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We perform quadrupled CO2 climate simulations with the Community Earth System Model version 1 (CESM1) to study how air-sea coupling affects the response of tropical rainfall under global warming. We use a hierarchy of ocean models to separate the effects of seasonal mixed-layer entrainment, wind-driven Ekman flows directed perpendicular to the wind, and the near-equator frictional flows directed in the same direction as the wind. We show that the Pacific Ocean's enhanced equatorial warming pattern (EEW) and equatorward ITCZ contraction observed in previous climate simulations emerge when the ocean model includes wind-driven Ekman and frictional flows. Furthermore, the near-equator frictional flow contributes more than half of the heat convergence in the equatorial Pacific Ocean. Finally, we show that although Ekman flow and near-equator frictional flow can both result in EEW, their coupled interactions with the Hadley circulation lead to opposite feedbacks on EEW's strength.

In the boreal spring of 2023, an extreme coastal El Niño struck the coastal regions of Peru and Ecuador, causing devastating rainfalls, flooding, and record dengue outbreaks. Observations and ocean model experiments reveal that northerly alongshore winds and westerly wind anomalies in the eastern equatorial Pacific, initially associated with a record-strong Madden-Julian Oscillation and cyclonic disturbance off Peru in March, drove the coastal warming through suppressed coastal upwelling and downwelling Kelvin waves. Atmospheric model simulations indicate that the coastal warming in turn favors the observed wind anomalies over the far eastern tropical Pacific by triggering atmospheric deep convection. This implies a positive feedback between the coastal warming and the winds, which further amplifies the coastal warming. In May, the seasonal background cooling precludes deep convection and the coastal Bjerknes feedback, leading to the weakening of the coastal El Niño. This coastal El Niño is rare but predictable at 1 month lead, which is useful to protect lives and properties.

Tropical cyclone (TC) projections with atmosphere-only models are associated with uncertainties due to their inability to represent TC-ocean interactions. However, global coupled models, which represent TC-ocean interactions, can produce basin-scale sea surface temperature biases in seasonal to centennial simulations that lead to challenges in representing TC activity. Therefore, focusing on recent individual major hurricane events, we investigated the influence of TC-ocean coupling on the response of TCs to anthropogenic change using atmosphere-only and coupled atmosphere-ocean regional model simulations. Under an extremely warm scenario, coupling does not influence the signs of projected TC rainfall and intensity responses. Coupling, however, does influence the magnitude of projected intensity and especially rainfall. Within a 500 km radius region of the TCs, the projected rainfall increases in coupled simulations are 3–47 % less than in the atmosphere-only simulations, driven by enhanced TC-induced sea surface temperature cooling in the former. However, the influence of coupling on the magnitude of projected rainfall could vary considerably over the regions of highest rainfall generated by TCs.

The ENSO-induced Pacific–South America (PSA) pattern is an important atmospheric bridge in linking the Antarctic climate to the tropical Pacific. The AGCM simulated PSA-like responses to ENSO are evidently weaker than the observed in terms of its intensity due to the lack of air–sea coupling processes. The Tasman Sea features active air–sea interactions. However, how and to what extent the air–sea coupling explains the deficiency of the AGCM responses to ENSO is unclear. In this study, the role of the air–sea coupling elsewhere the tropical Pacific in shaping the ENSO–South Pacific teleconnection is first estimated by comparing the coupled tropical Pacific pacemaker experiments (PACE) derived from the Community Earth System Model version 1 (CESM1) and the parallel Pacific Ocean–Global Atmosphere experiments (POGA) with the same atmospheric component model of CESM1. Our results suggest that the air–sea coupling elsewhere the tropical Pacific greatly intensifies the South Pacific atmospheric response to ENSO. Then the separated impact of air–sea coupling over the Tasman Sea is stressed with another set of AGCM experiments forced with the PACE sea surface temperature (SST) outputs in the Tasman Sea. The results show that the atmospheric response to the SST anomalies in the Tasman Sea bears a remarkable resemblance to that due to the air–sea coupling elsewhere the tropical Pacific, and explains about 30% of the intensified amplitude. This highlights a substantial contribution of the air–sea coupling over the Tasman Sea to intensifying the extratropical South Pacific atmospheric responses to ENSO, and provides a new perspective on the connection between tropical Pacific and Antarctic climate change.

Abstract We perform quadrupled CO2 climate simulations with the Community Earth System Model version 1 (CESM1) to study how air‐sea coupling affects the response of tropical rainfall under global warming. We use a hierarchy of ocean models to separate the effects of seasonal mixed‐layer entrainment, wind‐driven Ekman flows directed perpendicular to the wind, and the near‐equator frictional flows directed in the same direction as the wind. We show that the Pacific Ocean's enhanced equatorial warming pattern (EEW) and equatorward ITCZ contraction observed in previous climate simulations emerge when the ocean model includes wind‐driven Ekman and frictional flows. Furthermore, the near‐equator frictional flow contributes more than half of the heat convergence in the equatorial Pacific Ocean. Finally, we show that although Ekman flow and near‐equator frictional flow can both result in EEW, their coupled interactions with the Hadley circulation lead to opposite feedbacks on EEW's strength.

