A Century of Ocean Warming on Florida Keys Coral Reefs: Historic In Situ Observations

Kwon, K.; Choi, B.-J., and Lee, S.-H., 2018. Assimilation of Different SST Datasets to a Coastal Ocean Modeling System in the Yellow and East China Sea. In: Shim, J.-S.; Chun, I., and Lim, H.S. (eds.), Proceedings from the International Coastal Symposium (ICS) 2018 (Busan, Republic of Korea). Journal of Coastal Research, Special Issue No. 85, pp. 1041–1045. Coconut Creek (Florida), ISSN 0749-0208.Global gridded gap-free sea surface temperature (SST) datasets were quantitatively evaluated using independent insitu datasets in the Yellow and East China Sea from September 2011 to February 2012. The assimilation effect of the four different SST datasets on a regional ocean modeling system was examined. The SST from the gridded SST datasets was compared with two ocean buoy SST data and bi-monthly routine hydrographic observation data in the Yellow Sea (YS). The root-mean-square differences (RMSDs) of the OISST, MGDSST, OSTIA, and MWIR SST datasets relative to the in-situ SST were 0.64, 0.53, 0.62, and 0.91°C, respectively. The RMSDs of SST were higher than 1°C for all datasets in the southeastern corner of the YS. Ocean circulation was simulated with a regional ocean model, and the SST data from the four SST datasets were assimilated. Assimilation of the SST to the ocean model improved the ocean current as well as temperature distribution. The daily mean simulated temperature was compared to the observed SST and vertical profiles of the temperature at the ocean buoys and hydrographic observation stations. After the assimilation of OISST, MGDSST, OSTIA and MWIR datasets, RMSDs of the simulated SST were 0.78, 0.92, 0.66 and 0.86°C, respectively, at the buoy stations. The RMSDs of the simulated subsurface temperature were 1.60, 1.67, 1.56 and 1.70°C, respectively, at the hydrographic observation stations. The simulated SSTs from the model with assimilation of the OSTIA and OISST datasets had relatively smaller RMSDs.

Climate sensitivity, defined as the global-mean surface temperature change due to a doubling of atmospheric CO2, is a key metric for quantifying the Earth system response to increasing greenhouse gases. Estimates of climate sensitivity vary widely, making it difficult for societies to prepare for the impacts of climate change. Uncertainty in climate sensitivity is driven primarily by uncertainty in how clouds will respond to warming. But how clouds respond to climate change depends strongly on the geographic pattern of warming: the so-called ‘pattern effect’. This recently-discovered phenomenon is crucial to narrowing uncertainty in climate projections, yet fundamental understanding of the processes underpinning the pattern effect is underdeveloped. In particular, the potential role of changes in atmospheric circulation as a crucial link between warming patterns and cloud feedbacks remains unclear.  Here we use a series of idealised GCM simulations and a moist static energy (MSE) framework to investigate the coupling between tropical sea surface temperature (SST) warming, circulation changes and cloud feedbacks. In the simulations the SST of different ‘patches’ of the tropical ocean are perturbed, resulting in strongly non-linear cloud responses. We demonstrate that the circulation response is also non-linear and closely coupled to the cloud response. Specifically, SST warming in the west Pacific leads to a reduction in ascent fraction – the proportion of the atmosphere that is ascending at 500 hPa – over the tropical ocean, associated with an increased top-of-atmosphere shortwave cloud radiative effect.  In contrast, SST warming in the east Pacific has little effect on ascent fraction. We develop a framework for estimating ascent fraction as a function of near-surface MSE, inclusive of an entraining-plume model to account for dry-air mixing into moist ascending air. We demonstrate how this framework can provide insight into both the circulation changes associated with patterned SST warming and the resulting cloud feedbacks. 

The seasonal delay of tropical rainfall is a robust feature under global warming. This study finds that the seasonal delay of tropical rainfall is much more pronounced under spatially patterned sea surface temperature (SST) warming compared to uniform SST warming. Through the lens of the atmospheric energetic framework, we show that the enhanced seasonal delay is primarily driven by the interhemispheric contrast in SST warming between the Northern and Southern Hemispheres, which intensifies the inter‐seasonal difference in cross‐equatorial atmospheric energy transport between transition seasons. The SST warming features are found to be crucial, characterized by both its seasonal cycle and annual mean. The former is closely related to the seasonal delay of SST, especially in the northern high latitude, while the latter is further demonstrated by an atmospheric model forced with the annual‐mean spatially patterned SST warming.

