Initial Sea Surface Temperature Research Articles

Improving the Statistical Representation of Tropical Cyclone In-Storm Sea Surface Temperature Cooling

Abstract This study uses fixed buoy time series to create an algorithm for sea surface temperature (SST) cooling underneath a tropical cyclone (TC) inner core. To build predictive equations, SST cooling is first related to single variable predictors such as the SST before storm arrival, ocean heat content (OHC), mixed layer depth, sea surface salinity and stratification, storm intensity, storm translation speed, and latitude. Of all the single variable predictors, initial SST before storm arrival explains the greatest amount of variance for the change in SST during storm passage. Using a combination of predictors, we created nonlinear predictive equations for SST cooling. In general, the best predictive equations have four predictors and are built with knowledge about the prestorm ocean structure (e.g., OHC), storm intensity (e.g., minimum sea level pressure), initial SST values before storm arrival, and latitude. The best-performing SST cooling equations are broken up into two ocean regimes: when the ocean heat content is less than 60 kJ cm−2 (greater spread in SST cooling values) and when the ocean heat content is greater than 60 kJ cm−2 (SST cooling is always less than 2°C), which demonstrates the importance of the prestorm oceanic thermal structure on the in-storm SST value. The new equations are compared to what is currently used in a statistical–dynamical model. Overall, since the ocean providing the latent heat and sensible heat fluxes necessary for TC intensification, the results highlight the importance for consistently obtaining accurate in-storm upper-oceanic thermal structure for accurate TC intensity forecasts. Significance Statement The ocean provides the heat and moisture necessary for tropical cyclone (TC) intensification. Since the heat and moisture transfer depend on the sea surface temperature (SST), we create statistical equations for the prediction of SST underneath the storm. The variables we use combine the initial SST before the storm arrives, the upper-ocean thermal structure, and the strength and translation speed of the storm. The predictive equations for SST are evaluated for how well they improve TC intensity forecasts. The best-performing equations can be used for prediction in operational statistical models, which can aid intensity forecasts.

The initial errors occurring over Pacific-Atlantic Oceans and exerting large disturbing effect on ENSO predictability

Using a novel data analysis method for predictability dynamics, the impacts of initial sea surface temperature (SST) errors over Pacific and Atlantic Oceans on the predictability of eastern and central Pacific El Niño (i.e., EP and CP El Niño) are investigated. The results reveal the initial SST errors that cause large disturbing effects on EP and CP El Niño forecasting, respectively. These initial errors are both exhibiting a positive-negative-positive-negative-positive chain structure along the direction from northwest to southeast over the Pacific for EP and CP El Niño, which resemble a combined mode of North Pacific Victoria Mode (VM), eastern tropical Pacific positive SST pattern (ETPPSP), and South Pacific meridional mode (SPMM); simultaneously, they exhibit a positive-negative meridional dipole pattern over South Atlantic, referred to as South Atlantic subtropical dipole mode (SASD); additionally, there exist initial warm SST anomalies in the equatorial Atlantic for EP El Niño and in the north tropical Atlantic for the CP El Niño. The above initial errors lead to the underestimation of both CP and EP El Niño. Further analyses illustrate that the initial warm SST errors in the north tropical Atlantic are positively correlated with the VM-like error pattern, which competed with the effect of the ETPPSP, makes the intensity of CP El Niño underestimated; whereas the SASD-like error pattern is revealed to have a positive relationship with the SPMM-like error mode, which only exists during EP El Niño period and interacts with the ETPPSP for much weak EP El Niño intensity. It is obvious that, for predicting which type of El Niño will occur, attention should also be paid to the initial sea temperature accuracy in the Atlantic Ocean under the interference effect of the Pacific Ocean temperature uncertainties.