Tropical instability waves (TIWs) are oceanic features that form around the equatorial Pacific cold tongue and influence the large-scale circulation and coupled climate variability including El Niño–Southern Oscillation. Local air–sea coupling over TIWs is thought to play an important role in the atmosphere and ocean's energy and tracer budgets but is not well captured in coarse-resolution models. In this study, we isolate the impacts of TIW thermal (sea surface temperature–driven) and current (surface current–driven) feedbacks by removing TIW signatures in air–sea coupling fields in a high-resolution regional coupled model. The thermal feedback is found to damp TIW temperature variance by a factor of 2, associated both with the direct dependence of surface heat fluxes on SST (∼74%) and indirect impacts on surface winds (∼35%) and air temperature and humidity (∼−9%). These changes lead to cooling of the cold tongue SST by up to 0.1°C through reduced TIW-driven meridional heat fluxes and associated small changes in atmospheric circulation. The current feedback is decomposed into TIW (i.e., mesoscale) and mean (i.e., large-scale) components using separate experiments, with both having distinct impacts on TIWs and the mean state. The mesoscale current feedback reduces TIW eddy kinetic energy (EKE) by 22% through the eddy wind work, while the mean current feedback induces a further reduction of 8% by extracting energy from the mean currents and thus reducing barotropic EKE shear production. An improved understanding of small-scale tropical Pacific processes is needed to address biases in coarse-resolution models that impact their predictions and projections of Pacific climate variability and change. Significance Statement: Tropical instability waves (TIWs) are oceanic features with ∼1000-km wavelengths that propagate westward on either side of the eastern equatorial Pacific cold tongue. TIWs drive lateral and vertical heat fluxes that impact several aspects of El Niño–Southern Oscillation. While climate models with a moderate, 1/4° ocean resolution can capture some TIW variability, they fail to properly represent many associated processes such as the impact of TIWs on the overlying atmosphere. Using sensitivity studies performed using a high-resolution regional coupled model, we study the impact of TIW air–sea coupling on the eastern Pacific climate system. Increased understanding of small-scale processes from studies such as this is essential to understand and address biases in models used for seasonal climate predictions and projections in the Pacific region. [ABSTRACT FROM AUTHOR]

The El Niño and Southern Oscillation (ENSO), a phenomenon of air–sea coupling in the tropical Pacific, has strong response to global climate change. In this study, the primary region where ENSO occurred during the period 1955–2020 was selected as the key ENSO region, and the changes in air–sea coupling in this region were explored. The New Southern Oscillation Index (NSOI), modified from the previous Southern Oscillation Index, represents atmospheric changes, and the Niño-3.4 index represents oceanic changes. The absolute value of the running correlation coefficient between the Niño-3.4 index and NSOI in the 121-month time window was defined as the Intensity of Air–Sea Coupling (IASC) in the key ENSO region. The results showed that the IASC has significantly increased, with a confidence level of 95%, during the period 1955–2020, and the range where the correlation coefficient between the Niño-3.4 index and the sea level pressure anomaly over the key ENSO region was greater than 0.6 has evidently expanded in the context of global warming, which corresponded to the increase in IASC. Moreover, the coupling positions of sea surface temperature and wind anomalies changed, tending to the east of the equatorial Pacific during 1977–1998, and to the west during 1999–2020.

Abstract The densely populated Bay of Bengal (BoB) rim witnesses the deadliest tropical cyclones (TCs) globally, before and after the summer monsoon. Previous studies indicated that enhanced salinity and reduced thermal stratification reduce cooling under BoB TCs after the monsoon, suggesting that air‐sea coupling may favor stronger TCs during that season. Using observations and simulations from a one fourth degree regional ocean‐atmosphere model, we show that BoB TCs are stronger before the monsoon due to a more favorable large‐scale background state (less vertical wind shear and higher sea surface temperature). Air‐sea coupling however alleviates this background state influence, by reducing the number of premonsoon intense TCs, because of larger cooling and reduced upward enthalpy fluxes below TCs during that season. As the impact of air‐sea interactions on BoB TCs is largest for intense TCs, it should be further investigated for Category 3 and above TCs, which are not reproduced at one fourth degree resolution.

