An assessment of the possible future climatic impact of carbon dioxide increases based on a coupled one‐dimensional atmospheric‐oceanic model

Late Pliocene to early Pleistocene astronomically forced sea surface productivity and temperature variations in the Mediterranean

Influence of North American land processes on North Atlantic Ocean variability

Five upper ocean mixed layer models driven by ERA-Interim surface forcing are compared with a year of hydrographic observations of the upper 1000 m, taken at the Porcupine Abyssal Plain observatory site using profiling gliders. All the models reproduce sea surface temperature (SST) fairly well, with annual mean warm biases of 0.11 °C (PWP model), 0.24 °C (GLS), 0.31 °C (TKE), 0.91 °C (KPP) and 0.36 °C (OSMOSIS). The main exception is that the KPP model has summer SSTs which are higher than the observations by nearly 3°. Mixed layer salinity (MLS) is not reproduced well by the models and the biases are large enough to produce a non-trivial density bias in the Eastern North Atlantic Central Water which forms in this region in winter.All the models develop mixed layers which are too deep in winter, with average winter mixed layer depth (MLD) biases between 160 and 228 m. The high variability in winter MLD is reproduced more successfully by model estimates of the depth of active mixing and/or boundary layer depth than by model MLD based on water column properties. After the spring restratification event, biases in MLD are small and do not appear to be related to the preceding winter biases.There is a very clear relationship between MLD and local wind stress in all models and in the observations during spring and summer, with increased wind speeds leading to deepening mixed layers, but this relationship is not present during autumn and winter. We hypothesize that the deepening of the MLD in autumn is so strongly driven by the annual cycle in surface heat flux that the winds are less significant in the autumn. The surface heat flux drives a diurnal cycle in MLD and SST from March onwards, though this effect is much more significant in the models than in the observations.We are unable to identify one model as definitely better than the others. The only clear differences between the models are KPP’s inability to accurately reproduce summer SSTs, and the OSMOSIS model’s more accurate reproduction of MLS.

Trends in environmental computer applications

Zhang, K.; Jiang, T., and Huang, J., 2019. Spatial–temporal variation in sea surface temperature from Landsat time series data using annual temperature cycle. In: Jung, H.-S.; Lee, S.; Ryu, J.-H., and Cui, T. (eds.), Advances in Remote Sensing and Geoscience Information Systems of Coastal Environments. Journal of Coastal Research, Special Issue No. 90, pp. 58-65. Coconut Creek (Florida), ISSN 0749-0208.Sea surface temperature (SST) plays an important role in aquatic ecosystems and the biogeochemical cycle. Multi-temporal remote-sensing observations may be desirable alternatives to traditional in situ sensors for SST measurement. However, the frequently used low-to-moderate-resolution remote sensors usually cannot identify subtle SST variations in coastal areas due to the pixel radiance contamination caused by shoreline influences. For alleviating this problem, the SST of Jiaozhou Bay (JZB) between 1986 and 2017 was estimated by means of Landsat thermal infrared data and the single-channel retrieval algorithm. The retrieved results were validated by field-measured water temperature and bootstrap method. Then, the estimated SST was divided into five-year intervals and calculated the SST climatology for each period. With use of the annual temperature cycle fitting model, the time series data not only demonstrated the spatial–temporal variation of the water temperature of JZB but also effectively compensated for the lack of remote sensing data due to adverse weather in summer. The estimation results showed that the SST of JZB increased gently during the past 30 years, especially in coastal areas. The increase of SST near artificial facilities was evident, indicating the influence of urbanization and industrialization in coastal area. A correlation analysis of SST and meteorological factors revealed that air temperature influenced SST variation, especially in the central bay, whereas wind speed and precipitation had nearly no influence.