Rainfall–Mixed Layer–SST Feedback Contributing to Atlantic Meridional Mode Development

Abstract A simple air–sea coupled model for wind–evaporation–sea surface temperature (SST), wind-induced turbulence–mixed layer (ML)–SST, and wind–evaporation–ML–SST feedback is extended to unitedly represent the precipitation anomaly associated with moisture convergence and the ML depth (MLD) anomaly due to freshwater-induced buoyancy flux. An eigenanalysis reveals the presence of yet another feedback accompanying a cross-equatorial SST gradient. The feedback operates as follows: A cross-equatorial SST gradient anomaly forces surface wind anomalies to blow toward the warmer hemisphere, causing low-level convergence (divergence) and hence a positive (negative) precipitation anomaly in the warmer (cooler) hemisphere. The positive (negative) precipitation anomaly stratifies (destabilizes) the near-surface ocean and results in a shallower (deeper) ML, which enhances (reduces) the warming by climatological shortwave radiation, and thus provides positive feedback to the initial SST gradient anomaly. The strength of this feedback is similar to the three known feedbacks in terms of stability. Sensitivity experiments with the coupled general circulation model MIROC6 reveal that the precipitation-induced buoyancy flux anomaly accounts for up to ∼14% of the Atlantic meridional mode (AMM) amplitude in boreal spring through affecting the MLD anomaly in the deep tropics, which is consistent with the simple model results, supporting the existence of the feedback. In contrast, the evaporation-induced buoyancy anomaly contributes only marginally to the MLD and thus the SST anomalies. The ML temperature budget from MIROC6 confirms that sensitivity changes of the ML to the warming by climatological shortwave radiation due to the MLD anomaly are important in generating the SST anomalies associated with the AMM, which is consistent with previous observational studies. Significance Statement It is known that year-to-year variations in the sea surface north–south temperature gradient in the tropical Atlantic can affect the climate in both surrounding and remote regions. In this study, we used theoretical and state-of-the-art climate models to investigate a tropical air–sea coupled process and establish its contribution to the Atlantic climate variability. As a result, we identified a previously unknown process contributing to north–south gradient variations in which the atmosphere and ocean interact to enhance the initial variation, thus forming a positive feedback loop. In particular, precipitation and near-surface ocean state changes were determined to be essential. This feedback process accounts for up to 14% of the north–south temperature gradient variations in the tropical Atlantic during the boreal spring.

Modulating and Resetting Impacts of Different Volcanic Eruptions on North Atlantic SST Variations

AbstractThis study investigates the impact of volcanic eruption on the North Atlantic (NA) sea surface temperature (SST) during the last millennium based on both model simulations and reconstructions. Our focus is on the two types of relations between the states of SST and associated climate variables before and after the eruption: modulating and resetting. Here, modulating means that the posterior conditions depend on the initial SST and the volcano‐induced cooling is linearly superimposed on the initial SST phases, while resetting means that the posterior conditions are independent from the initial condition. Our analysis demonstrates that equatorial and northern volcanic eruptions larger than 30 Tg could reset NA SST, and there is a limitation of SST decrease after eruption, indicating the largest SST decrease does not exceed a certain value. While equatorial volcanic eruptions larger than 100 Tg and northern volcanic eruptions larger than 30 Tg can reset subsurface temperature changes. In contrast, even the largest volcanic eruption during the last millennium cannot reset the Atlantic Meridional Overturning Circulation.

Numerical study on advective fog formation and its characteristic associated with cold water upwelling.

Recent rapid industrial development in the Korean Peninsula has increased the impacts of meteorological disasters on marine and coastal environments. In particular, marine fog driven by summer cold water masses can inhibit transport and aviation; yet a lack of observational data hinders our understanding of this phenomena. The present study aimed to analyze the differences in cold water mass formation according to sea surface temperature (SST) resolution and its effects on the occurrence and distribution of sea fog over the Korean Peninsula from June 23-July 1, 2016, according to the Weather Research and Forecasting model. Data from the Final Operational Model Global Tropospheric Analyses were provided at 1° and 0.25° resolutions and NOAA real-time global SST (RTG-SST) data were provided at 0.083°. While conventional analyses have used initial SST distributions throughout the entire simulation period, small-scale, rapidly developing oceanic phenomena (e.g., cold water masses) lasting for several days act as an important mediating factor between the lower atmosphere and sea. RTG-SST was successful at identifying fog presence and maintained the most extensive horizontal distribution of cold water masses. In addition, it was confirmed that the difference in SST resolution led to varying sizes and strengths of the warm pools that provided water vapor from the open sea area to the atmosphere. On examining the horizontal water vapor transport and the vertical structure of the generated sea fog using the RTG-SST, water vapors were found to be continuously introduced by the southwesterly winds from June 29 to 30, creating a fog event throughout June 30. Accordingly, high-resolution SST data must be input into numerical models whenever possible. It is expected that the findings of this study can contribute to the reduction of ship accidents via the accurate simulation of sea fog.