Abstract The importance of air‐sea coupling in the simulation and prediction of the Madden‐Julian Oscillation (MJO) has been well established. However, it remains unclear how air‐sea coupling modulates the convection and related oceanic features on the subdaily scale. Based on a regional cloud‐permitting coupled model, we evaluated the impact of the air‐sea coupling on the convection during the convectively active phase of the MJO by varying the coupling frequency. The model successfully reproduced the atmospheric and oceanic variations observed by satellite and in situ measurements but with some quantitative biases. According to the sensitivity experiments, we found that stronger convection was mainly caused by the higher sea surface temperatures (SSTs) generated in high‐frequency coupled experiments, especially when the coupling frequency was 1 hr or shorter. A lower coupling frequency would generate the phase lags in the diurnal cycle of SST and related turbulent heat fluxes. Our analyses further demonstrated that the phase‐lagged diurnal cycle of SST suppressed deep convection through a decrease in daytime moistening in the lower troposphere. Meanwhile, in the upper ocean, the high‐frequency air‐sea coupling helped maintain the shallower mixed and isothermal layers by diurnal heating and cooling at the sea surface, which led to a higher mean SST. In contrast, the low‐frequency coupled experiments underestimated the SST and therefore convective activities. Overall, our results demonstrated that high‐frequency air‐sea coupling (1 hr or shorter) could improve the reproducibility of the intensity and temporal variation in both diurnal convection and upper ocean processes.

Abstract Atmosphere‐ocean feedbacks often improve the Madden‐Julian oscillation (MJO) in climate models, but these improvements are balanced by mean state biases that can degrade the MJO through changing the basic state on which the MJO operates. The Super‐Parameterized Community Atmospheric Model (SPCAM3) produces perhaps the best representation of the MJO among contemporary models, which improves further in a coupled configuration (SPCCSM3) despite considerable mean state biases in tropical sea surface temperatures and rainfall. We implement an atmosphere‐ocean‐mixed‐layer configuration of SPCAM3 (SPCAM3‐KPP) and use a flux‐correction technique to isolate the effects of coupling and mean state biases on the MJO. When constrained to the observed ocean mean state, air‐sea coupling does not substantially alter the MJO in SPCAM3, in contrast to previous studies. When constrained to the SPCCSM ocean mean state, SPCAM3‐KPP fails to produce an MJO, in stark contrast to the strong MJO in SPCCSM3. Further KPP simulations demonstrate that the MJO in SPCCSM3 arises from an overly strong sensitivity to El Niño–Southern Oscillation events. Our results show that simulated interannual variability and coupled‐model mean state biases affect the perceived response of the MJO to coupling. This is particularly concerning in the context of internal variability in coupled models, as many previous MJO sensitivity studies in coupled models used relatively short (20‐ to 50‐year) simulations that undersample interannual‐decadal variability. Diagnosing the effects of coupling on the MJO requires simulations that carefully control for mean state biases and interannual variability.

Precipitation over East Asia in six Met Office Unified Model (MetUM) simulations is compared with observation and ERA-Interim reanalysis. These simulations include three different horizontal resolutions, from low and medium to high, and including atmosphere-only version (Global Atmosphere 6.0; GA6) and air–sea coupling version (Global Coupled 2.0; GC2). Precipitation in simulations is systematically different from that in observations and reanalysis. Increasing horizontal resolution and including air–sea coupling improve simulated precipitation but cannot eliminate bias. Moisture sources of East Asian precipitation are identified using the Water Accounting Model (WAM-2layers) – a moisture tracking model that traces moisture source using collective information of evaporation, atmospheric moisture and circulation. Similar to precipitation, moisture sources in simulations are systematically different from that of ERA-Interim. Major differences in moisture sources include underestimated moisture contribution from tropical Indian Ocean and overestimate contribution from Eurasian continent. By increasing horizontal resolution, precipitation bias over the Tibetan Plateau is improved. From the moisture source point of view, this is achieved by reducing contribution from remote moisture source and enhancing local contribution over its eastern part. Although including air–sea coupling does not necessarily change East Asian precipitation, moisture sources show differences between coupled and atmosphere-only simulations. These differences in moisture sources indicate different types of models biases caused by surface flux or/and atmospheric circulation on different locations. This information can be used to target model biases on specified locations and due to different mechanisms.

The effect of air–sea coupling on simulated boreal summer intraseasonal oscillation (BSISO) is examined using atmosphere–ocean-mixed-layer coupled (SPCAM3-KPP, referred to as SPK throughout) and uncoupled configurations of the superparameterized (SP) Community Atmospheric Model, version 3 (SPCAM3, referred to as SPA throughout). The coupled configuration is constrained to either observed ocean mean state or the mean state from the SP coupled configuration with a dynamic ocean (SPCCSM3), to understand the effect of mean-state biases on the BSISO. All configurations overestimate summer mean subtropical rainfall and its intraseasonal variance. All configurations simulate realistic BSISO northward propagation over the Indian Ocean and western Pacific, in common with other SP configurations. Prescribing the 31 d smoothed sea surface temperature (SST) from the SPK simulation in SPA worsens the overestimated BSISO variance. In both coupled models, the phase relationship between intraseasonal rainfall and SST is well captured. This suggests that air–sea coupling improves the amplitude of simulated BSISO and contributes to the propagation of convection. Constraining SPK to the SPCCSM3 mean state also reduces the overestimated BSISO variability but weakens BSISO propagation. Using the SPCCSM3 mean state also introduces a 1-month delay to the BSISO seasonal cycle compared to SPK with the observed ocean mean state, which matches well with observation. Based on a Taylor diagram, both air–sea coupling and SPCCSM3 mean-state SST biases generally lead to higher simulated BSISO fidelity, largely due to their abilities to suppress the overestimated subtropical BSISO variance.