Accurate sea surface temperature (SST) datasets are critical to typhoon simulation/prediction, especially to the intensity forecast. In this study, four SST datasets were used to perform a series of experiments to examine the effects of different SST datasets and a cold SST feature on the simulation of typhoon Nangka (2015) using the Advanced Weather Research and Forecast model. Results show that the simulated typhoon intensity is very sensitive to the SST dataset used. The experiments with the SST dataset in which a cold SST feature to the south of the storm track was present/absent succeeded/failed to simulate the peak intensity and the subsequent rapid weakening of typhoon Nangka. Among the four datasets examined, only the SST dataset from the National Centers for Environmental Prediction Global Forecast System analysis captured the cold SST feature, which was likely induced by typhoon Chan‐Hom (2015) before the arrival of typhoon Nangka.

Simulations with the UCLA atmospheric general circulation model (AGCM) using two different global sea surface temperature (SST) datasets for January 1979 are compared. One of these datasets is based on Comprehensive Ocean-Atmosphere Data Set (COADS) (SSTs) at locations where there are ship reports, and climatology elsewhere; the other is derived from measurements by instruments onboard NOAA satellites. In the former dataset (COADS SST), data are concentrated along shipping routes in the Northern Hemisphere; in the latter dataset High Resolution Infrared Sounder (HIRS SST), data cover the global domain. Ensembles of five 30-day mean fields are obtained from integrations performed in the perpetual-January mode. The results are presented as anomalies, that is, departures of each ensemble mean from that produced in a control simulation with climatological SSTs. Large differences are found between the anomalies obtained using COADS and HIRS SSTs, even in the Northern Hemisphere where the datasets are most similar to each other. The internal variability of the circulation in the control simulation and the simulated atmospheric response to anomalous forcings appear to be linked in that the pattern of geopotential height anomalies obtained using COADS SSTs resembles the first empirical orthogonal function (EOF 1) in the control simulation. The corresponding pattern obtained using HIRS SSTs is substantially different and somewhat resembles EOF 2 in the sector from central North America to central Asia. To gain insight into the reasons for these results, three additional simulations are carried out with SST anomalies confined to regions where COADS SSTs are substantially warmer than HIRS SSTs. The regions correspond to warm pools in the northwest and northeast Pacific, and the northwest Atlantic. These warm pools tend to produce positive geopotential height anomalies in the northeastern part of the corresponding oceans. Both warm pools in the Pacific produce large-scale circulation anomalies with a pattern that resembles that obtained using COADS SSTs as well as EOF 1 of the control simulation; the warm pool in the Atlantic does not. These results suggest that the differences obtained with COADS SSTs and HIRS SSTs are mostly due to the differences in the datasets over the northern Pacific. There was a blocking episode near Greenland in late January 1979. Both simulations with warm SST anomalies over the northwest and northeast Pacific show a tendency toward increased incidence of North Atlantic blocking; the simulation with warm SST anomalies over the northwest Atlantic shows a tendency toward decreased incidence. These results suggest that features in both SST datasets that do not have a counterpart in the other dataset contribute signficantly to the differences between the simulated and observed fields. The results of this study imply that uncertainties in current SST distributions for the world oceans can be as important as the SST anomalies themselves in terms of their impact on the atmospheric circulation. Caution should be exercised, therefore, when linking anomalous circulation and SST patterns, especially in long-range prediction.

Most previous studies have reported a decrease in global tropical cyclone (TC) genesis frequency (TCGF) under anthropogenic warming. However, little attention has been drawn to the influence of sea surface temperature (SST) warming patterns on TCGF changes. Here, we investigate the impacts of three distinct SST warming patterns on global TCGF: uniform SST warming, nonuniform (El Niño-like) SST warming, and a combination of both. Results show that spatio-uniform SST warming has a limited impact on global TCGF, instead redistributing the TC genesis locations. Conversely, nonuniform SST warming significantly suppresses global TCGF. The combined warming produces a similar decrease in TCGF to nonuniform warming albeit with differences in spatial distribution. This indicates the dominant role of nonuniform SST warming in affecting TCGF and highlights the nonlinearity of the process. Further analysis shows that these differences in TCGF primarily stem from the distinct responses of tropical circulations to the three warming patterns.