Toward an optimal observational array for improving two flavors of El Niño predictions in the whole Pacific

This paper investigates the optimal observational array for improving the El Niño-Southern Oscillation (ENSO) prediction by exploring sensitive areas for target observations of two types of El Niño events in the whole Pacific. A target observation method based on the particle filter and pre-industrial control runs from six coupled model outputs in Coupled Model Intercomparison Project Phase 5 (CMIP5) experiments are used to quantify the relative importance of the initial accuracy of sea surface temperature (SST) in different Pacific areas. The initial accuracy of the tropical Pacific, subtropical Pacific, and extratropical Pacific can all exert influences on both types of El Niño predictions. The relative importance of different areas changes along with different lead times of predictions. Tropical Pacific observations are crucial for decreasing the root mean square error of predictions of all lead times. Subtropical and extratropical observations play an important role in decreasing the prediction uncertainty, especially when the prediction is made before and throughout the boreal spring. To consider different El Niño types and different start months for predictions, a quantitative frequency method based on frequency distribution is applied to determine the optimal observations of ENSO predictions. The final optimal observational array contains 31 grid points, including 21 grid points in the equatorial Pacific and 10 grid points in the North Pacific, suggesting the importance of the initial SST conditions for ENSO predictions not only in the tropical Pacific but also in the area outside the tropics. Furthermore, the predictions made by assimilating SST in sensitive areas have better prediction skills in the verification experiment, which can indicate the validity of the optimal observational array designed in this study.

A Simple Coupled Model of the Wind–Evaporation–SST Feedback with a Role for Stability

Abstract The wind–evaporation–SST (WES) feedback describes a coupled mechanism by which an anomalous meridional sea surface temperature (SST) gradient in the tropics evolves over time. As commonly posed, the (positive) WES feedback depends critically on the atmospheric response to SST anomalies being governed by a process akin to that argued by Lindzen and Nigam in 1987, and omits an alternative process by which SST anomalies modulate surface wind speed through vertical momentum mixing as proposed by Wallace et al. and Hayes et al. in 1989. A simple model is developed that captures the essential coupled dynamics of the WES feedback as commonly posed, while also allowing for momentum entrainment in response to evolving SST anomalies. The evolution of the coupled system depends strongly on which effects are enabled in the model. When both effects are accounted for in idealized cases near the equator, the initial anomalous meridional SST gradient grows over a time scale of a few months but is damped within one year. The sign and magnitude of the WES feedback depend on latitude within the tropics and exhibit hemispheric asymmetry. When constrained by realistic profiles of prevailing zonal wind, the model predicts that the WES feedback near the equator is stronger during boreal winter, while the domain over which it is positive is broader during boreal summer, and that low-frequency climate variability can also modulate the strength and structure of the WES feedback. These insights may aid in the interpretation of coupled climate behavior in observations and more complex models. Significance Statement Regional climate variability on time scales from months to decades, including El Niño, relies heavily on feedbacks between the atmosphere and the ocean in which some initial change in the environment is either amplified or damped over time. Several conceptual models for such feedbacks have been devised over the years to explain the coupled climate behavior seen in observations and computer simulations. A rather ubiquitous one is called the wind–evaporation–SST (WES) feedback, but the typical phrasing of it does not incorporate a potentially important influence of ocean temperature changes on the stability of the atmosphere above it. This study adds that effect to the WES feedback framework and examines climate variability through the lens of the augmented conceptual model.

Understanding the Complicated Relationship Between ENSO and Wintertime North Tropical Atlantic SST Variability

AbstractThe El Niño–Southern Oscillation (ENSO) is known to influence the North Tropical Atlantic (NTA) sea surface temperature (SST) during its decaying spring, providing an essential source of NTA predictability. However, the positive ENSO–NTA SST relationship is absent during boreal winter, impeding accurate anticipation of wintertime NTA SST fluctuations. We find that this absence is mainly due to different NTA preconditions. Taking into account the previous summer NTA SST state as an initial condition, a robust relationship is established between ENSO and wintertime NTA SST variability. Furthermore, we show that the NTA initial conditions are in part traced to the ENSO preconditions. Besides, the simultaneous local atmospheric conditions play a role in shaping the initial NTA SST variabilities, especially in the developing summer of El Niño events. The understanding of the complicated ENSO–wintertime NTA SST relationship has implications for exploring trans‐basin climate interactions and associated climate predictability.

