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The North Atlantic Oscillation (NAO) and North Atlantic tripole sea surface temperature (SST_tri) are important modes in the atmosphere and ocean over the North Atlantic, respectively. The link between the two is well‐known. However, this link weakened during 1980–2001, which is particularly pronounced in late winter and was not detected in early winter. This phenomenon has not been well revealed. The role of NAO in the above correlation changes was discussed. In late winter, a significant eastward shift (up to 20° longitude) of NAO south center during 1980–2001 was observed in both observation and CMIP6, accompanied by the eastward expansion of NAO north center. Spatial shift of the NAO forced the region of strong air‐sea interactions to shift and resulting in the collapse of NAO‐related SST_tri. These findings deepen our understanding of the NAO on the subseasonal scale. Plain Language Summary: A significant correlation between the North Atlantic Oscillation (NAO) and the North Atlantic tripole sea surface temperature (SST_tri) is widely recognized. However, this study found that the correlation between the two was significantly weakened in late winter during 1980–2001 while no such change was detected in early winter. Therefore, this paper will focus on the late winter and discuss the role of NAO spatial structure in the above correlation changes. When the NAO south center is located over the North Atlantic, both observations and the climate models indicate that the corresponding North Atlantic SST shows a significant tripole pattern. However, during 1980–2001, the NAO south center shift significantly eastward from the North Atlantic toward Western Europe (up to 20° longitude). At the same time, the NAO north center expanded eastward significantly. The eastward shift of the NAO results in the significant eastward shift of the turbulent heat flux and wind stress anomalies. Shift in the region of strong air‐sea interaction led to the collapse of NAO‐related SST_tri. These findings deepen our understanding of the NAO on the subseasonal scale and also provide implications for subseasonal‐seasonal predictions of Eurasian climate extremes. Key Points: The link between NAO and North Atlantic tripole SST weakened obviously during 1980–2001 late winter, which was not detected in early winterThe eastward shift of ∼20° longitude in NAO south center forced the strong air‐sea interactions region to shift in observations and CMIP6NAO's spatial shift in late winter caused the changes in the link between NAO and North Atlantic tripole SST [ABSTRACT FROM AUTHOR]

This study addresses a critical gap in understanding anthropogenic influences on tropical climate dynamics by investigating the impact of aerosol‐cloud interactions on large‐scale circulation. Despite extensive research on greenhouse gas‐induced warming and its effects on tropical circulation, the impact of aerosols, particularly their interactions with clouds, on large‐scale circulation remains understudied. Utilizing large‐domain radiative convective equilibrium cloud‐resolving simulations, this research demonstrates that increasing aerosol concentration intensifies tropical overturning circulation, evaluated at the mid‐troposphere (I) $(\mathcal{I})$, strongly correlating with domain mean cloud and radiative properties. Employing a weak temperature gradient approximation, I attribute variations in I $\mathcal{I}$ to changes in clear‐sky radiative cooling rather than stability. These radiative cooling changes are linked to humidity changes driven by warm rain suppression by aerosols. This study's findings underscore the need to take into account microphysical changes, particularly aerosol concentrations, when studying anthropogenic effects on tropical circulation. Plain Language Summary: Clouds intricately couple with the large‐scale overturning circulation in the tropics. Aerosols, small particles suspended in the atmosphere, interact with clouds. Thus, changes in aerosols concentration (Na) have the potential to affect cloud properties and by that the large‐scale circulation, with important implications for tropical climate and climate change. Despite this crucial relationship, the subject has been insufficiently explored. In this paper, I use a simplified, yet realistic, representation of the tropical atmosphere—radiative convective equilibrium large‐domain cloud‐resolving simulations—to investigate the effect of aerosol‐cloud interaction on overturning tropical circulation. By varying Na under diverse sea surface temperatures, I demonstrate that the strength of the overturning circulation intensifies with increasing Na. Utilizing a semi‐analytical expression for subsidence strength in clear‐sky tropical regions, I show that the intensified overturning circulation with increased Na can be attributed to heightened humidity in the mid‐troposphere, leading to intense radiative cooling. This mid‐tropospheric humidification can be explained by warm rain suppression by aerosols, which fosters stronger humidity mixing between clouds and their surroundings. These findings underscore the need to consider aerosol concentration changes when examining anthropogenic impacts on tropical circulation. Key Points: The overturning tropical circulation intensifies with aerosol concentration in a radiative convective equilibrium modelChanges in circulation strength can be explained by changes in diabatic subsidence driven by radiative changesRadiative changes can be explained by increased humidity at the mid‐troposphere due to warm rain suppression [ABSTRACT FROM AUTHOR]

The influence of El Niño‐Southern Oscillation (ENSO) on the North Tropical Atlantic (NTA) sea surface temperature (SST) is well‐documented in boreal spring, yet it manifests greater complexity in winter. Distinct from El Niño, La Niña has a statistically significant impact on winter NTA SST, which is primarily contributed by the re‐occurring (i.e., second and third years of multi‐year) La Niña events. Despite similar atmospheric forcing, prominent SST anomalies are observed in the NTA during the re‐occurring La Niña winters but not in the first‐year La Niña winters, mainly due to different initial states associated with previous tropical Pacific forcing. Targeted pacemaker experiments well reproduce the robust impacts of re‐occurring La Niña events on the wintertime NTA SST, highlighting the crucial impact of ENSO cycle complexity in its inter‐basin linkages. Plain Language Summary: The El Niño‐Southern Oscillation (ENSO) significantly influences the sea surface temperature (SST) in the North Tropical Atlantic (NTA), particularly as ENSO events decay during boreal spring. However, during winter when ENSO reaches its peak, the NTA SST anomalies exhibit strong uncertainty. While no marked SST anomalies are observed in the NTA during El Niño winters, prominent SST anomalies can often be found in the NTA during La Niña winters. The significant La Niña‐related SST anomalies in the NTA are primarily contributed by the second and third years of multi‐year La Niña events, rather than the first‐year La Niña events. The SST difference between the first‐year and re‐occurring La Niña winters can be attributed to the SST initial state in the NTA, which is related to the preceding forcing from the tropical Pacific. By incorporating this initial state, we can more accurately reconstruct the NTA SST anomalies during La Niña winters. Targeted pacemaker experiments corroborate the significant role of re‐occurring La Niña events in influencing wintertime NTA SST. Key Points: La Niña usually has stronger impacts on winter NTA SST than El Niño, primarily contributed by re‐occurring La Niña eventsDifferent NTA SST anomalies during the first‐year and re‐occurring La Niña can be well understood by considering the NTA initial stateTargeted pacemaker experiments confirm the important effect of re‐occurring La Niña on the NTA SST [ABSTRACT FROM AUTHOR]

Prior research extensively investigates the delayed influence of El Niño‐Southern Oscillation (ENSO) events on subsequent summer climates, with persistent sea surface temperature anomalies (SSTAs) in remote tropical oceans serving as crucial pathways. This study unveils a previously overlooked midlatitude pathway. During the developing winter, El Niño events induce basin‐scale cold SSTAs in the central North Pacific, which can persist into the following summer. These anomalies significantly influence early‐summer atmospheric circulation by enhancing atmospheric baroclinicity and transient eddy activities. Primarily driven by transient eddy vorticity forcing, an equivalent barotropic geopotential low anomaly emerges over the North Pacific. Enhanced by the southwesterly winds of the atmospheric low, tropical moisture is transported farther northeastward in the early summer, resulting in increased rainfall in the Pacific Northwest region. By elucidating this meridional pathway, our study advances the understanding of ENSO's delayed impacts and associated dynamical processes, in which the midlatitude oceanic feedbacks are emphasized. Plain Language Summary: The El Niño‐Southern Oscillation (ENSO) events are considered as a primary driver of climate anomalies. Even during their decaying phase, its impact on the Northern Hemisphere summer climate remains notable. This study delves into the intricate mechanisms underlying the delayed impacts of ENSO events on subsequent summer climates. While prior research has extensively explored the zonal pathways involving tropical Indian and Atlantic oceans, this study illuminates a previously overlooked meridional pathway. It reveals that El Niño events trigger significant cold sea surface temperature anomalies (SSTAs) in the North Pacific during their mature phase in winter, which persist into the following summer. These SSTAs wield substantial influence over early‐summer atmospheric circulation, fostering atmospheric baroclinicity and transient eddy activities. Consequently, an anomalous low‐pressure system emerges over the North Pacific in early summer, enhancing southwesterly winds and transporting tropical moisture farther northeastward. This moisture influx results in increased rainfall in the Pacific Northwest region. By elucidating this meridional pathway, the study advances our comprehension of ENSO's delayed impacts, highlighting the crucial role of midlatitude oceanic feedbacks. In essence, it demonstrates how ENSO events can influence North American climate anomalies during subsequent early summer, shedding light on a previously unrecognized pathway of ENSO's effect. Key Points: Cold central North Pacific sea surface temperature anomalies (SSTAs), initiated by El Niño events, can endure into the subsequent summerBy transient eddy forcing, these cold SSTAs induce a whole‐layer geopotential low anomaly over North Pacific in post‐El Niño early summerThus, northeastward moisture transport strengthens, boosting increased early‐summer rainfall in Pacific Northwest after El Niño events [ABSTRACT FROM AUTHOR]

Deep and abyssal layer decadal temperature trends from the mid‐1980s to the mid‐2010s are mapped globally using Deep Argo and historical ship‐based Conductivity‐Temperature‐Depth (CTD) instrument data. Abyssal warming trends are widespread, with the strongest warming observed around Antarctic Bottom Water (AABW) formation regions. The warming strength follows deep western boundary currents transporting abyssal waters north and decreases with distance from Antarctica. Abyssal cooling trends are found in the North Atlantic and eastern South Atlantic, regions primarily ventilated by North Atlantic Deep Water (NADW). Deep warming trends are prominent in the Southern Ocean south of about 50°S, the Greenland‐Iceland‐Norwegian (GIN) Seas and the western subpolar North Atlantic, with cooling in the eastern subpolar North Atlantic and the subtropical and tropical western North Atlantic. Globally integrated decadal heat content trends of 21.6 (±6.5) TW in the deep and 12.9 (±1.8) TW in the abyssal layer are more certain than previous estimates. Plain Language Summary: Even the deepest waters in the ocean, which sink to the abyss around Antarctica after being cooled and made saltier by heat exchange with the atmosphere and sea ice formation, have been shown to be warming around much of the globe in recent decades. The net warming rate below 2000‐m depth accounts for about 10% of total ocean heat uptake, but uncertainties in prior estimates have been about half the size of the signal owing to sparse sampling in the deep ocean. However, new observations from Deep Argo floats, capable of profiling to the ocean floor in most locations, have improved that situation in some regions. Here we analyze these new observations together with historical observations collected from ships since the 1970s to map decadal ocean temperature trends around the globe. As a result, we use more historical data than previous estimates. We refine the local patterns of warming and cooling in the waters deeper than 2,000 m. We confirm the amplitude of the net warming below 2,000 m estimated in previous studies, and extend the time covered by those estimates. The increased data coverage substantially reduces the uncertainty of the net warming estimate. Key Points: Analysis of Deep Argo float and historical ship‐based CTD data reveal global patterns in deep and abyssal layer decadal temperature trendsHigh resolution maps reveal spreading of abyssal warming from Antarctica and cooling from the North Atlantic on sub‐basin spatial scalesGlobally integrated decadal heat content trends are 21.6 (±6.5) TW in the deep and 12.9 (±1.8) TW in the abyssal layer [ABSTRACT FROM AUTHOR]