16 - Seasonal variability of sea surface temperature in Southern Indian coastal water using Landsat 8 OLI/TIRS images

The seasonal and interannual variations of the sea surface temperature (SST) above the Seychelles Dome (SD) are investigated using outputs from an OGCM. The SST warms from August to April and cools from May to July. The surface heat flux plays the most important role in the seasonal variation, and it is mostly due to shortwave radiation. The horizontal advection tends to warm the SST in austral winter owing to the southward Ekman heat transport associated with the Indian summer monsoon. The cooling by the vertical turbulent diffusion becomes most effective in austral summer owing to the thin mixed layer during that time. On the interannual time scale, the SST becomes anomalously warm (cool) when the SD is weak (strong). In contrast to the seasonal variation, the vertical diffusion plays the most important role and causes anomalous warming (cooling). This warming (cooling) is due to the anomalously warm (cold) water below the mixed layer as a result of the deeper (shallower) thermocline in response to ocean dynamics. Also, the cooling by the vertical diffusion becomes less (more) efficient, because the mixed layer is anomalously thick (thin). The horizontal advection contributes to the anomalous warming (cooling) due to the anomalous southward (northward) Ekman heat transport. On the other hand, the anomalous surface heat flux tends to cool (warm) the mixed layer, because the warming of the mixed layer by the shortwave radiation becomes less (more) efficient due to the anomalously thick (thin) mixed layer.

The Indian summer monsoon intraseasonal oscillations (MISOs) induce pronounced intraseasonal sea surface temperature (SST) variability in the Bay of Bengal (BoB), which has important feedbacks to atmospheric convection. An ocean general circulation model (OGCM) is employed to investigate the upper‐ocean processes affecting intraseasonal SST variability and its feedback to the MISO convection. In the BoB, the MISO induces intraseasonal SST variability predominantly through surface heat flux forcing with comparable contributions from shortwave radiation and turbulent heat flux, and to a much smaller extent through wind‐driven ocean mixed layer entrainment. The ocean salinity stratification, represented by mixed layer depth (MLD) and barrier layer thickness (BLT), has a strong control on SST but weak impact on convection of the MISO. The MLD is critical for the amplitude of SST response to various forcing processes, while the BLT mainly affects entrainment by determining the temperature difference between the mixed layer and the water below. From May to mid‐June, the shallow MLD and thin barrier layer greatly enhance intraseasonal SST anomalies, which can amplify convection fluctuations of the MISO through air‐sea interaction and leads to intense but short‐duration postconvection break spells. When either the MLD or the BLT is large, intraseasonal SSTs tend to be weak. Further investigation reveals that freshwater flux of the monsoon gives rise to the shallow MLD and thick barrier layer, and its overall effect on intraseasonal SSTs is a 20% enhancement. These results provide implications for improving the simulation and forecast of the MISO in climate models.

Makassar City in South Sulawesi (Indonesia) is located at a low elevation of about 0-25 meters, while the coastal area is only 1-5 meters above sea level and is composed of alluvial deposits. The western boundary is directly adjacent to the Makassar Strait. These conditions make Makassar City highly vulnerable to the impacts of ocean dynamics and coastline changes caused by erosion or sedimentation, posing significant threats to infrastructure and livelihoods. This study aims to quantify sea-level changes that potentially cause coastal disasters in Makassar by detecting temporal variations in sea surface temperature (SST) and coastline changes. This study utilized remote sensing technology from AQUA MODIS, Landsat 7 ETM+, and Landsat 8 OLI/TIRS. The in-situ sea temperature measurements were conducted using a conductivity-temperature-depth (CTD) hydrographic device. In addition, the coastline verification was performed using a traverse of a global positioning system (GPS) device. Image processing was done using the SST extraction and band ratio methods to detect sea surface temperatures and coastlines, respectively. According to the AQUA MODIS data, the maximum SST increased from 28.84°C to 30.69°C from 2004 to 2024 with the highest temperature occured in 2024. The increase of SST agreed to the increase of sea level and coastlines. The evidence of the coastline changes presented by sedimentation and erosion is about 3.47 hectares and 32.89 hectares, respectively. The geological factors that play a role in coastal sedimentation and erosion originate from river sedimentation supply and increased sea level.

