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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 Reef Cluster analysis is used to show the types of MJO propagation patterns likely to occur during El Niño and La Niña periods Ocean temperature variability is discussed with El Niño/La Niña phases as the background states and the MJO as a sub‐seasonal modulator

The Pacific Walker circulation and the closely connected El Niño/Southern Oscillation influence the climate and weather of the tropical Indo-Pacific region. They specifically exert a strong control on the regional occurrence of weather extremes, such as heatwaves, heavy precipitation and prolonged dry spells, which are becoming increasingly frequent and severe. However, climate models struggle to accurately simulate large-scale circulation changes in the tropics and thus their consequences for regional weather and future climate. Here we use high-resolution ERA5 reanalysis data from 1940 to 2022 to study the occurrence trends of weather patterns in the tropical Indo-Pacific region. We find that new large-scale synoptic situations that were rarely present before the 1990s have emerged in the Indo-Pacific, while some others that were prominent have disappeared. Those new synoptic situations are associated with an unusual proportion of heatwaves and extreme precipitation in the region. These weather patterns are physically consistent with a trend towards a stronger Pacific Walker circulation, wetter and warmer conditions in Southeast Asia and drier conditions in the equatorial Pacific. These changes cannot be fully explained by El Niño/Southern Oscillation and other relevant modes of interannual variability, and other factors such as global warming, aerosol forcing, external forcing mechanisms and nonlinear mode interactions may be contributing. Emerging weather patterns over recent decades are exacerbating extreme precipitation and heatwaves in the tropical Indo-Pacific region, according to a computation of trends in reanalysis data.

The weak temperature gradient (WTG) approximation is extended to the basic equations on a rotating plane. The circulation is decomposed into a diabatic component that satisfies WTG balance exactly and a deviation from this balance. Scale analysis of the decomposed basic equations reveals a spectrum of motions, including unbalanced inertio-gravity waves and several systems that are in approximate WTG balance. The balanced systems include equatorial moisture modes with features reminiscent of the MJO, off-equatorial moisture modes that resemble tropical depression disturbances, “mixed systems” in which temperature and moisture play comparable roles in their thermodynamics, and moist quasigeostrophic motions. In the balanced systems the deviation from WTG balance is quasi nondivergent, in nonlinear balance, and evolves in accordance to the vorticity equation. The evolution of the strictly balanced WTG circulation is in turn described by the divergence equation. WTG balance restricts the flow to evolve in the horizontal plane by making the isobars impermeable to vorticity and divergence, even in the presence of diabatically driven vertical motions. The vorticity and divergence equations form a closed system of equations when the irrotational circulation is in WTG balance and the nondivergent circulation is in nonlinear balance. The resulting “WTG equations” may elucidate how interactions between diabatic processes and the horizontal circulation shape slowly evolving tropical motions.

Observational evidence of two extratropical pathways to forcing tropical convective disturbances is documented through a statistical analysis of satellite-derived OLR and ERA5 reanalysis. The forcing mechanism and the resulting disturbances are found to strongly depend on the structure of the background zonal wind. Although Rossby wave propagation is prohibited in easterlies, modeling studies have shown that extratropical forcing can still excite equatorial waves through resonance between the tropics and extratropics. Here this “remote” forcing pathway is investigated for the first time in the context of convectively coupled Kelvin waves over the tropical Pacific during northern summer. The extratropical forcing is manifested by eddy momentum flux convergence that arises when extratropical eddies propagate into the subtropics and encounter their critical line. This nonlinear forcing has similar wavenumbers and frequencies with Kelvin waves and excites them by projecting onto their meridional eigenstructure in zonal wind, as a form of resonance. This resonance is also evidenced by a momentum budget analysis, which reveals the nonlinear forcing term is essential for maintenance of the waves, while the remaining linear terms are essential for propagation. In contrast, the “local” pathway of extratropical forcing entails the presence of a westerly duct during northern winter that permits Rossby waves to propagate into the equatorial east Pacific, while precluding any sort of resonance with Kelvin waves due to Doppler shifting effects. The intruding disturbances primarily excite tropical “cloud plumes” through quasigeostrophic forcing, while maintaining their extratropical nature. This study demonstrates the multiple roles of the extratropics in forcing in tropical circulations and illuminates how tropical–extratropical interactions and extratropical basic states can provide be a source of predictability at the S2S time scale.