In December 2022, North America experienced an unprecedented extreme cold event. However, the underlying physical mechanisms of this cold wave, and the extent to which it is driven by internal variability or external forcing, are not fully understood. Using ERA5 reanalysis data and the HadGEM3‐A‐N216 attribution simulations, we identified internal variability as the main cause, contributing −5.14 K to surface air temperature (SAT) anomalies in North America. External forcing slightly mitigated the cold by 0.42 K. An internally generated wave train from the North Pacific, influenced in combination by Pacific‐North American (PNA) and North Pacific Oscillation (NPO) teleconnection patterns, initiated this intense cyclonic event, contributing −2.18 K and −2.12 K to SAT anomalies, respectively. La Niña‐like sea surface temperature anomalies amplified this wave train and resultant cold wave. Additionally, excessive snow cover in the previous November also intensified the December cold anomalies by enhancing surface albedo and reducing solar radiation. Plain Language Summary: In December 2022, North America was hit by an exceptionally severe cold event. Scientists have been trying to understand the reasons behind this cold wave. Using detailed weather data and climate models, researchers found that natural climate variability played a major role, causing temperatures to drop by about 5.14 degrees Celsius. On the other hand, external factors like human‐induced climate change had a minor effect, slightly reducing the severity of the cold by 0.42 degrees Celsius. The study identified an atmospheric wave train pattern, originating from the North Pacific and moving toward North America, which played a crucial role in triggering this extreme weather. Further investigations showed that this wave train was influenced by specific large‐scale weather patterns in the Pacific region, namely the Pacific‐North American (PNA) and North Pacific Oscillation (NPO) patterns, which contributed to the cold temperatures by approximately 2.18 and 2.12 degrees Celsius, respectively. Additionally, colder‐than‐normal sea surface temperatures in the tropical central Pacific, associated with La Niña, strengthened the wave train. Internal thermodynamical processes, such as increased snow cover, also slightly intensified the cold wave by reflecting more sunlight and reducing the amount of solar energy reaching the surface. Key Points: Internal variability triggers 2022 December extreme cold wave in North AmericaPNA and NPO are two key teleconnections responsible for this extreme cold waveSnow cover‐SAT feedback intensifies this extreme cold wave [ABSTRACT FROM AUTHOR]

The interannual variation of the South China Sea (SCS) summer monsoon onset (SMO) may bring extreme weather and climate disasters in East Asia. However, its skillful forecast still remains challenging. This study investigates the intraseasonal ocean‐atmosphere interaction that affects the SCSSMO through diagnostic analysis and numerical experiments. It reveals that the cold sea surface temperature in the Southern SCS during winter (referred as cold tongue, CT) is the key pathway controlling the propagation of the 30–60 days intraseasonal oscillation (ISO) convective system from the Bay of Bengal (BOB) to the SCS. The CT variations affect the interannual variation of the SCSSMO. Specifically, the strong (weak) CT after the peak of La Niña (El Niño) years suppresses (enhances) the propagating ISO from the BOB to the SCS, resulting in a delayed (advanced) SCSSMO. This finding offers the new scientific insights for improving the forecasting of the SCSSMO. Plain Language Summary: The occurrence of a strong cold tongue (CT) in winter, commonly detected in the southern South China Sea (SCS) during La Niña decay years, plays a significant role in delaying the SCS summer monsoon onset (SCSSMO). It adversely affects the northeastward progression of the 30‐60‐day convective Intraseasonal Oscillation (ISO) from the equatorial Indian Ocean to the southern SCS. This interference leads to the delayed onset of the SCSSMO. It highlights the crucial influence of the CT sea surface temperatures (SST) on the linkage between Bay of Bengal and SCS at the intraseasonal scale, thus significantly impacting the timing of the SCSSMO. Key Points: The winter cold tongue in South China Sea (SCS) is a crucial oceanic precursor for the interannual variation of the SCS summer monsoon onset (SCSSMO)Strong cold tongue in the SCS can suppress the propagation of the 30‐60‐day intraseasonal oscillation into the SCSStrong SCS cold tongue during La Niña years tends to delay the SCSSMO [ABSTRACT FROM AUTHOR]

Regional hydrological sensitivity (i.e., precipitation change per degree local surface warming) contributes substantially to the uncertainty in future precipitation projections over tropical oceans. Here, we investigate the sensitivity of relative precipitation (P*, precipitation divided by the basin average precipitation) to local sea surface temperature (SST) change by dissecting it into three components, namely the sensitivity of P* to relative SST (SSTrel, SST minus the tropical mean SST) changes, the sensitivity of P* to surface convergence changes, and the sensitivity of surface convergence to SST gradient changes. We show that the relationships between P* and SSTrel, and between P*, surface convergence, and SST gradients are largely constant during climate change. This allows us to constrain regional hydrological sensitivity based on present‐day SST‐precipitation relationships. The sensitivity of surface convergence to SST gradient changes is a main source of uncertainty in regional hydrological sensitivity and is likely underestimated in GCMs. Plain Language Summary: Understanding how precipitation will change over tropical oceans is important because these changes influence the atmospheric circulation, which in turn affects the global climate and weather patterns. Climate models disagree on their projections of precipitation changes over tropical oceans in part due to a lack of understanding on how precipitation should respond to a given amount of local surface warming. We find that the sensitivity of precipitation to future changes in local sea surface temperature (which is commonly referred to as regional hydrological sensitivity) largely depends on the present‐day relationship between precipitation and local sea surface temperature, as well as that between precipitation and the spatial gradient in sea surface temperature, and both relationships are observable and thus can serve as constraints. We find that inter‐model differences in regional hydrological sensitivity result primarily from differences in the response of surface winds to sea surface temperature gradient changes. Key Points: Regional hydrological sensitivity is an important source of uncertainty in rainfall projections over tropical oceansRegional hydrological sensitivity can be constrained by components of rainfall‐temperature relationship that stay constant during warmingUncertainty in regional hydrological sensitivity originates largely from surface convergence sensitivity to temperature gradient changes [ABSTRACT FROM AUTHOR]

Existing approaches for predicting total water storage (TWS) rely on land surface or hydrological models using meteorological forcing data. Yet, such models are more adept at predicting specific water compartments, such as soil moisture, rather than others, which consequently impedes accurately forecasting of TWS. Here we show that machine learning can be used to uncover relations between nonseasonal terms of Gravity Recovery and Climate Experiment (GRACE) derived total water storage and the preceding hydrometeorological drivers, and these relations can subsequently be used to predict water storage up to 12 months ahead, and even exceptional droughts on the basis of near real‐time observational forcing data. Validation by actual GRACE observations suggests that the method developed here has the capability to forecast trends in global land water storage for the following year. If applied in early warning systems, these predictions would better inform decision‐makers to improve current drought and water resource management. Plain Language Summary: Traditional methods for predicting short‐term/seasonal variations in land total water storages rely on hydrological models. However, these models have a drawback—they are better at predicting water stored in specific parts of the land system like soil moisture than giving an accurate forecast for the overall integrated land total water storage. In this study, we demonstrate the applicability of machine learning in uncovering relationships between the de‐season and de‐linearized terms of global water storage variability as observed by the Gravity Recovery and Climate Experiment (GRACE) satellites, and the preceding hydrometeorological variables such as sea surface temperature. These relationships can then be utilized to forecast monthly changes in land total water storage up to 1 year ahead, and even to predict exceptional drought events based on near real‐time observational forcing data. The validation by actual GRACE observations, lends further credence to the effectiveness of the method developed here, showcasing its potential to forecast trends in global land total water storage for the upcoming year. The potential applications of these predictions in early warning systems are highly promising, and we anticipate that they can assist decision‐makers in enhancing current drought and water resource management practices. Key Points: We identify a stable lag relationship between hydrometeorological variables and the GRACE derived total water storage change (TWSC)Using this stable lag relationship, we are able to forecast the global TWSC up to 1 year ahead with solely observational data as inputsOur forecasts exhibit high consistency with actual GRACE data in terms of global mean land water storage trends for the following year [ABSTRACT FROM AUTHOR]

This study investigates why observed decadal‐scale climate variability is predominantly pronounced in the Niño4 region compared to other equatorial Pacific areas using both observation and model sensitivity experiments. The initial shift to the negative phase of Tropical Pacific Decadal Variability (TPDV) is primarily driven by the upward and eastward migration of isopycnal negative temperature anomalies along the equator. Subsequently, the wind fields associated with the negative phase of the Pacific Meridional Mode (PMM) induce anomalous vertical currents in the equatorial Pacific. This leads to anomalous upwelling and downwelling of mean temperature in the Niño4 and Niño3 regions, respectively, thereby strengthening and weakening the corresponding subsurface‐produced sea surface temperature anomalies. Our findings clarify the roles of subsurface temperature anomalies in the phase reversal of TPDV and PMM in amplifying decadal variance, specifically in the equatorial central Pacific. Plain Language Summary: Observations have consistently highlighted prominent decadal climate variability in the Niño4 region, yet the underlying cause of this distinct pattern remains largely elusive. In this study, we use composite analysis during the phase transition of Tropical Pacific Decadal Variability (TPDV) and modeling experiments to elucidate the mechanisms governing the observed decadal climate variability in the Niño4 region compared to other equatorial areas. Our findings reveal that the eastward and upward propagation of negative subsurface temperature anomalies primarily drives the phase reversal of TPDV. Following this transition from positive to negative phase, the Pacific Meridional Mode (PMM) plays a crucial role. Specifically, PMM‐associated wind forcing induces anomalous upwelling and downwelling in the Niño4 and Niño3 regions, respectively. This results in anomalous vertical advection of mean temperature, contributing to the strengthening and weakening of decadal variances in these regions. Key Points: Subsurface temperature anomalies initiate the phase reversal of TPDV while PMM plays a key role in equatorial SSTAs post‐transitionVertical heat advection is crucial in reinforcing/weakening decadal variance in the Niño4/Niño3 regionPMM‐associated wind fields induce anomalous vertical advection after the TPDV phase transition [ABSTRACT FROM AUTHOR]

As a practical reflection of the opportunity window of Madden‐Julian Oscillation (MJO), there are intermittent periods of relatively high forecasting skills, namely the forecast skill windows. Robust forecast skill windows are identified based on the subseasonal‐seasonal reforecast database, during which the majority of models show high forecast skills. A total of 15 MJO forecast skill windows during 1993–2020 have been identified. Most of the forecast skill windows are closely associated with active MJO events with high amplitude. Whether a high‐skill forecast window appears significantly depends on the magnitude of MJO intensity during the same period. The maintenance of active strong MJO events is potentially related with the warmer surface sea temperature anomalies in the western Pacific. Further research into such processes may unveil the MJO development mechanism and improve the MJO forecast skill. Plain Language Summary: With the continuous development of the economy and society, there is an increasing demand for subseasonal‐seasonal forecasts. The forecast skills of Madden‐Julian Oscillation (MJO) show significant high and low variabilities, associated with specific conditions. MJO forecast skill windows are confirmed based on subseasonal‐seasonal (S2S) forecast products in this study. These windows represent the periods when most models in the S2S database can accurately capture the MJO signal, indicating the MJO forecast skill experiences intermittent enhancements. When the MJO intensity is high in the same period, the high‐skill forecast window is more likely to appear. One potential reason for the maintenance of strong MJO is the anomalously warmer sea surface temperature in the western Pacific, along with other potential factors, providing the opportunity to forecast MJO with high skill. When the opportunity arises, the forecast skill of MJO improves, highlighting the significance of exploring the processes leading to the occurrence of these skill windows. This provides a pathway for more accurate MJO forecasting and improves the predictability of S2S. Key Points: Robust forecast skill windows of Madden‐Julian Oscillation (MJO) are identified based on the subseasonal‐seasonal reforecast databaseThe forecast skill windows are mostly related to strong MJO amplitudeWarmer sea surface temperature anomalies in the western Pacific potentially favors the maintenance of active strong MJO events [ABSTRACT FROM AUTHOR]