A simple stochastic one-dimensional model of interannual mid-latitude sea surface temperature (SST) variability that can be solved analytically is developed. A novel two-season approach is adopted, with the annual cycle divided into two seasons denoted summer and winter. Within each season the mixed layer depth is constant, and the transition of the mixed layer from summer to winter and vice versa is discontinuous. SST anomalies are forced by random atmospheric heat fluxes, assumed to be constant within each season for simplicity, with linear damping to represent atmospheric feedback. At the start of summer the initial SST anomaly is set equal to that at the end of the previous winter, and at the start of winter the initial temperature anomaly is found by instantaneously mixing the summer mixed layer with the heat stored below in the deeper winter mixed layer, thereby explicitly taking into account the ‘re-emergence mechanism’. Two simple auto-regressive equations for the summer and winter SST anomalies are obtained that can be easily solved. Model parameters include seasonal damping coefficients, mixed layer depths and standard deviations of the atmospheric forcing. Analytic expressions for season-to-season correlation and variability and power spectra are used to explore and illustrate the effects of the parameters quantitatively. Among the results it is found that, with regard to winter-to-winter temperature correlation, the re-emergence pathway is more influential than persistence via the summer mixed layer when the winter layer is more than twice the depth of the summer layer. With regard to winter temperature variability, the effect of a deeper winter mixed layer is to decrease the sensitivity to surface forcing and thus decrease variability, but also to increase persistence via re-emergence and thus increase variance at multidecadal scales.

Distinct pattern of interannual variability in sea surface temperature (SST) in the South Pacific [i.e., the South Pacific subtropical dipole (SPSD)] is examined using outputs from a coupled general circulation model. The SPSD appears as the second empirical orthogonal function (EOF) mode of the SST anomalies in the South Pacific and is associated with a northeast–southwest-oriented dipole of positive and negative SST anomalies in the central basin. The positive and negative SST anomaly poles start to develop during austral spring, reach their peak during austral summer, and gradually decay afterward. Close examination of mixed-layer heat balance yields that the SST anomaly poles develop mainly because warming of the mixed layer by shortwave radiation is modulated by the anomalous mixed-layer thickness. Over the positive (negative) pole, the mixed layer becomes thinner (thicker) than normal and acts to enhance (reduce) the warming of the mixed layer by climatological shortwave radiation. This thinner (thicker) mixed layer may be related to the suppressed (enhanced) evaporation associated with the overlying sea level pressure (SLP) anomalies. Weaker-than-normal surface wind also contributes to the thinner mixed layer in the case of the positive pole. Furthermore, the SLP anomalies are linked with the geopotential height anomalies in the upper troposphere and are associated with a stationary Rossby wave pattern along the westerly jet in the midlatitudes. This suggests that the SLP anomalies that generate the SPSD are not locally excited but remotely induced signals.

Vertical and horizontal mixing processes in the ocean mixed layer determine sea surface temperature and temperature variability. Accordingly, simulating these processes properly is crucial in order to obtain more accurate climate simulations and more reliable future projections using an ocean general circulation model (OGCM). In this study, by using Modular Ocean Model version 4 (MOM4) developed by Geophysical Fluid Dynamics Laboratory, the upper ocean temperature and mixed layer depth were simulated with two different vertical mixing schemes that are most widely used and then compared. The resultant differences were analyzed to understand the underlying mechanism, especially in the Tropical Pacific Ocean where the differences appeared to be the greatest. One of the schemes was the so-called KPP scheme that uses K-Profile parameterization with nonlocal vertical mixing and the other was the N scheme that was rather recently developed based on a second-order turbulence closure. In the equatorial Pacific, the N scheme simulates the mixed layer at a deeper level than the KPP scheme. One of the reasons is that the total vertical diffusivity coefficient simulated with the N scheme is ten times larger, at maximum, in the surface layer compared to the KPP scheme. Another reason is that the zonal current simulated with the N scheme peaks at a deeper ocean level than the KPP scheme, which indicates that the vertical shear was simulated on a larger scale by the N scheme and it enhanced the mixed layer depth. It is notable that while the N scheme simulates a deeper mixed layer in the equatorial Pacific compared to the KPP scheme, the sea surface temperature (SST) simulated with the N scheme was cooler in the central Pacific and warmer in the eastern Pacific. We postulated that the reason for this is that in the central Pacific atmospheric forcing plays an important role in determining SST and so does a strong upwelling in the eastern Pacific. In conclusion, what determines SST is crucial in interpreting the relationship between SST and mixed layer depth.