We develop an approach to correct biases in the atmospheric component of the Community Earth System Model using convolutional neural networks (CNNs) to create a corrective model parameterization for online bias reduction. By predicting systematic nudging increments derived from nudging toward the ERA5‐reanalysis, our method dynamically adjusts the model state, outperforming traditional corrections based on climatological increments alone. Our results show significant root mean squared error improvements across all state variables, with land precipitation biases reduced by 25%–35%, seasonally dependent. Notably, we observe an improvement to the Madden‐Julian Oscillation (MJO), where the CNN‐corrected model successfully propagates the MJO across the maritime continent, a challenge for many current climate models. This advancement underscores the potential of using CNNs for real‐time model correction, providing a robust framework for improving climate simulations. This advancement highlights the potential of CNNs for real‐time model correction, improving climate simulations and bridging observed and simulated dynamics. Plain Language Summary In this study, we created a new method to improve weather and climate predictions using advanced computer techniques. We used a type of artificial intelligence called convolutional neural networks to correct errors in a climate model called the Community Earth System Model. By using data from the ERA5 weather data set, our method makes real‐time adjustments to the model, making it much more accurate than traditional methods. Our approach significantly reduced errors in predicting weather conditions, especially rainfall over land, where errors were cut by 25%–35%, depending on the season. We also improved the model's ability to simulate important climate patterns like the North Atlantic Oscillation. One of our biggest successes was in accurately simulating the Madden‐Julian Oscillation, a major tropical weather pattern, allowing it to move across the maritime continent—an area where many models fail. This study shows that combining machine learning with traditional climate models can make predictions more accurate and reliable. Our new method helps bridge the gap between real‐world weather observations and computer simulations, offering a promising way to improve future weather and climate forecasts. Key Points Nudging increments are utilized as targets for a state‐dependent, spatially aware, corrective convolutional neural network in the Community Atmosphere Model Multi‐year, bias‐corrected climate simulations enhance the physical representation of low‐frequency modes of variability Multi‐year, bias‐corrected climate simulations improve the representation of the Madden‐Julian Oscillation and facilitate its propagation over the Maritime Continent

Interactions between large-scale waves and the Hadley cell are examined using a linear two-layer model on an f plane. A linear meridional moisture gradient determines the strength of the idealized Hadley cell. The trade winds are in thermal wind balance with a weak temperature gradient (WTG). The mean meridional moisture gradient is unstable to synoptic-scale (horizontal scale of ∼1000 km) moisture modes that are advected westward by the trade winds, reminiscent of oceanic tropical depression–like waves. Meridional moisture advection causes the moisture modes to grow from “moisture-vortex instability” (MVI), resulting in a poleward eddy moisture flux that flattens the zonal-mean meridional moisture gradient, thereby weakening the Hadley cell. The amplification of waves at the expense of the zonal-mean meridional moisture gradient implies a downscale latent energy cascade. The eddy moisture flux is opposed by a regeneration of the meridional moisture gradient by the Hadley cell. These Hadley cell–moisture mode interactions are reminiscent of quasigeostrophic interactions, except that wave activity is due to column moisture variance rather than potential vorticity variance. The interactions can result in predator–prey cycles in moisture mode activity and Hadley cell strength that are akin to ITCZ breakdown. It is proposed that moisture modes are the tropical analog to midlatitude baroclinic waves. MVI is analogous to baroclinic instability, stirring latent energy in the same way that dry baroclinic eddies stir sensible heat. These results indicate that moisture modes stabilize the Hadley cell and may be as important as the latter in global energy transport.