The recently‐observed poleward shift in western North Pacific tropical cyclone (TC) genesis has increased the TC threat to East Asia. We find that the poleward shift of TC genesis since 1979 is linked to mega‐ENSO. A downscaling analysis of TC genesis latitude given the constraint of mega‐ENSO using 30 models from the Coupled Model Intercomparison Project Phase 6 (CMIP6) show a continued increasing poleward shift with additional warming. We use the dynamic genesis potential index as a TC proxy in future CMIP6 simulations. These simulations show enhanced TC formation in the subtropics and decreased TC formation in the tropics. Modeled TCs in CMIP6 high‐resolution models that well represent mega‐ENSO project future poleward shifts in TC genesis. Both observations and simulations show that extra‐tropical North Pacific sea surface temperature warming associated with mega‐ENSO are the primary driver of the TC genesis poleward shift. Our study provides new insights into climate change‐driven TC migration. Plain Language Summary: The observed poleward shift in tropical cyclone (TC) genesis over the western North Pacific has increased the threat from these storms to East Asia. Until now, it remains unclear whether TC genesis will continue to move poleward in the future, due to both a relatively short reliable observational TC record as well as model inconsistencies. This study provides evidence that the poleward migration of TC genesis will likely continue due to anthropogenic warming. We find that there is a strong relationship between TC genesis latitude and a mode of Pacific sea surface temperature (SST) variability termed mega‐ENSO. We find using a suite of 30 climate models comprising the Coupled Modeled Intercomparison Project Phase 6 (CMIP6) that future poleward trends in TC genesis latitude are likely to continue. This poleward shift is observed whether using projected trends in mega‐ENSO or an index that measures the conduciveness of the environment for TC formation. Modeled tropical cyclones in high resolution simulations from CMIP6 also show a continued projected poleward shift in TC genesis. This poleward shift in TC genesis appears largely related to changes in extra‐tropical SST warming associated with mega‐ENSO. Key Points: The recently‐observed poleward shift of tropical cyclone (TC) genesis is related strongly to mega‐ENSOChanges in modeled TCs and a TC proxy in a warming climate show a consistent northward TC genesis migrationExtra‐tropical sea surface temperature warming associated with mega‐ENSO appears responsible for poleward TC genesis movement [ABSTRACT FROM AUTHOR]

We investigate the role of the subpolar North Atlantic (SPNA) for downstream predictability, using two decadal climate prediction systems. We use the subpolar extreme cold and fresh anomaly event developing in winter 2013/2014 as initial conditions and evaluate ensemble predictions of the two systems in the following decade. In addition, we perform ensemble pacemaker experiments where the models are forced toward observed ocean temperature and salinity anomalies in the SPNA from November 2014 through December 2019. The pacemaker experiments show improved skill along the Atlantic Water pathway, compared with the standard decadal predictions, and we therefore conclude that the correct description of the ocean in the SPNA is the key. The enhanced skill is most prominent in subsurface salinity in the form of propagating anomalies. Plain Language Summary: Observations show that ocean anomalies propagate across the North Atlantic and further north along the Norwegian coast. Anomalous ocean temperatures can modify heat exchange between ocean and atmosphere and influence the circulation of the atmosphere. Since such anomalies can persist for months, it potentially opens a door to seasonal prediction of the atmosphere. However, climate models used for seasonal and decadal prediction fail to predict these propagating anomalies. In our study we aim to find causes for this lack of predictability. We use the record low temperatures observed in the North Atlantic in 2015 as a test case. We employ two climate prediction systems and make two types of predictions: one type is a standard prediction initialized with winter 2014/2015 ocean conditions; the other type is initialized in the same way and in addition, the model is kept close to observations in the subpolar gyre during the whole prediction, in the region where the cold blob was formed. Comparing the two types of predictions, we see that keeping the model close to observations in the subpolar gyre increases the predictability along the Norwegian coast. This points to the subpolar gyre as a key area where models need to be improved. Key Points: Knowing temperature and salinity in the subpolar gyre increases skill downstream along the Atlantic Water pathwaySalinity anomalies propagate northward, while temperature anomalies are more difficult to traceA pacemaker experiment has been used for decadal predictions for the first time [ABSTRACT FROM AUTHOR]

Sea ice formation over open water exerts critical control on polar atmosphere‐ocean‐ice interactions, but is only crudely represented in sea ice models. In this study, a collection depth parameterization of new ice for flux polynya models is modified by including the sea ice concentration and ice growth rate as additional factors. We evaluated it in a climate model BCC‐CSM2‐MR and found that it improves simulation of Antarctic sea ice concentration and thickness in most of Indian and Atlantic sectors. Disagreement between the observed Antarctic sea ice expansion during 1981–2014 and the modeled decline still exists but is mitigated when the modified scheme is implemented. Further analysis indicates that these improvements are associated with the overcoming of premature closure of open water, which enhances the response of ocean to surface wind intensification during 1981–2014, and consequently slowdowns the sea surface temperature increase and the resulting Antarctic sea ice reduction. Plain Language Summary: Open water ice formation critically modulates sea ice variations and the associated polar atmosphere‐ocean interaction, but is not well represented in sea ice models. In this study, a modified collection depth parameterization of new ice based on an existing scheme is presented after including sea ice concentration and ice growth rate as additional factors. We evaluated this modified scheme in BCC‐CSM2‐MR and found that it can improve the simulation of mean Antarctic sea ice thickness and concentration in winter as well as Antarctic sea ice expansion from 1981 to 2014. Further analysis implies that these improvements can be attributed to the overcoming of the premature closure of open water areas in model simulations. Key Points: A modified collection thickness parameterization of new ice suitable for large‐scale climate simulations is presentedIt improves the simulation of Antarctic sea ice thickness and concentration, as well as Antarctic sea ice expansion during 1981–2014The improved simulations can be attributed to the overcoming of the premature closure of open water areas where new ice forms [ABSTRACT FROM AUTHOR]

Sea surface temperature (SST) anomalies over the North Tropical Atlantic (NTA) during the early boreal spring can trigger El Niño‐Southern Oscillation (ENSO) events in the following boreal winter. However, the future changes in the impact of the NTA on ENSO remain controversial. Here, we show distinct changes in the strength of the NTA−ENSO relationship due to global warming by comparing models from the Coupled Model Intercomparison Project (CMIP) 5 and CMIP6. The impact of the NTA on ENSO under greenhouse warming is notably enhanced in CMIP6 compared to CMIP5. A wetter mean state over the subtropical eastern North Pacific and increased oceanic sensitivity over the equatorial central Pacific are key factors that enhance the impact of the NTA SST on ENSO. Therefore, differences in the mean state under greenhouse warming between the CMIP5 and CMIP6 models can modulate the strength of the NTA−ENSO relationship. Plain Language Summary: The North Tropical Atlantic (NTA) region can affect the development of El Niño events, significantly impacting global weather systems. Our study compares two generations of climate models, CMIP5 and CMIP6, to understand how the influence of the NTA sea surface temperature (SST) on El Niño might change due to global warming. We found that the influence of the NTA SST on El Niño is stronger in the CMIP6 models than in the CMIP5 models. This stronger impact is due to changes in the climatological background states, including a wetter mean state over the subtropical eastern North Pacific and increased oceanic sensitivity over the equatorial central Pacific. Understanding these changes is crucial for improving predictions of future climate variabilities and their potential impacts on weather, ecosystems, and food production worldwide. Key Points: The relationship between the North Tropical Atlantic (NTA) and El Niño‐Southern Oscillation (ENSO) is significantly enhanced by global warming in CMIP6 compared to CMIP5Mean state change under greenhouse warming is responsible for the strengthening of the NTA‐ENSO relationship [ABSTRACT FROM AUTHOR]

Since the 1950s, observations and climate models show an amplification of sea surface temperature (SST) seasonal cycle in response to global warming over most of the global oceans except for the Southern Ocean (SO), however the cause remains poorly understood. In this study, we analyzed observations, ocean reanalysis, and a set of historical and abruptly quadrupled CO2 simulations from the Coupled Model Intercomparison Project Phase 6 archive and found that the weakened SST seasonal cycle over the SO could be mainly attributed to the intensification of summertime westerly winds. Under the historical warming, the intensification of summertime westerly winds over the SO effectively deepens ocean mixed layer and damps surface warming, but this effect is considerably weaker in winter, thus weakening the SST seasonal cycle. This wind‐driven mechanism is further supported by our targeted coupled model experiments with the wind intensification effects being removed. Plain Language Summary: The Southern Ocean (SO) sea surface temperature (SST) has experienced a decreased seasonal cycle since the 1950s, in contrast with the overall amplified seasonal cycle in the rest of global oceans. Here we investigated observations and climate model simulations and found that the decrease of SST seasonal cycle was associated with less warming in summer than in winter during the historical period. The suppressed warming in summer is accompanied by a deepened ocean mixed layer due to the intensification of surface westerlies. An enhanced mixed layer depth means the incoming heat flux will be trapped in a deeper mixed layer in summer, causing a cooler summer SST, which then leads to a weaker SST annual cycle. When the wind intensification effect is removed in our model simulations, the decreased SST seasonal cycle in the SO disappears. Key Points: Observations and climate models show a weakening sea surface temperature (SST) seasonal cycle induced by the delayed warming of summer SST over Southern Ocean (SO)The summer mixed layer depth and wind stress show increasing trends during the same period over the SOThe summer wind‐induced mixed layer deepening suppresses SO surface warming and thus weakening the SST seasonal cycle [ABSTRACT FROM AUTHOR]

El Niño Southern Oscillation (ENSO) diversity is characterized based on the longitudinal location of maximum sea surface temperature anomalies (SSTA) and amplitude in the tropical Pacific, as Central Pacific events are typically weaker than Eastern Pacific events. SSTA pattern and intensity undergo low‐frequency modulations, affecting ENSO prediction skill and remote impacts, and resulting in low‐frequency changes in ENSO variance. Yet, how different ENSO types contribute to these decadal variance changes remains unclear. Here, we decompose the low‐frequency changes of ENSO variance into contributions from ENSO diversity categories. We propose a fuzzy clustering of monthly SSTA to allow for non‐binary event category memberships, where each event can belong to different clusters. Our approach identifies two La Niña and three El Niño categories and shows that the major shift of ENSO variance in the mid‐1970s was associated with an increasing likelihood of strong La Niña and extreme El Niño events. Plain Language Summary: The El Niño Southern Oscillation (ENSO) is a climate phenomenon that involves changes in ocean temperatures in the central and eastern tropical Pacific and greatly influences the weather around the globe. ENSO events are usually categorized based on where these temperature variations are the strongest and how intense they are. However, these categories are at times ambiguous and the way ENSO behaves can change over decades. Our study introduces a new way to estimate how different kinds of ENSO events contribute to its overall variation over time. We base our variability analysis on a fuzzy categorization of ENSO events, which results in three different kinds of El Niño events and two kinds of La Niña events. We find that the decadal changes in ENSO variance, including the decadal shift in the mid‐1970s, were primarily associated with strong La Niña and extreme El Niño events. Key Points: Using a fuzzy categorization, five different El Niño Southern Oscillation (ENSO) types are identified in observationsExtreme El Niño events emerge as a distinct categoryStrong La Niña and Extreme El Niño categories mainly contributed to the shift in decadal ENSO variance around 1970 [ABSTRACT FROM AUTHOR]

Tropical cyclones (TCs) induce substantial upper‐ocean mixing and upwelling, leading to sea surface cooling. In this study, we explore changes in TC‐induced cold wakes along the United States (U.S.) Southeast and Gulf Coasts during 1982–2020. Our study shows a significant increase in TC‐induced sea surface temperature (SST) cooling of about 0.20°C near the U.S. Southeast Coast over this period. However, for the U.S. Gulf Coast, trends in TC‐induced SST cooling are insignificant. Analysis of the large‐scale oceanic environments indicate that the increasing TC‐induced cold wakes near the Southeast coast have been predominantly caused by the cooling of subsurface waters in that region. This upper‐ocean change is attributed to the enhancement of surface pressure gradient across land‐sea boundary and the associated increase in alongshore winds over there. Further analysis with climate models reveals the important role of anthropogenic forcings in driving these changes in the atmospheric circulation response along the U.S. Southeast Coast. Plain Language Summary: Tropical cyclones (TCs) can induce strong mixing in the upper ocean and upwelling of cold, nutrient‐rich water from subsurface to the surface. This process can induce significant sea surface cooling and enhance primary productivity. Utilizing satellite observations, we found evidence that the sea surface cooling associated with TCs has been increasing significantly in the near‐shore regions of United States (U.S.) Southeast Coast. However, corresponding trends in the U.S. Gulf Coast are not significant. Here we show that the enhanced TC‐induced SST cooling along the U.S. Southeast Coast has occurred in response to changes in the atmospheric circulation associated with global warming. These findings shed light on the potential changes in the interactions between TCs and the upper ocean conditions under a non‐stationary climate. Key Points: The tropical cyclone induced sea surface temperature cooling has significantly increased near the U.S. Southeast Coast in recent decadesThe increasing trend in TC‐induced cold wake is primarily attributed to subsurface cooling driven by the change in atmospheric circulationClimate models suggest greenhouse gases are likely responsible for the atmospheric circulation changes [ABSTRACT FROM AUTHOR]