Lagged oceanic effects on the East African short rains

The East African ‘short rains’ in October–December (OND) exhibit large interannual variability. Drought and flooding are not unusual, and long-range rainfall forecasts can guide planning and preparedness for such events. Although seasonal forecasts based on dynamical models are making inroads, statistical models based on sea surface temperature (SST) precursors are still widely used, making it important to better understand the strengths and weaknesses of such models. Here we define a simple statistical forecast model, which is used as a tool to shed light on the dynamics that link SSTs and rainfall across time and space, as well as on why such models sometimes fail. Our model is a linear regression, where the August states of El Niño-Southern Oscillation (ENSO) and the Indian Ocean Dipole (IOD) predict about 40% of the short rains variability in 1950–2020. The forecast errors are traced back to the initial SSTs: too-wet (too-dry) forecasts are linked linearly to positive (negative) initial ENSO and IOD states in August. The link to the initial IOD state is mediated by changes in the IOD between August and OND, highlighting a physical mechanism for prediction busts. We also identify asymmetry and nonlinearity: when ENSO and/or the IOD are positive in August, the range and variance of OND forecast errors are larger than when the SST indices are negative. Upfront adjustments of predictions conditional on initial SSTs would have helped in some years with large forecast busts, such as the dry 1987 season during a major El Niño, for which the model erroneously predicts copious rainfall, but it would have exacerbated the forecast in the wet 2019 season, when the IOD was strongly positive and the model predicts too-dry conditions.

Tropical North Atlantic Response to ENSO: Sensitivity to Model Spatial Resolution

AbstractIn this study, the ENSO teleconnection with the tropical North Atlantic (TNA) sea surface temperatures (SSTs) in boreal spring is analyzed in ocean–atmosphere coupled global circulation models. To assess the role played by horizontal resolution of models on this teleconnection, we used a multimodel dataset that is the first to combine models with both low and high resolution. The TNA response to ENSO projects onto the most significant SST mode of the tropical Atlantic at interannual time scales, the Atlantic meridional mode (AMM). Its evolution is primarily driven by the wind–evaporation–SST (WES) feedback, which in turn is based on the development of an initial SST gradient. This study examines and quantifies the relative contribution of a dynamic-related (upwelling) and a thermodynamic-related (evaporation) process in triggering this gradient in the case of the ENSO–TNA teleconnection. While no major contribution is found with the evaporation, a consistent contribution from the coastal upwelling off northwest Africa is identified. This contribution is enhanced in high-resolution models and highlights the close link between the upwelling in winter and the development of the AMM in spring. It is further shown that high-resolution models present a thinner and more realistic ocean mixed layer within the upwelling area, which enhances the effect of surface winds on upwelling and SSTs. As a consequence, high-resolution models are more sensitive than low-resolution models to surface wind errors, thereby they do not ensure improved reliability or predictability of the TNA SST response to ENSO.

Optimal Growth of IPV Lags AMV Modulations by up to a Decade

AbstractThe Interdecadal Pacific Variability (IPV) has global climate effects but its decadal prediction is a challenge. Here, we use linear inverse models to study the optimal growth of the IPV and reveal important precursor patterns. We find that the optimal growth of the IPV exists in observations due to interference among various sea surface temperature (SST) decadal variations. Small SST anomalies extending from the northeastern subtropical Pacific to the central tropical Pacific, in concert with thermocline dynamics, can develop into a mature phase of the IPV after ∼3 years. Furthermore, the initial SST anomalies lag the Atlantic Multidecadal Variability (AMV) by up to a decade, suggesting the potential importance of the AMV in IPV decadal predictability. As climate models commonly underestimate the AMV trans‐basin effect, our study calls for more efforts on reducing the model bias to improve IPV decadal prediction.