The observed global-mean surface temperature (GST) has been warming in the presence of increasing atmospheric concentration of greenhouse gases, but its rise has not been monotonic. Attention has increasingly been focused on the prominent variations about the linear trend in GST, especially on interdecadal and multidecadal time scales. When the sea-surface temperature (SST) and the land- plus-ocean surface temperature (ST) are averaged globally to yield the global-mean SST (GSST) and the GST, respectively, spatial information is lost. Information on both space and time is needed to properly identify the modes of variability on interannual, decadal, interdecadal and multidecadal time scales contributing to the GSST and GST variability. Empirical Orthogonal Function (EOF) analysis is usually employed to extract the space–time modes of climate variability. Here we use the method of pair-wise rotation of the principal components (PCs) to extract the modes in these time-scale bands and obtain global spatial EOFs that correspond closely with regionally defined climate modes. Global averaging these clearly identified global modes allows us to reconstruct GSST and GST, and in the process identify their components. The results are: Pacific contributes to the global mean variation mostly on the interannual time scale through El Nino-Southern Oscillation (ENSO) and its teleconnections, while the Atlantic contributes strongly to the global mean on the multidecadal time scale through the interhemispheric mode called the Atlantic Multidecadal Oscillation (AMO). The Pacific Decadal Oscillation (PDO) has twice as large a variance as the AMO, but its contribution to GST is only 1/10 that of the AMO because of its compensating patterns of cold and warm SST in northwest and northeast Pacific. Its teleconnection pattern, the Pacific/North America (PNA) pattern over land, is also found to be self-cancelling when globally averaged because of its alternating warm and cold centers. The Interdecadal Pacific Oscillation (IPO) is not a separate mode of variability but contains AMO and PDO. It contributes little to the global mean, and what it contributes is mainly through its AMO component. A better definition of a Pacific low-frequency variability is through the IPO Tripole Index (TPI), using difference of averaged SST in different regions of the Pacific. It also has no contribution to the GSST and GST due to the PDO being its main component.

Comparison of long-term variability of Sea Surface Temperature in the Arabian Sea and Bay of Bengal

This paper addresses several hypotheses designed to explain why AOGCM simulations of future climate in the third phase of the Coupled Model Intercomparison Project (CMIP3) feature an intensified reduction of precipitation over the Meso-America (MA) region. While the drying is consistent with an amplification of the subtropical high pressure cells and an equatorward contraction of convective regions due to the “upped ante” for convection in a warmer atmosphere, the physical mechanisms behind the intensity and robustness of the MA drying signal have not been fully explored. Regional variations in sea surface temperature (SST) warming may play a role. First, SSTs over the tropical North Atlantic (TNA) do not warm as much as the surrounding ocean. The troposphere senses a TNA that is cooler than the tropical Pacific, potentially exciting a Gill-type response, increasing the strength of the North Atlantic subtropical high. Second, the warm ENSO-like state simulated in the eastern tropical Pacific could decrease precipitation over MA, as warm ENSO events are associated with drying over MA.The authors use the International Centre for Theoretical Physics (ICTP) AGCM to investigate the effects of these regional SST warming variations on the projected drying over MA. First, the change of SSTs [Special Report on Emissions Scenarios (SRES) A1B’s Twentieth-Century Climate in Coupled Model (A1B-20C)] in the ensemble average of the CMIP3 models is applied to determine if the ICTP AGCM can replicate the future drying. Then the effects of 1) removing the reduced warming over the TNA, 2) removing the warm ENSO-event-like pattern in the eastern tropical Pacific, and 3) applying uniform SST warming throughout the tropics are tested. The ICTP AGCM can reproduce the general pattern and amount of precipitation over MA. Simulations in which the CMIP3 A1B-20C ensemble-average SSTs are added to climatological SSTs show drying of more than 20% over the MA region, similar to the CMIP3 ensemble average. Replacing the relatively cooler SSTs over the TNA excites a Gill response consistent with an off-equatorial heating anomaly, showing that the TNA relative cooling is responsible for about 16% (31%) of the drying in late spring (early summer). The warm ENSO-like SST pattern over the eastern Pacific also affects precipitation over the MA region, with changes of 19% and 31% in March–June (MMJ) and June–August (JJA), respectively. This work highlights the importance of understanding even robust signals in the CMIP3 future scenario simulations, and should aid in the design and analysis of future climate change studies over the region.