Using observations and CMIP6 historical simulations, the seasonal responses of Southern Ocean (50°S–70°S) sea surface temperature (SST) to Southern Annular Mode (SAM) variations are investigated in this study. The results suggest that the averaged Southern Ocean SST in austral spring and summer show a significant cooling in response to a positive SAM, while the responses in austral autumn and winter are negligible. The cooling effect is resulted from the cold water in higher latitudes and deeper oceans brought by the equatorward Ekman transport and the Ekman pumping associated with the positive SAM. Among CMIP6 models, the magnitude of the simulated cooling response connects to the climatological meridional and vertical ocean temperature gradients, and the magnitude of Ekman motion in response to SAM. In addition, the spring and summer SAM plays a more important role in modulating Southern Ocean SST in autumn and winter than the autumn and winter SAM. Plain Language Summary: Southern Annular Mode (SAM) is the first leading mode of atmospheric circulation in extratropical Southern Hemisphere and has an important influence on climate. This study evaluates the seasonal response of Southern Ocean SST to SAM variations in the CMIP6 historical simulations. We found that the regional averaged Southern Ocean sea surface temperature (SST) in austral spring and summer shows significant cooling signals in response to positive SAM. The responses of mean SST over Southern Ocean in austral autumn and winter to SAM during same seasons are not significant. The strengthening in Ekman transport and Ekman pumping in response to positive SAM would bring cold water from higher latitudes and deeper ocean to ocean surface, and hence, lead to a cooling effect. In addition, the simulations with a larger climatological meridional or vertical temperature gradient and stronger Ekman movements in response to positive SAM tends to generate a stronger cooling signal over Southern Ocean driven by positive SAM. Further analysis indicates that the austral spring and summer SAM has a more significant impact on Southern Ocean SST in austral autumn and winter, which might explain why the responses of Southern Ocean SST in austral autumn and winter to simultaneous SAM are not statistically significant. Key Points: The Southern Ocean sea surface temperature (SST) show a significant cooling in response to positive Southern Annular Mode (SAM) in austral spring and summerThe Ekman movements associated with enhanced SAM bring cold water from higher latitudes and deeper ocean, causing cooling effectsSAM in spring and summer play a more important role in modulating the autumn and winter SST than the SAM in autumn and winter [ABSTRACT FROM AUTHOR]

Near‐term projections of drought in the southwestern United States (SWUS) are uncertain. The observed decrease in SWUS precipitation since the 1980s and heightened drought conditions since the 2000s have been linked to a cooling sea surface temperature (SST) trend in the Equatorial Pacific. Notably, climate models fail to reproduce these observed SST trends, and they may continue doing so in the future. Here, we assess the sensitivity of SWUS precipitation projections to future SST trends using a Green's function approach. Our findings reveal that a slight redistribution of SST leads to a wetting or drying of the SWUS. A reversal of the observed cooling trend in the Central and East Pacific over the next few decades would lead to a period of wetting in the SWUS. It is critical to consider the impact of possible SST pattern trends on SWUS precipitation trends until we fully trust SST evolution in climate models. Plain Language Summary: Precipitation trends in the southwestern United States (SWUS) are sensitive to the pattern of sea surface temperature (SST) trends in the Tropical Pacific. Since the turn of the century, a decrease in SWUS precipitation has been linked to a cooling of the Central and Eastern Pacific (1990–2020). Notably, climate models are unable to simulate this observed cooling SST trend. In this study, we answer how SWUS precipitation projections may be impacted by potential error in the simulation of future SST trends by climate models. We first demonstrate that slight changes in the pattern of SST trends leads to either a wetting or drying of the SWUS. Second, if the current 30‐year cooling trend in the Central and East Pacific switches to a warming trend, the SWUS could experience a near‐term increase in precipitation. While climate models are the main tool to predict the global response to anthropogenic climate change, we must consider and account for their error in projections of global warming. Key Points: The observed Equatorial Pacific cooling trend, unpredicted by climate models, may have led to decreased precipitation in the southwestern USWith a sea surface temperature‐precipitation Green's function, we find that small changes in sea surface temperature can either wet or dry the southwestern USA reversal of the cooling trend in the Equatorial Pacific could lead to a wetting trend in the southwestern US [ABSTRACT FROM AUTHOR]

We utilize ocean 10‐m wind speed (U10m) from the microwave Multi‐sensor Advanced Climatology data set to examine the coupling between convective cloud and precipitation processes, synoptic state, and U10m and to evaluate the representation of U10m in global climate models (GCMs). We find that midlatitude U10m is underestimated by GCMs relative to observations. We examine two potential mechanisms to explain this model behavior: cold pool formation in cold air outbreaks (CAOs) associated with downdrafts that enhance U10m and sea surface temperature (SST) gradients affecting U10m through thermally forced surface winds at regional scales. When the effects of the CAO index (M) and SST gradients on U10m are accounted for, a relationship between GCM horizontal resolution and U10m appears. The strongest correlation between resolution and U10m is over the western boundary currents characterized by frequent CAOs atop strong SST gradients which drives the strongest surface fluxes on Earth. Plain Language Summary: Surface wind drives the exchange of momentum and energy between the atmosphere and ocean, forcing movement of ocean surface water that impacts the circulation responsible for transporting heat and carbon. It is thus important to study how well global climate models (GCMs) simulate near surface winds. Here, we show an underestimation of ocean surface wind in the latest‐generation of GCMs and examine how an underestimation of ocean surface winds covaries with biases in surface temperature and fine‐scale precipitation‐driven circulations. We show the effect of model horizontal grid resolution on the wind speed bias and analyze surface wind speed bias occurrence in western boundary currents. Key Points: Coupled model intercomparison project (CMIP6) models underestimate midlatitude ocean surface wind speed compared to spaceborne microwave radiometersSimulated ocean surface wind speed bias scales with model resolution at a magnitude strongly influenced by meteorologyOcean surface wind speed bias is most correlated with resolution in western boundary currents [ABSTRACT FROM AUTHOR]

Local meteorology over the Great Barrier Reef (GBR) can significantly influence ocean temperatures, which in turn impacts coral ecosystems. While El Niño–Southern Oscillation (ENSO) provides insight into the expected synoptic states, it lacks details of anticipated sub‐seasonal weather variability at local scales. This study explores the influence of the Madden‐Julian oscillation (MJO) on Australian tropical climate, both independently and in combination with ENSO, focusing on GBR impacts. We find that during El Niño periods, including the summer of 2009/10, faster propagating MJO patterns can disrupt background warm, dry conditions, and potentially provide cooling relief via increased cloud cover and stronger winds. In La Niña periods, such as the summer of 2021/22, the MJO tends to be prevented from passing the Maritime continent, forcing it to remain in a standing pattern in the Indian Ocean. This leads to decreased cloud cover and weaker winds over the GBR, generating warm ocean anomalies. Plain Language Summary: Bleaching is likely when tropical corals are exposed to ocean temperatures above a threshold for a prolonged period. In austral summer, tropical weather over the Great Barrier Reef (GBR) can vary from hot and sunny to stormy with rain and strong winds. During El Niño, summer weather over the GBR is typically warm, still, and dry, increasing the likelihood of coral bleaching due to increased exposure to solar radiation and decreased mixing. During La Niña, tropical storms, with cooling effects through increased rainfall and cloud cover, are more typical. The Madden‐Julian oscillation (MJO) is an eastward moving storm pattern near the equator that can also influence the background climate over the GBR. We find that the MJO can significantly influence the weather variability over the GBR, altering the expected states of El Niño and La Niña periods. Key Points: Composite maps show how the Madden‐Julian oscillation (MJO) can change meteorological patterns on the Great Barrier ReefCluster analysis is used to show the types of MJO propagation patterns likely to occur during El Niño and La Niña periodsOcean temperature variability is discussed with El Niño/La Niña phases as the background states and the MJO as a sub‐seasonal modulator [ABSTRACT FROM AUTHOR]

A machine learning method is used to identify sources of long‐term ENSO predictability in the ocean (sea surface temperature (SST) and heat content) and the atmosphere (near‐surface zonal wind (U10)). Tropical SST represents the primary source of predictability skill. While U10 does not increase the skill when associated with SST, our analysis suggests U10 alone has apredictive skill comparable to that of SST between 11 and 21 months in advance, from late fall up to late spring. The long‐lead signal originates from coupled wind‐SST interactions across the Indian Ocean (IO) and propagates across the Pacific via an atmospheric bridge mechanism. A linear correlation analysis supports this mechanism, suggesting a precursor link between anomalies in SST in the western and wind in the eastern IO. Our results have important implications for ENSO predictions beyond 1 year ahead and identify the key role of U10 over the IO. Plain Language Summary: Many extreme events, such as floods or droughts, can be attributed to the El Niño Southern Oscillation, a mode of large‐scale ocean‐atmosphere coupled variability in the tropical Pacific Ocean occurring with a period of approximately 4 years. In this analysis, we use a machine learning methodology to disentangle the key atmospheric and oceanic ENSO components' relative contribution to its predictability, particularly the role of near‐surface 10‐m zonal wind. We quantify the potential for improved ENSO predictions for up to 2 years in advance and present a mechanistic understanding of the location of the sources of predictability. While equatorial sea surface temperature represents the primary source of ENSO predictability, the equatorial U10 plays a vital role from late spring to fall, from 1 to 2 years in advance. The enhanced predictability skill is shown to be linked to an SST anomaly originating in the Indian Ocean. The ML model used provides a new way to get new insights into the sources of predictability for ENSO and can be used as a simple but powerful tool to improve the underlying mechanistic understanding. Key Points: A deep learning‐based approach suggests near‐surface 10 m wind to play a significant role in providing skills for long‐term ENSO predictabilityThe skill of the 10‐m zonal wind is large from 12 months up to 23 months in advance (depending on the season)The signal is generated by coupled wind‐SST interactions in the Indian Ocean and later propagates across the Pacific [ABSTRACT FROM AUTHOR]

The behavior of the El Niño–Southern Oscillation (ENSO) has undergone significant changes since the year 2000. Meanwhile, a notable westward shift and strengthening in the atmosphere‐to‐ocean Bjerknes feedback were observed. We find that this shift can be primarily attributed to a weakened relationship between the zonal gradient of precipitation anomaly and that of sea surface temperature (SST) anomaly since 2000.This weakened relationship is a comprehensive manifestation of reduced El Niño‐related precipitation anomalies in the central‐eastern tropical Pacific and increased anomalies in the western tropical Pacific. These changes are connected to the mean state change in the tropical Pacific after 2000, where the cooler background SSTs in the central‐eastern tropical Pacific suppress upward motion, and the warmer background SSTs in the western tropical Pacific promote upward motion in the overlying atmosphere. Our findings offer a potential explanation for the westward shift and strengthening in the atmosphere‐to‐ocean Bjerknes feedback since 2000. Plain Language Summary: The El Niño–Southern Oscillation (ENSO) is a climate phenomenon that plays a major role in global weather and climate systems. The development of ENSO is mainly attributed to a positive feedback known as the Bjerknes feedback, which represents the atmospheric response to the oceanic forcing and vice versa. It is noted that ENSO has behaved differently since the year 2000. Concurrently, a pronounced westward movement and strengthening in the atmosphere‐to‐ocean Bjerknes feedback have also been observed. Analyses show that changes in the Bjerknes positive feedback are largely due to a weakened relationship between anomalous rainfall patterns and sea surface temperatures (SSTs). This implies that during El Niño events, there is less rainfall in the central and eastern parts of the tropical Pacific, and more rainfall in the western tropical Pacific. These changes are linked to a cooling of background SSTs in the central‐eastern tropical Pacific, which reduces the upward air movement and rainfall in that region, and a warming of background SSTs in the western Pacific, which promotes the upward air movement and rainfall. Key Points: Westward shift and strengthening of the atmosphere‐to‐ocean Bjerknes feedback in the tropical Pacific have been observed since 2000A weakened precipitation‐to‐sea surface temperature (SST) response drives the changes in the atmosphere‐to‐ocean Bjerknes feedbackChanges in precipitation‐to‐SST response are linked to the interdecadal shift in the tropical Pacific background state [ABSTRACT FROM AUTHOR]