Asymmetric relationship between ENSO and the tropical Indian Ocean summer SST anomalies

AbstractDuring the summer following El Niño, a basin-wide sea surface temperature (SST) warming takes place over the tropical Indian Ocean (TIO), exerting profound influences on the Asian summer monsoon. This is an important source of seasonal predictability for the Asian summer monsoon. Based on observations, however, the present study finds that the relationship between El Niño-Southern Oscillation (ENSO) and the TIO SST anomalies during the decaying summer is asymmetric with a much weaker relationship between La Niña and the TIO SST anomalies relative to El Niño. The analyses show that this asymmetric relationship can be explained by the asymmetries in initial TIO SST, oceanic Rossby wave in the southern Indian Ocean and ENSO decaying rate. In contrast to El Niño events, La Niña events tend to have a stronger initial TIO warming and a less peak intensity with a weaker oceanic Rossby wave response in the southern Indian Ocean. On the other hand, La Niña events tend to decay more slowly with the persistent SST cooling over the central equatorial Pacific in the following summer. The equatorial Pacific SST cooling would induce an anomalous anticyclone via a Gill-type Rossby wave response, weakening the positive feedback between the anomalous cyclone spanning the tropical Northwest Pacific and North Indian oceans and the TIO summer basin-wide SST cooling. These results have important implications for the climate predictability of the Indian Ocean and Asian summer monsoon.

Exploring North Atlantic and North Pacific Decadal Climate Prediction Using Self-Organizing Maps

AbstractDecadal climate prediction can provide invaluable information for decisions made by government agencies and industry. Modes of internal variability of the ocean play an important role in determining the climate on decadal time scales. This study explores the possibility of using self-organizing maps (SOMs) to identify decadal climate variability, measure theoretical decadal predictability, and conduct decadal predictions of internal climate variability within a long control simulation. SOM is applied to an 11-yr running-mean winter sea surface temperature (SST) in the North Pacific and North Atlantic Oceans within the Community Earth System Model 1850 preindustrial simulation to identify patterns of internal variability in SSTs. Transition probability tables are calculated to identify preferred paths through the SOM with time. Results show both persistence and preferred evolutions of SST depending on the initial SST pattern. This method also provides a measure of the predictability of these SST patterns, with the North Atlantic being predictable at longer lead times than the North Pacific. In addition, decadal SST predictions using persistence, a first-order Markov chain, and lagged transition probabilities are conducted. The lagged transition probability predictions have a reemergence of prediction skill around lag 15 for both domains. Although the prediction skill is very low, it does imply that the SOM has the ability to predict some aspects of the internal variability of the system beyond 10 years.

Comparison of the third-generation Japanese ocean flux data set J-OFURO3 with numerical simulations of Typhoon Dujuan (2015) traveling south of Okinawa

Insufficient in situ observations in high winds make it difficult to verify climatological data sets and the results of tropical cyclone (TC) simulations. Reliable data sets are necessary for developing numerical models that predict TCs more accurately. This study attempted to compare the third-generation Japanese Ocean Flux Data Sets with Use of Remote-Sensing Observations (J-OFURO3) data, with TC simulations conducted by a 2 km mesh coupled atmosphere-wave-ocean model. This is a case study of Typhoon Dujuan (2015) and the area of approximately 20̊N, 130̊E, south of Okinawa, was selected. The comparison reveals that J-OFURO3 data are reliable for verifying the atmospheric and oceanic components of TC simulations with two different initial sea surface temperature (SST) conditions, although the blank area remains within the inner core area for air temperature, specific humidity, and latent heat flux owing to issues with the construction method. Simulated maximum surface wind speeds (MSWs) are significantly correlated with J-OFURO3 MSWs. The asymmetrical distribution of simulated surface wind speeds within the inner core area can be reproduced well in the J-OFURO3 data set. In terms of the oceanic response to the TC, TC-induced sea surface cooling was reproduced well in the J-OFURO3 data set and is consistent with the simulation results. Unlike simulated SST, simulated surface wind speeds, surface air temperature, and surface specific humidity are still inconsistent with the J-OFURO3 data, even when the J-OFURO3 SST is used as the initial condition. New algorithms, more satellite data used, and model improvement are expected in the future.

