.37 °C, respectively. The percentage of SST difference between the predicted SST and OSTIA SST, within ±0.5 °C and ±1 °C, is 71.24% and 95.22%, respectively. The results indicate that the proposed training method gives good prediction accuracy.

Seasonal and inter-annual variability of net primary production in the NW Iberian margin (1998–2016) in relation to wind stress and sea surface temperature

Seasonal and inter-annual variability of satellite-derived net primary production (NPP) in the NW Iberian margin and its relationship with the offshore Ekman transport (-Qx) and a variety of sea surface temperature (SST) indices have been examined over the period 1998–2016. Seasonality explained about 55% of NPP variability over the shelf and the adjacent ocean. Maximum NPP rates occurred by May in the adjacent ocean, and were delayed until July over the shelf. The excess production (ΔNPP) over the shelf compared to the ocean domain represented 0.45 ± 0.02 g C m−2 d−1 or 37 ± 2% of the total NPP and peaked in August, in between the maximum -Qx and the maximum SST difference between the shelf and the adjacent ocean (ΔSST). During the upwelling season, the inter-annual variability of NPP in the adjacent ocean correlated positively with the spring stratification (SSTstr) and the average -Qx over the upwelling season and ΔNPP correlated inversely with ΔSST. Conversely, during the downwelling season, ΔNPP correlated with the average stratification (SSTdown) over the downwelling season. The rates of change of NPP with the climate-related variables (-Qx, ΔSST, SSTstr, SSTdown), obtained from these regressions, may be used to test the sensitivity of the NW Iberian upwelling productivity to climate change.

Properties of the Frequency Spectra of the Sea Surface and Land Surface Air Temperature Anomalies in a Simple Stochastic Climate Model with Fluctuating Parameters

The frequency properties of the spectra of sea surface temperature (SST) and land surface air temperature (SAT) anomalies are analyzed based on a simple energy-balance climate model taking into account the fluctuations of the radiation balance, the latent and sensible heat flux, and the near-surface wind velocity in two particular cases: when the statistical properties of the model parameters correspond to white noise (small-scale and mesoscale subintervals) and the combined case when the properties of the synoptic subinterval of these parameters are taken into account in the SAT block. It is found that, in the first case, the spectra have no features, while, in the second case, the spectra contain selected frequencies in the synoptic and low-frequency intervals. The dependence of their frequencies on the model parameters is analyzed. The properties of the standard deviations of SST and SAT anomalies are investigated.

Short-Term Variation of the Surface Flow Pattern South of Lombok Strait Observed from the Himawari-8 Sea Surface Temperature

Spatial and temporal information on oceanic flow is fundamental to oceanography and crucial for marine-related social activities. This study attempts to describe the short-term surface flow variation in the area south of the Lombok Strait in the northern summer using the hourly Himawari-8 sea surface temperature (SST). Although the uncertainty of this temperature is relatively high (about 0.6 ∘ C), it could be used to discuss the flow variation with high spatial resolution because sufficient SST differences are found between the areas north and south of the strait. The maximum cross-correlation (MCC) method is used to estimate the surface velocity. The Himawari-8 SST clearly shows Flores Sea water intruding into the Indian Ocean with the high-SST water forming a warm thermal plume on a tidal cycle. This thermal plume flows southward at a speed of about 2 m / s . The Himawari-8 SST indicates a southward flow from the Lombok Strait to the Indian Ocean, which blocks the South Java Current flowing eastward along the southern coast of Nusa Tenggara. Although the satellite data is limited to the surface, we found it useful for understanding the spatial and temporal variations in the surface flow field.

Variability and Predictability of North Atlantic Hurricane Frequency in a Large Ensemble of High-Resolution Atmospheric Simulations

AbstractVariability of North Atlantic annual hurricane frequency during 1951–2010 is studied using a 100-member ensemble of climate simulations by a 60-km atmospheric general circulation model that is forced by observed sea surface temperatures (SSTs). The ensemble mean results well capture the interannual-to-decadal variability of hurricane frequency in best track data since 1970, and suggest that the current best track data might underestimate hurricane frequency prior to 1966 when satellite measurements were unavailable. A genesis potential index (GPI) averaged over the main development region (MDR) accounts for more than 80% of the SST-forced variations in hurricane frequency, with potential intensity and vertical wind shear being the dominant factors. In line with previous studies, the difference between MDR SST and tropical mean SST is a useful predictor; a 1°C increase in this SST difference produces 7.05 ± 1.39 more hurricanes. The hurricane frequency also exhibits strong internal variability that is systematically larger in the model than observations. The seasonal-mean environment is highly correlated among ensemble members and contributes to less than 10% of the ensemble spread in hurricane frequency. The strong internal variability is suggested to originate from weather to intraseasonal variability and nonlinearity. In practice, a 20-member ensemble is sufficient to capture the SST-forced variability.