The long‐term memory of the ocean makes sea surface temperature anomalies (SSTAs) become a significant predictor for the subsequent atmosphere, and the tropical ocean is primarily regarded as a major source of atmospheric anomalies. While in North Pacific, the local midlatitude SSTAs also have large contributions but have not been adequately considered yet. We discover a strong connection between the Kuroshio‐Oyashio Extension (KOE) SSTAs in spring and the local atmospheric circulation anomalies in following summer at interannual timescale, wherein, the spring KOE SSTAs are generally independent of tropical ocean, and they are primarily induced by the concurrent atmospheric anomalies via surface heat flux and ocean dynamic processes. The spring KOE SSTAs can persist to summer, and then generate nearly reversed whole‐layer atmospheric circulation anomalies in their north side through both diabatic heating and atmospheric transient eddy forcing. Consequently, precipitation anomalies in Pan‐Pacific regions are distinctly modulated from spring to summer. Plain Language Summary: Because of the vast heat‐holding capacity and the long‐term memory of ocean, sea surface temperature anomalies (SSTAs) are usually taken as the significant factors to understand and predict climate anomalies. On interannual timescale, attentions have primarily centered on the tropical SSTAs, but recent studies indicated that the SSTAs in mid‐to‐high latitudes, especially in the Kuroshio‐Oyashio Extension (KOE) could have important feedbacks on the atmosphere. In this study, the KOE SSTAs in spring are discovered to have large interannual variability, and they are independent of the tropical SSTAs but closely linked to the subsequent summer atmospheric anomalies. It is found that the spring KOE SSTAs are mainly forced by the atmosphere via the surface heat flux and the ocean dynamic processes. In turn, they can persist to summer, and then play a dominant role in the air‐sea interaction in North Pacific, inducing remarkable geopotential height anomalies in north side. Consequently, in terms of the KOE SSTAs evolving from spring to summer, the Pan‐Pacific precipitation anomalies are distinctly modulated due to the opposite air‐sea interaction processes in the two seasons. These findings advocate for the use of springtime KOE SSTAs as a predictive indicator for following summer atmospheric and precipitation conditions. Key Points: The spring Kuroshio‐Oyashio Extension (KOE) sea surface temperature anomalies (SSTAs) are independent of tropical ocean and primarily forced by the concurrent local atmosphere at interannual timescaleThe spring KOE SSTAs can persist to summer and exert a delayed cross‐season impact on the subsequent summer atmosphereAssociated with the spring KOE SSTAs, precipitation anomalies in Pan‐Pacific regions are distinctly modulated from spring to summer [ABSTRACT FROM AUTHOR]

We investigate the role of ocean heat transport (OHT) in driving the decadal variability of the Arctic climate by analyzing the pre‐industrial control simulation of a high‐resolution climate model. While the OHT variability at 65°N is greater in the Atlantic, we find that the decadal variability of Arctic‐wide surface temperature and sea ice area is much better correlated with Bering Strait OHT than Atlantic OHT. In particular, decadal Bering Strait OHT variability causes significant changes in local sea ice cover and air‐sea heat fluxes, which are amplified by shortwave feedbacks. These heat flux anomalies are regionally balanced by longwave radiation at the top of the atmosphere, without compensation by atmospheric heat transport (Bjerknes compensation). The sensitivity of the Arctic to changes in OHT may thus rely on an accurate representation of the heat transport through the Bering Strait, which is difficult to resolve in coarse‐resolution ocean models. Plain Language Summary: We studied how ocean heat transport (OHT) affects decade‐timescale variability in the Arctic climate using a high‐resolution climate model. Specifically, we compared the impacts of heat entering the Arctic Ocean through the Nordic Seas from the Atlantic and through the Bering Strait from the Pacific. Though more heat is transported from the Atlantic, Arctic surface temperature and sea ice respond more strongly to changes in OHT through the Bering Strait. Unlike Atlantic OHT, changes in Bering Strait OHT impact local air temperatures directly, without compensating changes in atmospheric heat transport. Proper representation of the Arctic's sensitivity to future increased OHT may thus rely on correctly representing OHT through Bering Strait, which is challenging in coarse‐resolution ocean models. Key Points: Ocean heat transport variability through the Bering Strait has an outsized effect on Arctic sea ice cover and surface temperatureAtlantic ocean heat transport anomalies into the Arctic are compensated by atmospheric heat transport anomalies on decadal timescales [ABSTRACT FROM AUTHOR]

We use neural networks and large climate model ensembles to explore predictability of internal variability in sea surface temperature (SST) anomalies on interannual (1–3 years) and decadal (1–5 and 3–7 years) timescales. We find that neural networks can skillfully predict SST anomalies at these lead times, especially in the North Atlantic, North Pacific, Tropical Pacific, Tropical Atlantic and Southern Ocean. The spatial patterns of SST predictability vary across the nine climate models studied. The neural networks identify "windows of opportunity" where future SST anomalies can be predicted with more certainty. Neural networks trained on climate models also make skillful SST predictions in reconstructed observations, although the skill varies depending on which climate model the network was trained. Our results highlight that neural networks can identify predictable internal variability within existing climate data sets and show important differences in how well patterns of SST predictability in climate models translate to the real world. Plain Language Summary: We train neural networks (a machine learning model) to predict sea surface temperature (SST) between 3 and 7 years in the future. The neural networks are trained using data from existing climate model simulations. The regions where neural networks make the most accurate predictions depend on which climate model is used for training. The neural networks also make accurate predictions when given a data set of reconstructed SST observations, which means some of the patterns learned from the climate models also apply to the real climate system. However, there are unique differences between prediction accuracy in climate models and the reconstructed observations, which suggests directions for future research. Key Points: Neural networks can learn predictable signals of internal sea surface temperature (SST) variability at 1–3, 1–5, and 3–7 years lead timesNeural networks trained on climate model output can skillfully predict SST variability in reconstructed observationsNeural network skill in predicting observed SST variability depends on the climate model used for training [ABSTRACT FROM AUTHOR]

The Arctic sea ice cover has decreased rapidly over the last few decades both in extent and thickness. Here we present multi‐year (2013–2022) observations of sea ice thickness in the northwestern Barents Sea based on Upward Looking Sonar measurements and show that the winter sea ice has become thicker over the last decade. Sea ice thickness from the Pan‐Arctic Ice Ocean Modeling and Assimilation System (PIOMAS) reproduces both the observed variability and recent 10‐year trend and shows that this thickening (0.24 m decade−1) has not been seen since the 1990s. Using PIOMAS we find that the recent increase in sea ice thickness can be explained by increased sea ice freezing as a result of lower temperatures in the ocean and in the atmosphere. The recent thickening is set in the context of a long‐term thinning trend, with PIOMAS showing much thinner ice now than in the 1980s. Plain Language Summary: The Arctic sea ice cover is becoming smaller and thinner due to global warming. We have measured sea ice thickness in the Barents Sea since 2013, and find that the ice thickness has increased since the measurements were initiated, contrary to what we would expect in a warming world. The Arctic sea ice cover can, however, increase for periods typically up to a decade due to natural climate variability. We find that increased sea ice formation due to lower ocean and air temperatures has caused the recent thickening of the ice cover. We also find that the Barents Sea ice thickness has decreased since the 1980s, and despite the recent thickening, the ice cover is much thinner now than it used to be. Key Points: Upward Looking Sonar measurements in the Barents Sea show increased sea ice thickness during the last decadeIn an ice‐ocean reanalysis (PIOMAS) the recent thickening is due to increased ice freezing, associated with lower ocean and air temperaturesThe long‐term thickness trend is negative, meaning that despite recent thickening, ice is now much thinner than in the 1980s [ABSTRACT FROM AUTHOR]

Previous modeling studies indicate that even though marine cloud brightening under a susceptibility‐based strategy is effective in reducing the global average surface temperature, it triggers a La Niña‐like sea‐surface temperature response with cooling mostly confined within lower latitudes. Here we explore a different cloud seeding strategy involving seeding of regions with low susceptibility, primarily over the ocean in midlatitudes during the winter. Simulations with the Community Earth System Model, version 2 reveal that because the regional forcing is weaker and more widespread, cooling is more evenly distributed over the globe. This new strategy also does not result in the La Niña‐like state seen in the other strategies. Plain Language Summary: Most previous marine cloud brightening (MCB) simulations have focused on the regions more likely to induce strong cooling. A common response in these simulations across different climate models is a La Niña‐like sea surface temperature pattern which could disrupt the El Niño Southern Oscillation. We explored simulations in which MCB is deployed over the least susceptible regions rather than the most susceptible. This new seeding strategy cools the globe more evenly and no longer triggers a La Niña‐like response. Key Points: We explore the idea of deploying marine cloud brightening (MCB) over broader regions with low susceptibility to cloud seedingThis approach induces fairly uniform cooling over the globe unlike MCB that targets the most susceptible regionsThis new seeding strategy has fewer climatic side effects and does not trigger a La Niña‐like response [ABSTRACT FROM AUTHOR]

The El Niño–Southern Oscillation (ENSO) teleconnection to Europe is projected to strengthen under global warming in most climate model simulations. However, given the current difference between recent observations and historical model simulations of tropical Pacific sea surface temperature trends, with models simulating an El Niño‐like warming in recent decades which is in disagreement with observations, it is important to understand the relative contributions of changes to the teleconnection forcing and background state to the overall teleconnection change. Using idealized climate model experiments, we show that both the eastward shift of El Niño precipitation and background state changes make contributions to the overall teleconnection change. These results suggest that the ENSO–Europe teleconnection can be expected to strengthen under global warming, even if ENSO precipitation anomalies do not shift eastwards as currently projected. However, the magnitude of the strengthening may depend on how much of an eastward shift does occur. Plain Language Summary: El Niño–Southern Oscillation (ENSO) can influence the weather and climate in Europe, and this connection is expected to become stronger under global warming according to most climate models. However, there is a difference between recent observations of sea surface temperatures in the Pacific Ocean and what climate models simulate. These differences could have important implications for future projections of ENSO's impact on Europe. To understand how likely the projected future strengthening of this link is, we looked at how two factors contribute to this connection change: (a) changes in rainfall associated with El Niño in the tropical Pacific and (b) overall changes in global climate elsewhere. Using a simplified climate model, we found that both these factors play a role in making the connection between El Niño and Europe stronger. This suggests that even if the specific patterns of El Niño rainfall don't change as projected, the link between El Niño and Europe will still get stronger due to global warming. However, how much stronger it gets might depend on the actual changes in El Niño rainfall, so it's important to figure out why there's a difference between observations and the model projections of Pacific Ocean temperature trends. Key Points: The El Niño–Southern Oscillation teleconnection to Europe is projected to strengthen under global warmingThis change is driven by an eastward shift of El Niño precipitation anomalies in the tropical Pacific and background state changes globallyBackground state changes have a greater impact on European circulation than precipitation changes, particularly over central‐eastern Europe [ABSTRACT FROM AUTHOR]

Quantitative constraints on past mean ocean temperature (MOT) critically inform our historical understanding of Earth's energy balance. A recently developed MOT proxy based on paleoatmospheric Xe, Kr, and N2 ratios in ice core air bubbles is a promising tool rooted in the temperature dependences of gas solubilities. However, these inert gases are systematically undersaturated in the modern ocean interior, and it remains unclear how air‐sea disequilibrium may have changed in the past. Here, we carry out 30 tracer‐enabled model simulations under varying circulation, sea ice cover, and wind stress regimes to evaluate air‐sea disequilibrium in the Last Glacial Maximum (LGM) ocean. We find that undersaturation of all three gases was likely reduced, primarily due to strengthened high‐latitude winds, biasing reconstructed MOT by −0.38 ± 0.37°C (1σ). Accounting for air‐sea disequilibrium, paleoatmospheric inert gases indicate that LGM MOT was 2.27 ± 0.46°C (1σ) colder than the pre‐industrial era. Plain Language Summary: The ocean plays a central role in Earth's climate system as a major reservoir of heat. Understanding how ocean heat content (OHC) changed in the past is therefore key to unraveling the history of global climate. Xenon, krypton, and nitrogen trapped in ice core air bubbles offer a means of reconstructing past OHC, because changes in global ocean temperature affect the solubilities of these gases in seawater, leading to corresponding changes in their atmospheric abundances. For example, a colder ocean can hold more xenon, meaning less xenon resides in the atmosphere. However, these gases in the ocean today are slightly out of equilibrium with the atmosphere (i.e., they are undersaturated), and it remains unclear to what extent this disequilibrium could have changed in the past. We carried out global atmosphere‐ocean model simulations, finding that undersaturation was likely reduced in the Last Glacial Maximum (LGM), a colder era of global climate ∼20,000 years ago. Our analysis suggests that a small component of the additional xenon in the colder LGM ocean arose from this change in air‐sea disequilibrium. After accounting for this effect, ice core noble gas measurements suggest a slightly warmer LGM ocean than previously thought. Key Points: Global ocean air‐sea gas exchange simulations suggest reduced undersaturation of inert gases in the Last Glacial Maximum (LGM) oceanReduced LGM undersaturation indicates a small cold bias in mean ocean temperature (MOT) reconstruction from ice core noble gasesA revised estimate of MOT, accounting for air‐sea disequilibrium, is 2.27 ± 0.46°C colder than the pre‐industrial era [ABSTRACT FROM AUTHOR]