A simple conceptual model of surface specific humidity change over land is described, based on the effect of increased moisture advection from the oceans in response to sea surface temperature (SST) warming. In this model, future q over land is determined by scaling the present-day pattern of land q by the fractional increase in the oceanic moisture source. Simple model estimates agree well with climate model projections of future (mean spatial correlation coefficient 0.87), so over both land and ocean can be viewed primarily as a thermodynamic process controlled by SST warming. Precipitation change is also affected by , and the new simple model can be included in a decomposition of tropical precipitation change, where it provides increased physical understanding of the processes that drive over land. Confidence in the thermodynamic part of extreme precipitation change over land is increased by this improved understanding, and this should scale approximately with Clausius–Clapeyron oceanic q increases under SST warming. Residuals of actual climate model from simple model estimates are often associated with regions of large circulation change, and can be thought of as the “dynamical” part of specific humidity change. The simple model is used to explore intermodel uncertainty in , and there are substantial contributions to uncertainty from both the thermodynamic (simple model) and dynamical (residual) terms. The largest cause of intermodel uncertainty within the thermodynamic term is uncertainty in the magnitude of global mean SST warming.

Based on the historical and RCP8.5 experiments from 25 Coupled Model Intercomparison Project phase 5 (CMIP5) models, the impacts of sea surface temperature (SST) warming in the tropical Indian Ocean (IO) on the projected change in summer rainfall over Central Asia (CA) are investigated. The analysis is designed to answer three questions: (1) Can CMIP5 models reproduce the observed influence of the IO sea surface temperatures (SSTs) on the CA rainfall variations and the associated dynamical processes? (2) How well do the models agree on their projected rainfall changes over CA under warmed climate? (3) How much of the uncertainty in such rainfall projections is due to different impacts of IO SSTs in these models? The historical experiments show that in most models summer rainfall over CA are positively correlated to the SSTs in the IO. Furthermore, for models with higher rainfall-SSTs correlations, the dynamical processes accountable for such impacts are much closer to what have been revealed in observational data: warmer SSTs tend to favor the development of anti-cyclonic circulation patterns at low troposphere over north and northwest of the Arabian Sea and the Bay of Bengal. These anomalous circulation patterns correspond to significantly enhanced southerly flow which carries warm and moisture air mass from the IO region up to the northeast. At the same time, there is a cyclonic flow over the central and eastern part of the CA which further brings the tropical moisture into the CA and provides essential moist conditions for its rainfall generation. In the second half of twenty-first century, although all the 25 models simulate warmed SSTs, significant uncertainty exists in their projected rainfall changes over CA: half of them suggest summer rainfall increases, but the other half project rainfall decreases. However, when we select seven models out of the 25 based on their skills in capturing the dynamical processes as observed, then the model projected changes are much closer. Five out of the seven models predicted more rainfall over CA. Such a result is helpful for allowing us to attribute part of the observed upward rainfall trend in the CA region in the last several decades to the IO SST warming.

Most of CMIP5 models projected a weakened Walker circulation in tropical Pacific, but what causes such change is still an open question. By conducting idealized numerical simulations separating the effects of the spatially uniform sea surface temperature (SST) warming, extra land surface warming and differential SST warming, we demonstrate that the weakening of the Walker circulation is attributed to the western North Pacific (WNP) monsoon and South America land effects. The effect of the uniform SST warming is through so-called “richest-get-richer” mechanism. In response to a uniform surface warming, the WNP monsoon is enhanced by competing moisture with other large-scale convective branches. The strengthened WNP monsoon further induces surface westerlies in the equatorial western-central Pacific, weakening the Walker circulation. The increase of the greenhouse gases leads to a larger land surface warming than ocean surface. As a result, a greater thermal contrast occurs between American Continent and equatorial Pacific. The so-induced zonal pressure gradient anomaly forces low-level westerly anomalies over the equatorial eastern Pacific and weakens the Walker circulation. The differential SST warming also plays a role in driving low-level westerly anomalies over tropical Pacific. But such an effect involves a positive air-sea feedback that amplifies the weakening of both east–west SST gradient and Pacific trade winds.