Evaluation of the Initial Sea Surface Temperature From the HY-2B Scanning Microwave Radiometer

Haiyang-2B (HY-2B) is the second marine dynamic environment satellite of China. Sea surface temperature (SST) products from the scanning microwave radiometer (SMR) onboard HY-2B satellite are evaluated against in situ measurements. Approximately, ten months of data are used for the initial evaluation, from January 15, 2019 to November 15, 2019. The temporal and spatial windows for collocation are 30 min and 25 km, respectively, which produce 450 416 matchup pairs between HY-2B/SMR and in situ SSTs. The statistical comparison of the entire data set shows that the mean bias is −0.13 °C (SMR minus buoy), and the corresponding root-mean-square error (RMSE) is 1.06 °C. Time series of collocations for the SST difference shows that a good agreement is found between HY-2B/SMR and in situ SSTs after June 15, revealing a mean bias and an RMSE of only 0.09 °C and 0.72 °C, respectively. A three-way error analysis is conducted between the SMR, Global Precipitation Measurement Microwave Imager (GMI), and in situ SSTs. Individual standard deviations are found to be 0.41 °C for the GMI SST, 0.15 °C for the in situ SST, and 1.03 °C for the SMR SST. The results indicate that the HY2B/SMR SST products need to be improved during the period from January 15, 2019 to June 15, 2019.

The Role of Interactive SST in the Cloud‐Resolving Simulations of Aggregated Convection

AbstractThis study investigates the role of interactive sea surface temperature (SST) in the early development of aggregated convection using a vector vorticity equation cloud‐resolving model coupled to a slab ocean. The simulations are initialized by a mock Walker circulation driven by initial SST gradient in the elongated x axis, with an average of 300 K and sinusoidal variation of amplitude ranging from 1.5 to 3 K. According to large‐scale perturbation strength, which is caused by SST variation, the results can be divided into two groups. Under weak perturbation, convection‐SST feedback efficiently eliminates SST gradient and moisture anomaly. The large‐scale environment is homogenized within 2 days. Even though SST in the group with stronger perturbation undergoes a similar process, significant moist static energy (MSE) advection in the boundary produces enough moisture difference to introduce virtual temperature effect and aggregation is triggered. Once dry zone starts to expand, radiative and convective effects regenerate SST gradient, which intensifies circulation and accelerates the process. We further show that the evolution of aggregation or not is captured by the trend of MSE‐EIS (estimated inversion strength) variance. The results highlight the boundary layer processes on the formation of aggregated convection in the tropics.

The effect of atmosphere–ocean coupling on the prediction of 2016 western North Pacific tropical cyclones

AbstractWe examine the merit of atmosphere–ocean coupled models for tropical cyclone (TC) predictions in the western North Pacific (WNP), where accurate TC predictions remain challenging. The UK Met Office operational atmospheric global numerical weather prediction (NWP) model is compared with two trial coupled configurations, in which the operational atmospheric model is coupled to a one‐dimensional mixed‐layer ocean model and a three‐dimensional dynamical ocean model. Reforecasts for the 2016 TC season show that the coupled models outperform the NWP model for TC location predictions, with a systematic improvement of 50–100 km over the seven‐day forecasts, but the coupled models amplify the underestimation of TC intensity in the NWP model. Nearly identical TC predictions (for both location and intensity) are found in the two coupled models, indicating the dominance of thermodynamic processes at the air–sea interface for TC predictions on these timescales. The improved prediction of the TC position in the coupled models is associated with an enhanced Western North Pacific Subtropical High (WNPSH), which introduces an anticyclonic steering flow anomaly that shifts TC tracks further west in the southern part of the region and further east in the northern part. Based on sensitivity experiments, we show that these improvements in the coupled models are due mainly to colder initial sea‐surface temperatures (SSTs). Air–sea feedbacks do not change the WNPSH or TC tracks noticeably. Apart from the effect of the initial SSTs, tropical ocean warming due to air–sea interaction in the coupled forecasts can also reduce the predicted TC intensity, presumably due to a stronger regional Hadley circulation with increased subtropical subsidence.