Coastal El Niño is an extreme situation of El Niño‐Southern Oscillation (ENSO) with sea surface temperature warming confined in the far‐eastern equatorial Pacific. Some coastal El Niños evolve into a basin scale El Niño, and some don't, implying a diversity in ENSO evolutions after a coastal El Niño event. In this study, the coastal El Niños in 2017 and 2023 are selected to examine their subsequent evolution. Both coastal El Niños developed after a La Niña, with the former followed by a La Niña and the latter by a basin‐scale El Niño. The cold (warm) subsurface temperatures in 2017 (2023) were key factors leading to the divergent ENSO evolution. Convection over the western tropical Pacific and the atmospheric circulation anomalies across the equatorial Pacific also contributed to the differences. Model predictions suggest that differences in ENSO evolution after a coastal El Niño are associated with differences in ENSO predictability. Plain Language Summary: Compared with the global impact of basin‐scale El Niño–Southern Oscillation (ENSO) events, coastal El Niño impacts are mainly focused along the South American coast. They are less studied, especially, in terms of temporal evolution and longer‐term development. Here, we examine the divergent evolution of ENSO conditions in the tropical Pacific after the coastal El Niños in 2017 and 2023. This subsequent divergent evolution of these events was associated with both preceding subsurface ocean heat content levels, convection over the western tropical Pacific, and concurrent atmospheric circulation. Specifically, preceding subsurface ocean cooling combined with low‐level easterly wind anomalies led to the growth of La Niña after the coastal El Niño in 2017, while strong preceding subsurface ocean warming led to the growth of El Niño after the coastal El Niño in 2023. These differences in the evolution of tropical Pacific Ocean conditions after a coastal El Niño were associated with different levels of ENSO predictability. Key Points: The coastal El Niño in 2017 was followed by a La Niña, while the coastal El Niño in 2023 evolved into a basin‐scale El NiñoSubsurface ocean heat content levels, western Pacific convection, and off‐equatorial circulation differences affect El Niño‐Southern Oscillation (ENSO) evolutionDivergent evolution of conditions in the tropical Pacific after a coastal El Niño is associated with differences in ENSO predictability [ABSTRACT FROM AUTHOR]

Biweekly sea surface temperature (SST) variability significantly contributes to over 50% of the intraseasonal variability in the eastern equatorial Pacific (EEP) and Atlantic (EEA). Our study investigates this biweekly variability, employing a blend of in–situ and reanalysis data sets. The research identifies biweekly signals in SST, meridional wind, and ocean currents, notably in September–November in EEP and June–August in EEA. Biweekly southerly (northerly) winds drive instantaneous northward (southward) ocean currents in EEP, but with a 1–2‐day phase delay in EEA. Consequently, these currents lead to SST anomalies with a 3–4‐day lag in both EEP and EEA due to the presence of the cold tongue. The study reveals the origin of biweekly wind fluctuations in the western Pacific for EEP and the subpolar Pacific for EEA, connected by atmospheric Rossby waves validated through a linearized non‐divergent barotropic model. This research affirms the influence of subtropical and subpolar atmospheric forcing on equatorial SST. Plain Language Summary: Our research focuses on understanding the regular changes in sea surface temperature (SST) occurring every 2 weeks, which significantly contribute to the seasonal variations in the eastern equatorial Pacific (EEP) and Atlantic (EEA). By analyzing a mix of direct and reconstructed data, we uncover the distinct patterns of these biweekly changes in SST, winds, and ocean currents. Our investigation shows that the movements of the ocean currents are closely linked to the shifts in wind direction, affecting the temperature of the ocean waters. Notably, we observe a delay in the relationship between wind and SST in both EEP and EEA. Through our analysis, we establish that the origins of these biweekly wind patterns can be traced to specific regions in the Pacific. Moreover, we identify the role of atmospheric Rossby waves in connecting these wind patterns to their source regions, which helps us understand how changes in atmospheric conditions in different parts of the ocean can impact the equatorial SST. Key Points: Over 50% of intraseasonal SST variability in the eastern equatorial Pacific and Atlantic is attributed to biweekly fluctuationsThe atmospheric winds play a crucial role in driving the biweekly SST variabilityBiweekly winds in the eastern equatorial Pacific and Atlantic stem from the subtropical and subpolar regions, respectively [ABSTRACT FROM AUTHOR]

Stable water isotopes in inland Antarctic ice cores are powerful paleoclimate proxies; however, their relationship with dynamical atmospheric circulations remains controversial. Using a water isotope climate model (MIROC5‐iso), we assessed the influence of the Last Glacial Maximum (LGM; ∼21,000 years ago) sea surface temperatures (SST) and sea ice (SIC) on Antarctic precipitation isotopes (δ18Op) through atmospheric circulation. The results revealed that the synoptic circulation mostly maintained southward moisture transport, reaching inland Antarctica. The steepened meridional SST gradient in the mid‐latitudes increased δ18Op in inland Antarctica with the enhanced baroclinic instability and synoptic moisture transport. In contrast, expanded SIC distribution decreased δ18Op over Antarctica by enhanced preferential removal of heavy isotopes during vapor transport due to the increased transport distance and enhanced surface cooling. These findings propose to use Antarctic ice cores to describe the southern hemisphere atmospheric circulation, represented by the westerly jets, during the LGM and other past climates. Plain Language Summary: Stable water isotopes are widely used to reconstruct past variations of Earth's climate, such as the temperature in Antarctica during the Last Glacial Maximum (LGM) ∼21,000 years ago. This is an essential period for the climate community, given the order of magnitude of the temperature change between the LGM and today, which is similar to that of today's warming. However, the relationship between stable water isotopes and temperature is still subject to debate because of the influence of other climatic factors. Using an isotope‐enabled climate model, we found that the isotopic composition of Antarctic precipitation was not simply associated with the high and low average Antarctic temperature, but was substantially influenced by changes in dynamical atmospheric circulation related to sea surface temperature and sea ice expansion. We also suggest that representation of the past atmospheric circulations, such as westerly jets, can be constrained using water isotopic signals in Antarctic ice cores. Key Points: Synoptic circulations sustained the moisture transport toward inland AntarcticaMeridional sea surface temperature gradient enhanced moisture and heavy isotope precipitations on Antarctica, unlike sea ice expansionAntarctic ice core isotopes may refine southern hemisphere atmospheric circulations during the last glacial maximum [ABSTRACT FROM AUTHOR]

Sea surface temperature (SST) variability on decadal timescales has been associated with global and regional climate variability and impacts. The mechanisms that drive decadal SST variability, however, remain highly uncertain. Many previous studies have examined the role of atmospheric variability in driving decadal SST variations. Here we assess the strength of oceanic forcing in driving decadal SST variability in observations and state‐of‐the‐art climate models by analyzing the relationship between surface heat flux and SST. We find a largely similar pattern of decadal oceanic forcing across all ocean basins, characterized by oceanic forcing about twice the strength of the atmospheric forcing in the mid‐ and high latitude regions, but comparable or weaker than the atmospheric forcing in the subtropics. The decadal oceanic forcing is hypothesized to be associated with the wind‐driven oceanic circulation, which is common across all ocean basins. Plain Language Summary: Decadal variabilities in SST create large climate responses, ranging from heat waves to droughts to enhanced hurricanes. However, there has been considerable uncertainty over whether decadal SST variations are driven primarily by atmospheric forcing or ocean forcing related to ocean circulation. Using a newly developed theoretical framework, we provide the first quantitative estimation of decadal oceanic forcing across the global ocean in observations and state‐of‐the‐art climate model. Our estimation shows that decadal ocean forcing is stronger than the atmospheric forcing by about 2–3 times in the mid‐ and high latitude, but comparable or even weaker than atmospheric forcing in the subtropics. Key Points: In the mid‐ and high latitude, decadal oceanic forcing is stronger than atmospheric forcing by about 2–3 times across world ocean basinsIn the subtropics, decadal oceanic forcing is comparable to or even weaker than atmospheric forcingDecadal oceanic forcing is likely contributed predominantly by the wind‐driven oceanic circulation [ABSTRACT FROM AUTHOR]

Humid heatwaves, characterized by high temperature and humidity combinations, challenge tropical societies. Extreme wet‐bulb temperatures (TW) over tropical land are coupled to the warmest sea surface temperatures by atmospheric convection and wave dynamics. Here, we harness this coupling for seasonal forecasts of the annual maximum of daily maximum TW (TWmax). We develop a multiple linear regression model that explains 80% of variance in tropical mean TWmax and significant regional TWmax variances. The model considers warming trends and El Niño and Southern Oscillation indices. Looking ahead, the strong‐to‐very‐strong El Niño at the end of 2023, with an Oceanic Niño Index of ∼2.0, suggests a 2024 tropical land mean TWmax of 26.2°C (25.9–26.4°C), and a 68% chance (24%–94%) of breaking existing records. This method also predicts regional TWmax in specific areas. Plain Language Summary: The heat and humidity in the tropics can be particularly challenging for people to stay comfortable and healthy. This combination of heat and moisture is described using a measure called the wet‐bulb temperature (TW). We found that these extremely humid and hot conditions on land can be predicted about 5 months in advance using a physics‐based statistical model. The forecast is possible because the peak of El Niño comes before the peak in the warmest sea surface temperatures, which affects the maximum TW on land. This prediction can help tropical societies to better prepare for extreme heat. Key Points: Tropical wet‐bulb temperatures (TW) peak around 5 months after El Niño wintersA multiple linear regression model considering the El Niño‐Southern Oscillation index and the long‐term warming trend effectively explains TWmax variabilityOur model quantifies the likelihood of strong El Niño and human‐induced warming pushing TWmax to record‐breaking levels [ABSTRACT FROM AUTHOR]

Changes in the volume transport of Atlantic water into the Arctic Ocean can affect the heat and mass balance in the central Arctic Ocean. To understand the impacts of Arctic storms on the inflow through Fram Strait, we implemented the NEMO ocean model for the Arctic Ocean, to simulate the decadal variations of the water volume transport through Fram Strait. The simulations suggest that the water inflow tends to be weaker in the decades of the 1960 and 2010s but stronger in the 1980s. The decadal variation is associated with decadal variability of the storm density in the Greenland Sea. When there is an increased storm density near Fram Strait, the southerly wind anomalies dominate the Atlantic water pathway. As a response, there is an increased Atlantic inflow through Fram Strait. Plain Language Summary: On decadal scales, Arctic storms near Fram Strait are highly correlated with the water volume transport into the Arctic Ocean through Fram Strait. When there are more storms near Fram Strait, the transport tends to increase. In addition, the heat flux associated with the water volume transport reflects the impacts of both the linear trend in ocean temperature and the decadal variation of water volume transport. Key Points: On a decadal scale, the storms in the Greenland Sea can affect the volume transport of Atlantic water inflow through Fram StraitAssociated heat flux reflects the impacts of both the linear trend in ocean temperature and the decadal variation of water volume transport [ABSTRACT FROM AUTHOR]