A Moist Conceptual Model for the Boundary Layer Structure and Radiatively Driven Shallow Circulations in the Trades

AbstractA conceptual model is developed to analyze how radiative cooling and the effect of moisture and shallow convection modify the boundary layer (BL) structure and the strength of mesoscale shallow circulations. The moist BL allows for a convective mass flux to modify the BL mass balance, which enhances inversion entrainment compared to a dry case and acts as a moisture valve to the BL. The convective mass flux is found to be insensitive to the applied radiative cooling and in the absence of heterogeneities cloud-free conditions exist only for unusual large-scale forcings. The model is able to explain the moderate range of BL heights and humidities observed in the trades. In a two-column setup, differential radiative BL cooling causes a pressure difference, which drives a BL flow from the cold and moist column to the warm and dry column and couples them dynamically. The small inversion buoyancy jump of the moist BL yields a stronger BL flow of 4 m s−1 instead of 1 m s−1 in the dry case. For typical conditions of the subsidence-dominated tropical oceans, a radiatively driven shallow circulation is stronger than one driven by sea surface temperature (SST) gradients. While the strength of the SST-driven circulation decreases with decreasing SST difference, the radiatively driven circulation is insensitive to the radiative BL cooling difference. In both cases, convection is suppressed in the descending branch of the shallow circulation and enhanced in the ascending branch, resembling patterns of organized shallow convection.

The diversity of La Niña decay and the corresponding spring and summer precipitation anomalies over eastern China

AbstractThe present study investigates the diversity of the La Niña decaying phase and the corresponding spring and summer precipitation anomalies over the eastern China. Based on the differences in sea surface temperature anomaly (SSTA) evolution during the La Niña decaying phase, 18 La Niña events in the period 1961–2016 are classified into three types—namely, the “persistent type” (P‐type), the “re‐intensified type” (R‐type), and the “fast‐decay type” (F‐type). Precipitation responses over eastern China during the decaying spring and summer of the three types of La Niña present significant differences. For the R‐type La Niña decaying spring, the enhanced precipitation appears over northeastern China but significant suppressed precipitation anomalies are observed elsewhere, particularly in Yellow River basin, the Yangtze River basin, and southeastern China. Significant negative precipitation anomaly appears over northeastern China in both P‐type and F‐type La Niña decaying spring. In the decaying summer, for P‐type La Niña, dry anomalies are apparent in southern and northern China. For R‐type La Niña, negative rainfall anomalies are notable in northeastern China, the Hetao region, and the middle reaches of the Yangtze River basin. For F‐type La Niña, significant negative rainfall anomalies are found over the Yangtze River basin and parts of northern China. The responses of the large‐scale circulation anomalies to the distinct SSTA patterns of the different types of La Niña are responsible for the diversity of rainfall anomalies over eastern China. The precipitation anomaly pattern in eastern China is closely associated with the different types of La Niña decay, and it is seasonal‐dependent. These two aspects should be taken into account when conducting seasonal predictions of spring and summer rainfall anomalies over eastern China using El Niño–Southern Oscillation as a predictor.

Assessing the extended-range predictability of the ocean model HYCOM with the REMO ocean data assimilation system (RODAS) in the South Atlantic

ABSTRACT The Brazilian Oceanographic Modeling and Observation Network (REMO, acronym for ‘Rede de Modelagem e Observação Oceanográfica’ in Portuguese) has developed the REMO Ocean Data Assimilation System (RODAS). It is based on an Ensemble Optimal Interpolation scheme applied into the Hybrid Coordinate Ocean Model (HYCOM). This study aims to investigate the extended-range predictability of the HYCOM + RODAS System over the western South Atlantic by using its analyses as initial condition for 48 hindcasts, each covering 30 days. The outputs were compared to persistence (no change from the initial condition) and to a model free run. The hindcasts had the lowest root mean square difference (RMSD) and highest correlation of sea surface temperature (SST) and sea level anomaly (SLA) at all lead times. By the 30th day, persistence RMSD reached 1.09°C and 0.08 m for SST and SLA, respectively, while the hindcast RMSD reached 0.46°C and 0.05 m. The free run RMSD was almost constant with an average of 0.88°C and 0.13 m. In the subsurface, hindcast RMSD increase was even lower. The results suggest that HYCOM + RODAS predictive skill extends for more than a month and the thermohaline state of the ocean was consistently improved with respect to the free model run.