A new regional coupled ocean–atmosphere model, WRF4-LICOM, was used to investigate the impacts of regional air–sea coupling on the simulation of the western North Pacific summer monsoon (WNPSM), with a focus on the normal WNPSM year 2005. Compared to WRF4, WRF4-LICOM improved the simulation of the summer mean monsoon rainfall, circulations, sea surface net heat fluxes, and propagations of the daily rainband over the WNP. The major differences between the models were found over the northern South China Sea and east of the Philippines. The warmer SST reduced the gross moist stability of the atmosphere and increased the upward latent heat flux, and then drove local ascending anomalies, which led to the increase of rainfall in WRF4-LICOM. The resultant enhanced atmospheric heating drove a low-level anomalous cyclone to its northwest, which reduced the simulated circulation biases in the stand-alone WRF4 model. The local observed daily SST over the WNP was a response to the overlying summer monsoon. In the WRF4 model, the modeled atmosphere exhibited passive response to the underlying daily SST anomalies. With the inclusion of regional air–sea coupling, the simulated daily SST–rainfall relationship was significantly improved. WRF4-LICOM is recommended for future dynamical downscaling of simulations and projections over this region.

The effects of air–sea coupling over the tropical Indian Ocean (TIO) on the eastward propagating boreal winter intraseasonal oscillation (MJO) are investigated by comparing a fully coupled and a partially decoupled Indian Ocean experiment using the SINTEX-F coupled model. Air–sea coupling over the TIO significantly enhances the intensity of the eastward propagations of the MJO along the 5°–10°S zonal areas. The zonal asymmetry of the SST anomaly (SSTA) is responsible for the enhanced eastward propagation. A positive SSTA appears to the east of the MJO convection, which results in the boundary layer moisture convergence and positively feeds back to the MJO convection. In addition, the air–sea interaction effect on the eastward propagation of the MJO is related to the interannual variations of the TIO. Air–sea coupling enhances (reduces) the eastward-propagating spectrum during the negative Indian Ocean dipole mode and positive Indian Ocean basin mode. Such phase dependence is attributed to the role of the background mean westerly in affecting the wind–evaporation–SST feedback. Air–sea coupling (decoupling) enhances (reduces) the zonal asymmetry of the low-level specific humidity, and thus the eastward propagation spectrum of the MJO.

Abstract In extreme event attribution, which aims to answer whether and to what extent a particular extreme weather event can be attributed to global warming, the probability of an event is generally estimated through large ensemble simulations, using an atmospheric general circulation model (AGCM). In islands, such as Japan, it has been considered that surface air temperature (SAT) can be significantly affected by the surrounding sea surface temperature (SST), which mostly is affected by atmospheric circulation at mid- and high-latitudes. Therefore, the absence of SST responses to atmospheric variability in AGCMs impacts the estimation of the occurrence of extreme events, such as heat waves in Japan. In this study, we examined the impact of air–sea coupling on the probability of occurrence of severe heat waves that occurred in Japan in the summer of 2010 by analyzing the probability differences obtained from AGCM and coupled general circulation model (CGCM) large-ensemble experiments. The observed ocean temperature, salinity, and sea ice were assimilated in the 100-member CGCM experiments, as they were assigned as boundary conditions in the 100-member AGCM experiments. The SAT around Japan in the northern summer is largely related to the Bonin high, whose interannual variability is largely affected by the Silk Road and Pacific-Japan (PJ) pattern teleconnections in the real world. The SAT anomaly over Japan was related to the pressure variability due to the Silk Road and PJ patterns in the CGCM experiment. By contrast, the SAT over Japan simulated by AGCM was less sensitive to such pressure variability, and the SAT ensemble spread became narrower in AGCM. The results suggest that the probability of occurrence of the 2010 heat wave in Japan would tend to be underestimated by the AGCM ensemble compared to the CGCM ensemble, provided that the ensemble averages of the SAT anomalies were equal between CGCM and AGCM experiments. This study raised the issue of the absence of SST response to atmospheric variability in AGCMs, which can critically impact the estimation of extreme event probability, particularly in mid-latitude islands, such as Japan.