A severe hailstorm that occurred in Spain on 30 August 2022, caused material and human damage, including one fatality due to giant hailstones up to 12 cm in diameter. By applying a pseudo‐global warming approach, here we evaluate how a simultaneous marine heatwave (and anthropogenic climate change) affected a unique environment conductive to such giant hailstones. The main results show that the supercell development was influenced by an unprecedented amount of convective available energy, with significant contributions from thermodynamic factors. Numerical simulations where the marine heatwave is not present show a notable reduction in the hail‐favorable environments, related mainly to modifications in thermodynamic environment. Our simulations also indicate that the environment in a preindustrial‐like climate would be less favorable for convective hazards and thus the hailstorm event would likely not have been as severe as the observed one, being possible to perform a novel attribution of such kind. Plain Language Summary: In August 2022, northeastern Spain faced a damaging hailstorm with hailstones up to 12 cm, causing significant harm and one fatality. This study examined how hail‐favorable environments were modified by a marine heatwave and human‐induced climate change. Numerical simulations show that the storm's intensity was influenced by abundant atmospheric energy and moisture from the warm sea, partly influenced by human‐induced warming. When the warm sea factor was excluded from the simulations, hailstones were smaller. These findings emphasize the role of human‐induced climate change and warm sea surface temperature events in intensifying extreme and high‐impact weather events like hailstorms. Key Points: Unprecedented hailstones in Spain (up to 12 cm) caused widespread damage and one fatalityA record‐breaking marine heatwave enhanced the strong hail‐favorable environmentNovel demonstration of an extreme hailstorm event attribution to anthropogenic warming [ABSTRACT FROM AUTHOR]

Precipitation projections in transient climate change scenarios have been extensively studied over multiple climate model generations. Although these simulations have also been used to make projections at specific Global Warming Levels (GWLs), dedicated simulations are more appropriate to study changes in a stabilizing climate. Here, we analyze precipitation projections in six multi‐century experiments with fixed atmospheric concentrations of greenhouse gases, conducted with the UK Earth System Model and which span a range of GWLs between 1.5 and 5°C of warming. Regions are identified where the sign of precipitation trends in high‐emission transient projections is reversed in the stabilization experiments. For example, stabilization reverses a summertime precipitation decline across Europe. This precipitation recovery occurs concurrently with changes in the pattern of Atlantic sea surface temperature trends due to a slow recovery of the Atlantic Meridional Overturning Circulation in the stabilization experiments, along with changes in humidity and atmospheric circulation. Plain Language Summary: Climate model projections consistently predict that summer precipitation over Europe is expected to decline in the future as global temperatures rise under continued global warming. In our study, we use new climate model simulations that simulate a world where atmospheric concentrations of greenhouse gases are no longer increasing and the rise in global temperatures has slowed down. We show that the summer rainfall decline across Europe can, to some extent, be reversed if global temperatures were to stabilize. This has important implications for adaptation and planning decisions, particularly in so‐called climate change "hot‐spots" such as the Mediterranean. Key Points: Climate stabilization experiments show significant differences in projected precipitation compared to high‐emission transient scenariosNorthern European and Mediterranean projected summer drying is partially reversedEuropean summer precipitation changes are consistent with the atmospheric response to Atlantic SST changes [ABSTRACT FROM AUTHOR]

The difference in observed atmospheric anomalies over the Northern Hemisphere winter between 2021–22 and 2020–21 La Niña years indicated a tripole pattern consisting of a Japan cyclone, a Bering Sea anticyclone, and a cyclone over the North American continent. This feature, however, was not replicated in the North American Multi‐Model Ensemble (NMME) forecasts. A set of model sensitivity experiments was performed to better understand the cause of this discrepancy. The results revealed the possible role of the influence of sea surface temperature (SST) anomalies, particularly over the Indian Ocean, on the observed circulation differences that was further modulated by internal atmospheric variability. The failure in predicting circulation changes in NMME was next attributed to the errors in SST predictions over the Indian Ocean and highlights the need for improvements in SST forecasts over this region. Plain Language Summary: The tropical SST anomalies associated with the El Niño‐Southern Oscillation (ENSO) are known to influence the global atmospheric circulation and are the major source of skill in U.S. seasonal predictions. As the cold phase of ENSO, La Niña features below‐normal SST anomalies and suppressed convection over the equatorial central and eastern Pacific. Such a tropical heating distribution favors the formation of the atmospheric circulation pattern that has a roughly opposite effect on U.S. surface climate compared to El Niño, the warm phase of ENSO, although the effect is not strictly symmetric. For the recent two La Niña boreal winters of 2020–21 and 2021–22, the observed circulation patterns differed, but dynamical seasonal prediction failed to replicate this feature. Understanding the cause for the discrepancy of circulation changes between prediction and observations is of fundamental importance for the improvement of seasonal forecasts. Toward this, we designed numerical experiments that are forced with observed and predicted SST anomalies over different ocean basins. The results show that it is the errors in SST prediction over the Indian Ocean that contributed to the failure in the prediction of circulation changes, highlighting the importance of skillful prediction of SST over this region. Key Points: The difference in observed atmospheric anomalies for 2022 versus 2021 La Niña boreal winters featured a Northern Hemisphere tripole patternIndian Ocean SST contributed to the formation of observed tripole pattern, with internal atmospheric variability modulating its magnitudeErrors in SST predictions over the Indian Ocean led to the failure in predictions of the circulation changes in NMME forecasts [ABSTRACT FROM AUTHOR]

Current knowledge suggests a drought Indian monsoon (perhaps a severe one) when the El Nino Southern Oscillation and Pacific Decadal Oscillation each exhibit positive phases (a joint positive phase). For the monsoons, which are exceptions in this regard, we found northeast India often gets excess pre‐monsoon rainfall. Further investigation reveals that this excess pre‐monsoon rainfall is produced by the interaction of the large‐scale circulation associated with the joint phase with the mountains in northeast India. We posit that a warmer troposphere, a consequence of excess rainfall over northeast India, drives a stronger monsoon circulation and enhances monsoon rainfall over central India. Hence, we argue that pre‐monsoon rainfall over northeast India can be used for seasonal monsoon rainfall prediction over central India. Most importantly, its predictive value is at its peak when the Pacific Ocean exhibits a joint positive phase and the threat of extreme drought monsoon looms over India. Plain Language Summary: Monsoon brings rain over India. But some years are droughts. These drought monsoon years are historically associated with warmer sea surface temperatures (SSTs) in the eastern Pacific and cooler SST in the northern Pacific. This motivated scientists to predict drought monsoons when we observe a warm eastern and cold northern Pacific Ocean. However, in some years, the monsoon is not drought despite the SST anomalies in the Pacific suggesting so. We find that, in such years, rainfall over northeastern India during pre‐monsoon months is often excessive. So we argue that when the Pacific Ocean state suggests a drought monsoon over India (central region) but if pre‐monsoon rainfall over northeastern India is excessive, then we can rely less on the drought signal of the Pacific Ocean. Key Points: Pre‐monsoon rainfall over northeastern India is a potential indicator of false alarms of monsoon drought over central Indian regionAssociation between northeastern India pre‐monsoon rainfall and monsoon rainfall over central India oscillates multidecadallySea surface temperature anomalies in the Pacific are a key driver of pre‐monsoon rainfall over the northeastern India [ABSTRACT FROM AUTHOR]

The ocean regulates the Earth's climate by transporting heat from the equator to the poles. Here, we use satellite‐based sea surface observations of air‐sea heat fluxes and eddy detection to investigate the mesoscale heat transport. "Mesoscale" refers to both the Eulerian perspective as the spatio‐temporal scales of ∼100 km and ∼1 month, as well as the Lagrangian aspect as isolated vortices identified from the dynamic topography. Paradoxically, there are a considerable number of mesoscale eddies inconsistent between their surface thermal and dynamic signals, that is, cold‐core anticyclones and warm‐core cyclones are globally prevalent. On account of such inconsistency, we show that the mesoscale meridional heat transport carried by geostrophic components is 10 times larger than (and opposite in direction to) that of the wind‐driven Ekman components. An offset between SSH‐SST coherent and incoherent eddies in the Ekman heat transport is apparent, whereas the geostrophic heat transport is contained within coherent eddies. Plain Language Summary: Rotating water masses in the ocean, termed as mesoscale eddies, are dynamically important features because they can transport nutrients and displace heat in the Earth's climate system. In the same manner as the atmospheric weather systems that are associated with high or low pressures, mesoscale eddies are accompanied by sea level anomalies and therefore can be observed by satellite images. Conventionally, anticyclonic eddies detected as clockwise vortices in the Northern Hemisphere display warm temperature anomalies at the center. However, recent studies have found that the sea surface temperature signal of an eddy might be uncertain and even contradictory to their dynamical circulation patterns. In this study, we combine sea surface observations of temperature and velocity fields to determine the patterns of global ocean heat transport associated with mesoscale eddies. Key Points: The geostrophic component of meridional heat transport (MHT) at the mesoscale is 10 times larger than the Ekman componentSSH‐SST coherent eddies dominate the spatial patterns of MHT at the mesoscaleThough incomparable in magnitude with the large scale MHT, mesoscale eddies can still transport 30 TW of heat near sea surface [ABSTRACT FROM AUTHOR]

Strong positive Indian Ocean Dipole (pIOD) events like those in 1997 and 2019 caused significant flooding in East Africa. While future projections indicate an increase in pIOD events, limited historical data hinders a comprehensive understanding of these extremes, particularly for unprecedented events. To overcome this we utilize a large ensemble of seasonal reforecast simulations, which show that regional rainfall continues to increase with pIOD magnitude, with no apparent limit. In particular we find that extreme rain days are highly sensitive to the pIOD index and their seasonal frequency increases super‐linearly with higher pIOD magnitudes. It is vital that socio‐economic systems and infrastructure are able to handle not only the increasing frequency of events like 1997 and 2019 but also unprecedented seasons of extreme rainfall driven by as‐yet‐unseen pIOD events. Future studies should prioritize understanding the hydrological implications and population exposure to these unprecedented extremes in East Africa. Plain Language Summary: The Indian Ocean Dipole is a pattern of climate variability in the Indian Ocean, characterized by opposite‐signed sea surface temperature differences from normal in the west and east. During positive events (pIOD), the western Indian Ocean is warmer than usual, which disrupts the normal circulation of the atmosphere. When pIOD is strong, extreme rainfall and flooding are common in East Africa. This happened in 1997 and 2019. According to future predictions, the frequency of extreme pIOD events will increase. However, our understanding of these events is limited as there is not a large enough sample of past events in the historical data to study. To address this, we evaluate a large collection of climate model simulations called seasonal reforecasts. The results show no evidence of an upper limit to the impact of pIOD on regional rainfall. The frequency of rain days increases during pIOD, whilst extremely heavy rain days increase even more. This means that more frequent extreme pIOD seasons will likely bring more heavy rainfall impacts. It also means that if pIOD reaches a high magnitude which has not yet been recorded, the rainfall impacts are likely to be even larger than those seen in 1997 or 2019. Key Points: Unprecedented strong positive Indian Ocean Dipole (IOD) events are likely to bring extreme rainfall to East AfricaThe extreme component of the seasonal distribution of rain days is particularly sensitive to the magnitude of the IODThe impact of larger IOD events on extreme rainfall frequency increases non‐linearly with the IOD magnitude [ABSTRACT FROM AUTHOR]

Using observations and Atlantic forced coupled model simulations, we show evidence for an asymmetry in the link between beginning of year tropical Atlantic sea surface temperature anomalies (SSTAs) and end of the year El Niño‐Southern Oscillation events. We find a greater tendency for warm Atlantic SSTAs to lead to a La Niña than for cold anomalies to lead to El Niño. The model experiments showed that the Atlantic had a greater chance to force the tropical Pacific if the Pacific was initially in a neutral state. In the model, a warm Atlantic from March–May was able to produce an atmospheric response leading to easterly wind anomalies in the western Pacific. This in turn induces a subsurface oceanic response, leading to La Niña at the end of the year. The atmospheric response does not occur for a cold Atlantic, leading to no impacts in the Pacific. Plain Language Summary: It has been found that the tropical Atlantic can have an impact on an El Niño or La Niña events that form in the tropical Pacific at the end of the year. We show using observations and targeted model experiments that a warmer than normal Atlantic from March‐May can lead to a La Niña, but a colder than normal Atlantic does not lead to an El Niño. The model shows a strong atmospheric response to warm Atlantic surface temperature, leading to wind changes in the Pacific that aid La Niña formation. This strong atmospheric response does not occur for cold Atlantic temperatures leading to no changes in the Pacific. The model also shows that the Atlantic has a greater chance of impacting the Pacific at the end of the year if the Pacific is already in near average conditions at the beginning of the year. These results may improve forecasts of La Niña events and may help in understanding past changes in the Atlantic‐Pacific relationship. Key Points: Observed tropical Atlantic forced pacemaker experiments produce La Niña events, but not El Niño events, in unison with observationsA warm Atlantic had a greater chance of leading to a La Niña event if the tropical Pacific was initially in neutral conditionsThere was a tropical‐wide response to a warm Atlantic in the model, affecting western Pacific wind. This was not seen for a cold Atlantic [ABSTRACT FROM AUTHOR]