Differences in the association of sea surface temperature—precipitating systems over the Bay of Bengal and the Arabian Sea during southwest monsoon season

The intriguing, but complex, association among sea surface temperature (SST) and different types of precipitating systems (deep and shallow) over the Bay of Bengal and the Arabian Sea has been elucidated utilizing 16 years of tropical rainfall measuring mission (TRMM) data. The characteristics and their convective forcing of these two seas are fundamentally different due to differences in SST. At a given SST, the occurrence of deeper (shallow) systems is higher (lower) over the Bay of Bengal than in the Arabian Sea. The occurrence of deeper systems increases with SST over both the seas till 30°C and decreases from 30 to 31°C. On the other hand, the occurrence of shallow systems is independent of SST over the Bay of Bengal while it decreases with rise in SST over the Arabian Sea. The prevalence of weaker convective available potential energy and drier mid‐troposphere over the Arabian Sea than over the Bay of Bengal is detrimental for cloud growth and is responsible for lower occurrence of deep systems and higher occurrence of shallow systems. The differences in mid‐tropospheric dynamics and moisture between the Arabian Sea and the Bay of the Bengal play a major role in the occurrence of deep and shallow systems.

Influence of sea surface temperature difference on the tropical cyclone genesis number in the Western North Pacific in August 1998 and August 2016

Influence of sea surface temperature difference on the tropical cyclone genesis number in the Western North Pacific in August 1998 and August 2016

Modelling Sea Surface Temperature (SST) in the Hudson Bay Complex Using Bulk Heat Flux Parameterization: Sensitivity to Atmospheric Forcing, and Model Resolution

ABSTRACTSea surface temperature (SST) from four Nucleus for European Modelling of the Ocean (NEMO) model simulations is analyzed to study the bulk flux parameterization to compute SST over the Hudson Bay Complex (HBC) for the summer months (August and September) from 2002 to 2009. The NEMO simulation was forced with two atmospheric forcing sets with different resolutions: the Coordinated Ocean-ice Reference Experiment, version 2 (COREv2), as the lower resolution and the Canadian Meteorological Centre’s Global Deterministic Prediction System Reforecasts (CGRF) as the higher resolution. The CGRF forcing is also implemented in the third and fourth runs using different runoff data and different NEMO resolutions (1/12° versus 1/4°). Results show that all four modelled SSTs followed observed SST patterns, with regional differences in SST bias between simulations with different atmospheric forcing. The SST differences are small between simulations forced with the same atmospheric forcing but with different model resolution or runoff. This implies that the model resolution and runoff have a small effect on the simulated SST in the HBC. Moreover, to better capture the effect of near-surface temperature (Tair) on simulated SST, we conducted three analyses using the Haney flux linearization formula. Results from these assessments did not indicate any direct influence on the model-simulated SSTs by Tair. Looking at the heat flux as a signature for SST showed that both averaged spatial distribution and time series of net heat flux produced by the three CGRF forcing simulations were higher than the net heat flux generated by the CORE 2 simulation. This was generally true for all four components of the total heat flux (sensible, latent, shortwave, and longwave) individually as well. Total heat flux in summer is governed by the shortwave heat flux, with values up to 120 W m−2 in August, and the longwave heat flux is the main contributor to the total heat flux differences. These heat flux differences lead to corresponding colder model SSTs for the CGRF runs and warmer SSTs for the CORE 2 simulations.

Relative roles of dynamic and thermodynamic processes in causing positive and negative global mean SST trends during the past 100 years

Global mean surface temperature (GMST) during 1910–2012 experienced four alternated rapid warming and warming hiatus phases. Such a temporal variation is primarily determined by global mean sea surface temperature (SST) component. The relative roles of ocean dynamic and thermodynamic processes in causing such global mean SST variations are investigated, using two methods. The first method is ocean mixed layer heat budget analysis. The budget diagnosis result shows that the thermodynamic processes dominate in the rapid warming phases, while the ocean dynamics dominate during the hiatus phases. The second method relies on the diagnosis of a simple equilibrium state model. This model captures well the horizontal distribution of SST difference between two warmer and cooler equilibrium states during either the rapid warming or hiatus phases. It is found that the SST difference during the rapid warming phases is primarily controlled by the increase of downward longwave radiation as both column integrated water vapor and CO2 increase during the phases. During the hiatus phases, the water vapor induced greenhouse effect offsets the CO2 effect, and the SST cooling tendency is primarily determined by the ocean dynamics over the Southern Ocean and tropical Pacific. The SST pattern associated with the Interdecadal Pacific Oscillation (IPO) might be responsible for the remote and local ocean dynamic responses through induced wind change.