Using sea surface temperature (SST) and wind speed retrieved by the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI), for the period of 1998–2003, we have studied the annual cycle of SST and confirmed the bimodal distribution of SST over the north Indian Ocean. Detailed analysis of SST revealed that the summer monsoon cooling (winter cooling) over the eastern Arabian Sea (Bay of Bengal) is more prominent than winter cooling (summer monsoon cooling). A sudden drop in surface short wave radiation by 57 W m−2 (74 W m−2) and rise in kinetic energy per unit mass by 24 J kg−1 (26 J kg−1) over the eastern Arabian Sea (Bay of Bengal) is observed in summer monsoon cooling period. The subsurface profiles of temperature and density for the spring warming and summer monsoon cooling phases are studied using the Arabian Sea Monsoon Experiment (ARMEX) data. These data indicate a shallow mixed layer during the spring warming and a deeper mixed layer during the summer monsoon cooling. Deepening of the mixed layer by 30 to 40 m with corresponding cooling of 2°C is found from warming to summer monsoon cooling in the eastern Arabian Sea. The depth of the 28°C isotherm in the eastern Arabian Sea during the spring warming is 80 m and during summer monsoon cooling it is about 60 m, while over the Bay of Bengal the 28°C isotherm is very shallow (35 m), even during the summer monsoon cooling. The time series of the isothermal layer depth and mixed layer depth during the warming phase revealed that the formation of the barrier layer in the spring warming phase and the absence of such layers during the summer cooling over the Arabian Sea. However, the barrier layer does exist over the Bay of Bengal with significant magnitude (20–25 m). The drop in the heat content with in first 50 m of the ocean from warming to the cooling phase is about 2.15 × 108 J m−2 over the Arabian Sea.

Remote forcing of sea surface temperature (SST) variations in the Indian Ocean during the course of El Nino- Southern Oscillation (ENSO) events is investigated using NCEP reanalysis and general circulation model (GCM) experiments. Three experiments are conducted to elucidate how SST variations in the equatorial Pacific influence surface flux variations, and hence SST variations, across the Indian Ocean. A control experiment is conducted by prescribing observed SSTs globally for the period 1950-99. In the second experiment, observed SSTs are prescribed only in the tropical eastern Pacific, while climatological SSTs are used elsewhere over the global oceans. In the third experiment, observed SSTs are prescribed in the tropical eastern Pacific, while a variable-depth ocean mixed layer model is used at all other ocean grid points to predict the SST. Composites of surface fluxes and SST over the Indian Ocean are formed based on El Nino and La Nina events during 1950-99. The surface flux variations in the eastern Indian Ocean in all three experiments are similar and realistic, confirming that much of the surface flux variation during ENSO is remotely forced from the Pacific. Furthermore, the SST anomalies in the eastern tropical Indian Ocean are well simulated by the coupled model, which supports the notion of an ''atmospheric bridge'' from the Pacific. During boreal summer and fall, when climatological winds are southeasterly over the eastern Indian Ocean, remotely forced anomalous easterlies act to increase the local wind speed. SST cools in response to increased evaporative cooling, which is partially offset by increased solar radiation associated with reduced rainfall. During winter, the climatological winds become northwesterly and the anomalous easterlies then act to reduce the wind speed and evaporative cooling. Together with increased solar radiation and a shoaling mixed layer, the SST warms rapidly. The model is less successful at reproducing the ENSO-induced SST anomalies in the western Indian Ocean, suggesting that dynamical ocean processes contribute to the east-west SST dipole that is often observed in boreal fall during ENSO events.