ENSO's atmospheric teleconnections drive anomalous North Pacific sea surface temperatures through changes in surface heat fluxes ("the atmospheric bridge"). Previous research focusing on the bridge as a seasonal phenomenon did not consider how ENSO‐related changes in synoptic variability might also impact surface turbulent heat fluxes (STHF). In this study, we find that while well over half of ENSO's impact on STHF occurs on low‐frequency (>8 days) time scales, up to 20% of its impact arises on high‐frequency (<8 days) time scales, through changes in the covariance between surface wind speed and air‐sea enthalpy difference that typically warms the ocean south of the storm track. During El Niño, the North Pacific storm track and its attendant sea surface warming shift southward, reducing warming of the central North Pacific ocean and thereby enhancing the bridge signal there. Additionally, changes in the bulk formula coefficients between ENSO phases drive STHF differences (5%–10%). Plain Language Summary: The El Niño‐Southern Oscillation (ENSO) has global impacts through teleconnections, which can influence the underlying ocean via the "atmospheric bridge." The atmospheric bridge results in upward surface heat flux and colder sea surface temperature (SST) over the central North Pacific and downward surface heat flux and warmer SST along the coast of North America during El Niño winters. While previous research has studied the influence of longer timescale features on this bridge‐related surface heat flux pattern, the corresponding impact of shorter timescale variability remains unexplored. We find that while longer timescales (>8 days) dominate, shorter timescale influence on the fluxes is non‐negligible. Shorter timescale variability warms the ocean south of the track of North Pacific storms. This warming contribution shifts with the storm location between the two ENSO phases. While the resulting difference between ENSO phases is small, it is mostly aligned with the total surface turbulent heat flux (STHF) difference between El Niño and La Niña. Also, the bulk formula coefficients used to compute the fluxes vary, leading to 5%–10% of the STHF difference between ENSO phases. In summary, the contribution of shorter timescale variability and coefficient changes to the North Pacific bridge‐related STHF is small but non‐negligible. Key Points: While seasonal variability dominates ENSO‐related surface turbulent heat fluxes over the North Pacific, synoptic effects are non‐negligibleENSO‐related storm track shift affects the high‐frequency contribution to the turbulent heat fluxesDifferences in the bulk formula coefficient between two ENSO phases have a small but non‐negligible influence on the surface heat fluxes [ABSTRACT FROM AUTHOR]

Air‐sea exchanges across oceanic fronts are critical in powering cloud formation, precipitation, and atmospheric storms. Oceanic submesoscale fronts of scales 1–10 km are characterized by strong sea surface temperature (SST) gradients. However, it remains elusive how submesoscale fronts affect the overlying atmosphere due to a lack of high‐resolution observations or models. Based on rare high‐resolution in situ observations in the Kuroshio Extension region, we quantify the air‐sea exchanges across an oceanic submesoscale front. The cross‐front SST and turbulent heat flux gradients reaches 2.4°C/km and 47 W/m2/km, respectively, far stronger than that typically found in mesoscale‐resolving products. The stronger SST gradient drives substantially stronger air‐sea fluxes and vertical mixing than mesoscale fronts, enhancing cloud formations. The intense air‐sea exchanges across submesoscale fronts are confirmed in idealized model simulations, but not resolved in mesoscale‐resolving climate models. Our finding provides essential knowledge for improving simulations of cloud formation, precipitation, and storms in climate models. Plain Language Summary: Oceanic fronts, characterized by large sea surface temperature (SST) gradients, are ubiquitous in the global ocean. Through intense heat and moisture release, these oceanic fronts induce large horizontal gradient of sea level pressure or increasing vertical mixing intensity in the lower atmosphere, are critical in powering cloud formation, precipitation, and atmospheric storms, but are sensitive to SST gradients. Oceanic submesoscale fronts of spatial scales 1–10 km are characterized by strong SST gradients. However, our knowledge of how the submesoscale fronts affect the overlying atmosphere is by and large void, due to a lack of high‐resolution observations or models. Here, based on high‐resolution in situ observations and model simulations, we show that submesoscale fronts drive much stronger air‐sea exchanges and vertical mixing as compared to mesoscale fronts, with significant implications for marine atmosphere boundary layer changes and cloud formations. Limited by the coarse resolution, the intense air‐sea exchanges across submesoscale fronts are not resolved in mesoscale‐resolving climate models. These results highlight the importance of submesoscale air‐sea interactions and call for a proper representation of submesoscale air‐sea exchanges in the next generation of climate models. Key Points: Observations show strong gradient in sea surface temperature and turbulent heat flux across a submesoscale oceanic frontSubmesoscale fronts drive substantially stronger air‐sea fluxes and vertical mixing than mesoscale frontsThe intense air‐sea exchanges across submesoscale fronts are not resolved in mesoscale‐resolving climate models [ABSTRACT FROM AUTHOR]

The surface air temperature (SAT) over the Sahara Desert has increased at a much faster rate than average tropical land in recent decades. This study examines the relative roles of anthropogenic greenhouse gas (GHG) forcing and sea surface temperature (SST) change in the observed Saharan temperature increase during boreal warm season from 1979 to 2020 using atmospheric general circulation model simulations. It is found that the SST forcing dominates the observed Saharan warming. Further analysis shows that the warming ocean forces the Saharan SAT increase by moving more energy to the Sahara Desert, while the water vapor feedback plays a secondary role. The reason for the stronger Saharan warming than the average tropical land given the same SST forcing is also explored. We found that the largest contributor to the warming contrast is the lapse‐rate feedback, which is attributable to the difference in the vertical warming profile. Plain Language Summary: Sahara Desert has experienced a stronger warming than the tropical land on average since 1979. Debates continue on whether the amplified Saharan warming is a response to the remote sea surface temperature (SST) change or the radiative forcing brought about by the increasing anthropogenic greenhouse gas. In this study, we quantify the relative contributions of these two forcing agents to the observed Saharan temperature increase. It is found that the observed Saharan warming is largely controlled by the remote SST forcing. As the ocean warms up, it acts to transport more energy to the Sahara Desert and warms the surface. The warming contrast between the Sahara Desert and the average tropical land is found to be dominated by the lapse‐rate feedback (LR), which favors the Saharan warming but suppresses the average tropical land warming. The difference in LR is a result of the different vertical warming structure over the Sahara Desert and average tropical land. Key Points: The observed Saharan warming since 1979 is largely a result of the sea surface temperature (SST) change rather than direct anthropogenic greenhouse gas radiative forcingThe dominant factor driving Saharan warming is the anomalous atmospheric energy transport from the warming oceanLapse rate and water vapor feedbacks both amplify Saharan warming relative to the average tropical land in response to the SST forcing [ABSTRACT FROM AUTHOR]

Global warming and climate change have increased the frequency and intensity of floods and droughts, limiting economic development and threatening human survival. Therefore, accurate global forecasts well in advance of precipitation are essential to facilitate timely adaptation. Current seasonal forecasts are based mainly on numerical models, but raw forecasts suffer from systematic bias and under/overdispersion problems and cannot be directly used in applications. In addition, bias correction methods for global forecasts need to be further developed. Based on a fusion of ResNet34 and Unet, called Res34‐Unet, deep learning post‐processing is proposed to correct global precipitation forecasts of the North American Multi‐Model Ensemble (NMME). Compared with raw global NMME predictions, post‐processed precipitation predictions can be improved by up to 45%, which is significant at different latitudes. Feature importance analysis shows that precipitation itself, meridional wind, and sea surface temperature are key factors. Plain Language Summary: Under the influence of global warming, extreme events, especially floods and droughts, are becoming more frequent, severely limiting social and economic development and greatly affecting people's lives. Therefore, accurate global forecasts are crucial to help people adaptively respond as soon as possible. Currently, seasonal forecasts are based mainly on numerical models. The North American Multi‐Model Ensemble (NMME) is one of the most advanced multi‐model ensemble systems for intra‐seasonal to interannual global prediction. However, due to deficiencies in numerical weather prediction models and inaccurate initial conditions, raw model predictions still have a large bias compared to observations. Therefore, accurate and efficient post‐processing algorithms are essential. Traditional post‐processing algorithms have some disadvantages such as the assumption of linearity, and spatial and temporal inconsistency. In addition, most post‐processing work has a regional focus, and more research focusing on global post‐processing prediction is needed to reduce global losses from extreme events. With the rapid development of machine learning, artificial intelligence is an effective tool to improve post‐processing. The fusion of ResNet34 and Unet, called Res34‐Unet, is proposed to post‐process global NMME rainfall predictions. Compared with raw NMME predictions, post‐processed predictions can be improved by up to 45%, which is significant at different latitudes. Key Points: Accurate global seasonal precipitation prediction is essential, but the bias of raw model predictions is largeRes34‐Unet post‐processing provides accurate seasonal precipitation prediction and outperforms Unet post‐processingRes34‐Unet post‐processing can improve predictions by up to 45%, which is significant at different latitudes [ABSTRACT FROM AUTHOR]

Marine heatwaves (MHWs) are extremely warm ocean temperature events that significantly affect marine environments, but their effects on the coastal carbonate system are still uncertain. In this study, we systematically quantify MHWs' impacts on air‐sea carbon dioxide (CO2) flux anomalies (FCO2′) in the Mid‐Atlantic Bight (MAB) and South Atlantic Bight (SAB) from 1992 to 2020. During the longest MHW in both regions, oceanic CO2 uptake capabilities substantially decreased, primarily due to significant increases in the seawater partial pressure of CO2 (pCO2sea). For all cases, MHWs played a more significant role in driving pCO2sea changes in the MAB than the SAB, where non‐thermal drivers dominated pCO2sea variability. In the MAB, weakened wind speeds related to wintertime atmospheric perturbations increase ocean temperatures and pCO2sea, further reducing CO2 uptake during winter MHWs. This work is the first to connect extreme temperatures to coastal air‐sea CO2 fluxes. The reduction in CO2 absorption noted during MHWs in this study has important implications for coastal regions to act as continued sinks for excess CO2 emissions in the atmosphere. Plain Language Summary: The transfer of carbon dioxide (CO2) between the atmosphere and ocean is sensitive to sea surface temperature (SST) changes because warmer SSTs increase the sea surface partial pressure of CO2 and reduce the ocean's ability to absorb CO2 from the atmosphere. It is, therefore, conceivable that marine heatwaves (MHWs), which are extremely warm ocean temperature events, could modify how carbon moves between the ocean and the atmosphere. This study provides the first attempt to evaluate the impacts of MHWs on the air‐sea CO2 flux (FCO2) anomalies along the US East Coast, encompassing the Mid‐Atlantic Bight (MAB) and South Atlantic Bight (SAB) during 1992–2020. Both regions experienced reduced CO2 absorption in response to the longest MHWs in each region. These extreme temperatures had a larger impact on CO2 absorption in the MAB compared to the SAB, where non‐temperature factors were more influential. The coastal ocean plays an important role in helping to mitigate human‐induced climate change by absorbing excess CO2 from the atmosphere. As such, the demonstrated reduced absorption of the ocean associated with MHWs in this study, which might also apply to other coastal locations, has vital implications for the efficiency of the ocean in offsetting global warming impacts. Key Points: Marine heatwaves (MHWs) primarily generated positive sea surface pCO2 (pCO2sea) anomalies in the Mid‐Atlantic Bight (MAB) and South Atlantic Bight (SAB) but had a larger impact on air‐sea CO2 flux anomalies in the MABReduced wind speeds amplified MHW contributions during CO2 sink months and counteracted them during CO2 source monthsIn the MAB, wintertime atmospheric perturbations related to zonal shifts in the jet stream produce slower wind speeds which aid in generating air‐sea heat flux type MHW events that ultimately reduce oceanic CO2 uptake [ABSTRACT FROM AUTHOR]