Wind–Mixed Layer–SST Feedbacks in a Tropical Air–Sea Coupled System: Application to the Atlantic

Abstract The ocean–atmosphere feedback associated with the thermodynamic coupling among wind speed, evaporation, and sea surface temperature (SST), called the wind–evaporation–SST (WES) feedback, contributes to the cross-equatorial SST gradient over the tropical oceans. By conducting an eigenanalyses of simple linear air–sea coupled models, it is shown that two additional feedback processes are present when the variable oceanic mixed layer depth (MLD) is considered. The horizontal structures of the leading modes are similar to the WES mode, which shows a meridional dipole in the SST anomalies straddling the equator with cross-equatorial wind anomalies that represent the weakening/strengthening of the trade winds over the warm/cool SST anomalies. The coupling of the variable MLD with winds and SST more than doubles the growth rate of the WES mode and enhances the equatorward propagation of the coupled disturbances. The identified feedbacks operate as follows: The weaker winds associated with warm SST anomalies shoal the mixed layer through suppressed turbulent mixing, which causes the mixed layer to be more sensitive to the climatological shortwave radiation and amplifies the initial positive SST anomalies. Likewise, deepening of the mixed layer due to stronger winds acts to maintain the negative SST anomaly on the other side of the dipole. The MLD anomalies can also be generated by the buoyancy flux anomaly related to the wind-induced latent heat flux anomaly. The antiphase relationship between the SST and MLD anomalies seen in the simple model bears some resemblance to that which is observed in the observations and a state-of-the-art coupled model during the Atlantic meridional mode.

An Episodic Weakening in the Boreal Spring SST–Precipitation Relationship in the Western Tropical Pacific since the Late 1990s

Abstract We found that a positive sea surface temperature (SST)–precipitation relationship in the western tropical Pacific (WTP) during boreal spring, in which higher SSTs are associated with higher precipitation, episodically weakens from the late 1990s to the early 2010s. During 1980–98, warm SSTs induce positive precipitation and low pressure in the WTP. The associated enhanced convection dampens the initial warm SSTs by reflecting incoming solar radiation. The reduced incoming solar radiation into the ocean leads to a SST cooling tendency. In contrast, the associated southwesterly wind anomalies reduce oceanic mixing by decreasing the mean wind, contributing to an SST warming tendency, though relatively small. Therefore, the cloud–radiation effect is a dominant process of the negative SST tendency. By contrast, during 1999–2014, although an SST cooling tendency is similarly induced by warm SST anomalies, the cooling tendency is enhanced by anomalous ocean advection, as a result of enhanced easterly wind anomalies in the southern part of the WTP. This results in a weakening of a positive relationship of the SST and precipitation during 1999–2014. As such, the associated anomalous convective heating in the WTP during 1999–2014 is weak, changing the atmospheric teleconnection patterns in the midlatitude and surface air temperature anomalies in western North America and northeastern Eurasia.

Multi-Physics Ensemble versus Atmosphere–Ocean Coupled Model Simulations for a Tropical-Like Cyclone in the Mediterranean Sea

Between 19 and 22 January 2014, a baroclinic wave moving eastward from the Atlantic Ocean generated a cut-off low over the Strait of Gibraltar and was responsible for the subsequent intensification of an extra-tropical cyclone. This system exhibited tropical-like features in the following stages of its life cycle and remained active for approximately 80 h, moving along the Mediterranean Sea from west to east, eventually reaching the Adriatic Sea. Two different modeling approaches, which are comparable in terms of computational cost, are analyzed here to represent the cyclone evolution. First, a multi-physics ensemble using different microphysics and turbulence parameterization schemes available in the WRF (weather research and forecasting) model is employed. Second, the COAWST (coupled ocean–atmosphere wave sediment transport modeling system) suite, including WRF as an atmospheric model, ROMS (regional ocean modeling system) as an ocean model, and SWAN (simulating waves in nearshore) as a wave model, is used. The advantage of using a coupled modeling system is evaluated taking into account air–sea interaction processes at growing levels of complexity. First, a high-resolution sea surface temperature (SST) field, updated every 6 h, is used to force a WRF model stand-alone atmospheric simulation. Later, a two-way atmosphere–ocean coupled configuration is employed using COAWST, where SST is updated using consistent sea surface fluxes in the atmospheric and ocean models. Results show that a 1D ocean model is able to reproduce the evolution of the cyclone rather well, given a high-resolution initial SST field produced by ROMS after a long spin-up time. Additionally, coupled simulations reproduce more accurate (less intense) sea surface heat fluxes and a cyclone track and intensity, compared with a multi-physics ensemble of standalone atmospheric simulations.