The sea surface temperature (SST) warming in the high-impact area of the North Atlantic prompts active convection over the Qinghai–Tibet Plateau (QTP), which consequently drives the Hadley Cell (HC) in the South Asian monsoon region to shift northward. This interaction mechanism stresses the “hub” effect of the QTP in the atmospheric energy and water cycle of the low- to mid–high latitude systems during the convergence of westerly and monsoon winds. The Rossby source, also famous as the “oscillation source,” formed in the upper troposphere by the SST variations in the high-impact area of the North Atlantic, is an essential “thermal driving source” for the interannual shifts in convection over the QTP. The meridional teleconnection wave train structure triggered by the warming (1991–2020)/cooling (1961–1990) of the SST in the high-impact area of the mid–high latitudes of the North Atlantic displays a reversed phase. The Rossby wave train, which spreads from the North Atlantic to the QTP during the high-impact sea surface warming phase in the North Atlantic, indicates a remarkable anticyclonic structure (strong divergence) in the high altitude (200 hPa) of the QTP, which favors the generation of active convective activity in the latter 30 years. By contrast, convective activity is blocked. During the two stages of 1961–1990 and 1991–2020, despite a significant interdecadal positive and negative phase reversal in the North Atlantic Multiyear Oscillation (AMO), the variance in the definition range between the AMO and the high-impact area of the North Atlantic led to substantial differences in the meridional teleconnection wave train structures and the corresponding effects. In addition, the latent heat emitted by the enhanced convective activity on the QTP during the sea surface warming phase in the high-impact area of the North Atlantic can strengthen the “heat pump” effect of the QTP, cause the northward shift of HC in the South Asian monsoon region, and spark the mutual feedback mechanism between the plateau convection and the HC in the South Asian monsoon region. According to these interdecadal response characteristics, this paper offers a comprehensive physical image that exhibits the mutual feedback between the convection over the QTP and the HC in the South Asian monsoon region, where the active convection is initiated by the SST warming in the high-impact area of the North Atlantic.

Significant uncertainty exists in regional climate change projections, particularly for rainfall and other hydro-climate variables. In this study, we conduct a series of Atmospheric General Circulation Model (AGCM) experiments with different future sea surface temperature (SST) warming simulated by a range of coupled climate models. They allow us to assess the extent to which uncertainty from current coupled climate model rainfall projections can be attributed to their simulated SST warming. Nine CMIP5 model-simulated global SST warming anomalies have been super-imposed onto the current SSTs simulated by the Australian climate model ACCESS1.3. The ACCESS1.3 SST-forced experiments closely reproduce rainfall means and interannual variations as in its own fully coupled experiments. Although different global SST warming intensities explain well the inter-model difference in global mean precipitation changes, at regional scales the SST influence vary significantly. SST warming explains about 20–25% of the patterns of precipitation changes in each of the four/five models in its rainfall projections over the oceans in the Indo-Pacific domain, but there are also a couple of models in which different SST warming explains little of their precipitation pattern changes. The influence is weaker again for rainfall changes over land. Roughly similar levels of contribution can be attributed to different atmospheric responses to SST warming in these models. The weak SST influence in our study could be due to the experimental setup applied: superimposing different SST warming anomalies onto the same SSTs simulated for current climate by ACCESS1.3 rather than directly using model-simulated past and future SSTs. Similar modelling and analysis from other modelling groups with more carefully designed experiments are needed to tease out uncertainties caused by different SST warming patterns, different SST mean biases and different model physical/dynamical responses to the same underlying SST forcing.

Lower Stratospheric water vapor (SWV) is one of important drivers of global climate change. Increases and decreases in lower SWV have been found to strengthen and offset global warming effects, respectively. Using several data sets, we find that sea surface temperature (SST) warming in the past 100 years has caused an increase in SWV. SST warming over the tropical Indian Ocean and the western Pacific has resulted in a drier stratosphere. However, tropical Atlantic Ocean warming has resulted in a significantly wetter stratosphere and is the main contributor to the increasing trend of SWV in the past 100 years. The responses of Rossby and Kelvin waves over the Indian Ocean and western Pacific to Atlantic warming have led to a warmer tropopause temperature, resulting in more water vapor entering the stratosphere. This study suggests that SWV trend may simply be the result of a game between warm pool SST and tropical Atlantic SST changes.