Teleconnections have traditionally been studied for the case of dry dynamical response to a given diabatic heat source. Important anomalies often occur within convective zones, for instance, in the observed remote response to El Niño. The reduction of rainfall and teleconnection propagation in deep convective regions poses theoretical challenges because feedbacks involving convective heating and cloud radiative effects come into play. Land surface feedbacks, including variations of land surface temperature, and ocean surface layer temperature response must be taken into account. During El Niño, descent and negative precipitation anomalies often extend across equatorial South America and the Atlantic intertropical convergence zone. Analysis of simulated mechanisms in a case study of the 1997/98 El Niño is used to illustrate the general principals of teleconnections occurring in deep convective zones, contrasting land and ocean regions. Comparison to other simulated events shows similar behavior. Tropospheric temperature and wind anomalies are spread eastward by wave dynamics modified by interaction with the moist convection zones. The traditional picture would have gradual descent balanced by radiative damping, but this scenario misses the most important balances in the moist static energy (MSE) budget. A small “zoo” of mechanisms is active in producing strong regional descent anomalies and associated drought. Factors common to several mechanisms include the role of convective quasi equilibrium (QE) in linking low-level moisture anomalies to free tropospheric temperature anomalies in a two-way interaction referred to as QE mediation. Convective heating feedbacks change the net static stability to a gross moist stability (GMS) M. The large cloud radiative feedback terms may be manipulated to appear as a modified static stability Meff, under approximations that are quantified for the quasi-equilibrium tropical circulation model used here. The relevant measure of Meff differs between land, where surface energy flux balance applies, and short time scales over ocean. For the time scale of an onsetting El Niño, a mixed layer ocean response is similar to a fixed sea surface temperature (SST) case, with surface fluxes lost into the ocean and Meff substantially reduced over ocean-enhancing descent anomalies. Use of Meff aids analysis of terms that act as the initiators of descent anomalies. Apparently modest terms in the MSE budget can be acted on by the GMS multiplier effect, which yields substantial precipitation anomalies due to the large ratio of the moisture convergence to the MSE divergence. Advection terms enter in several mechanisms, with the leading effects here due to advection by mean winds in both MSE and momentum balances. A Kelvinoid solution is presented as a prototype for how easterly flow enhances moist wave decay mechanisms, permitting relatively small damping terms by surface drag and radiative damping to produce the substantial eastward temperature gradients seen in observations and simulations and contributing to precipitation anomalies. The leading mechanism for drought in eastern equatorial South America is the upped-ante mechanism in which QE mediation of teleconnected tropospheric temperature anomalies tends to produce moisture gradients between the convection zone, where low-level moisture increases toward QE, and the neighboring nonconvective region. Over the Atlantic ITCZ, the upped-ante mechanism is a substantial contributor, but on short time scales several mechanisms referred to jointly as troposphere/SST disequilibrium mechanisms are important. While SST is adjusting during passive SST (coupled ocean mixed layer) experiments, or for fixed SST, heat flux to the ocean is lost to the atmosphere, and these mechanisms can induce descent and precipitation anomalies, although they disappear when SST equilibrates. In simulations here, cloud radiative feedbacks, surface heat fluxes induced by teleconnected wind anomalies, and surface fluxes induced by QE-mediated temperature anomalies are significant disequilibrium contributors. At time scales of several months or longer, remaining Atlantic ITCZ rainfall reductions are maintained by the upped-ante mechanism.