The causality of the link between Autumn Barents‐Kara (BK) sea ice and the winter North Atlantic Oscillation (NAO) is uncertain, given teleconnections stemming from the tropics may influence both the extra‐tropics and the Arctic. We explore the relationship between tropical rainfall and BK sea ice in autumn, by nudging the tropics to follow observed variability in otherwise free running ensemble simulations. Tropical forcing alone can skillfully reproduce a significant fraction of observed interannual NAO variability in late autumn. We also show that interannual variability in the NAO is strongly related to simulated BK sea ice. As a result, we are able to reproduce some of the observed link between tropical rainfall and autumn BK sea ice. However, only during the strong 1997 El Niño are clear tropical influences at high latitudes found. Large ensembles and strong tropical forcing are required to detect tropical forced variability in models at high latitudes. Plain Language Summary Regional variations in Arctic sea ice during autumn have been linked to large scale weather patterns over the Atlantic, which impact on European weather. Commonly, this can be attributed to the North Atlantic Oscillation (NAO). Whether the relationship with sea ice and the NAO is physical, or coincidental, is unclear, given that remote tropical weather can impact on both Arctic sea‐ice and the NAO. In this study, we explore how the tropics could impact sea ice in the Barents‐Kara (BK) seas during autumn, by constructing controlled experiments where we specify the state of the tropical atmosphere. We repeat this many times, to determine how much variability there is in this relationship. We find that there is a link between tropical weather and large‐scale weather patterns in the Atlantic, with a weak link found between tropical weather and BK sea‐ice. However, during years when tropical convection is particularly active in the east Pacific, we can see a much stronger impact on the Arctic during autumn. Our results indicate that the link between the tropics and Arctic may be too weak in models and is only detectable during years where the tropical variability is particularly strong. Key Points Tropical nudging experiments reproduce some of the observed interannual variability in autumn Barents‐Kara sea ice Tropical nudging reproduces a significant fraction of observed autumn North Atlantic Oscillation (NAO) variability, and the anticorrelation of NAO with sea ice Only during the strong El Niño of 1997 is the model able to reproduce the strong observed teleconnection from the tropics to sea ice

Mixed Rossby‐gravity (MRG) waves play a significant role in tropical variability. Their kinetic energy spectra exhibit maximal amplitudes at synoptic scales in the upper troposphere and at planetary scales in the upper stratosphere. The mechanism for different scale selection in the two regions has remained elusive. Here, we use a spherical barotropic model with the background zonal wind profiles derived from ERA5 reanalysis to show that the recently introduced MRG wave excitation mechanism −${-}$wave‐mean flow interactions produces MRG waves with the observed scale properties in the two regions. Simulations with idealized zonal jets show that the jet position determines the MRG scale selection: the closer the jet to the equator, the smaller the scale of the excited MRG waves. Therefore, midlatitude jets, such as found in the upper stratosphere, support the excitation of planetary‐scale MRG waves. Plain Language Summary Mixed Rossby‐gravity (MRG) waves, which are important for tropical weather and climate, obtain different spatial scales in two distinct atmospheric regions: synoptic scales in the upper troposphere and planetary scales in the upper stratosphere. So far, the mechanism responsible for this behavior is not identified. In this study, we propose interactions involving waves that originate from the tropics and zonal jets (i.e., wave‐mean flow interactions) as the mechanism behind the observed MRG wave scales. We provide evidence by conducting numerical simulations with an idealized model that resolves MRG waves with high accuracy. We identify MRG waves generated by wave‐mean flow interactions and show that their peak scale can be attributed to the position of the jet. The closer the jet to the equator, the smaller the scale of generated MRG waves. This not only offers an explanation for the observed spatial scales of the tropospheric and stratospheric MRG waves, but also points out the importance of the background flow to correctly represent MRG waves in weather and climate models. Key Points Mixed Rossby‐gravity waves in the upper stratosphere and troposphere have peak scales at zonal wavenumbers 1–3, and 6, respectively Observed peak scales are generated by wave‐mean flow interactions in numerical simulations with the observed zonal‐mean zonal wind profiles The peak MRG scale is associated with the jet position: the closer the jet to the equator, the smaller the scale of the excited waves

Anomalous tropical longwave cloud‐radiative heating of the atmosphere is generated when convective precipitation occurs, which plays an important role in the dynamics of tropical disturbances. Defining the observed cloud‐radiative feedback as the reduction of top‐of‐atmosphere longwave radiative cooling per unit precipitation, the feedback magnitudes are sensitive to the observed precipitation data set used when comparing two versions of Global Precipitation Climatology Project, version 1.3 (GPCPv1.3) and the newer version 3.2 (GPCPv3.2). GPCPv3.2 contains larger magnitudes and variance of daily precipitation, which yields a weaker cloud‐radiative feedback in tropical disturbances at all frequencies and zonal wavenumbers. Weaker cloud‐radiative feedbacks occur in GPCPv3.2 at shorter zonal lengths on intraseasonal timescales, which implies a preferential growth at planetary scales for the Madden‐Julian oscillation. Phase relationships between precipitation, radiative heating, and other thermodynamic variables in eastward‐propagating gravity waves also change with the updated GPCPv3.2. Plain Language Summary High‐altitude, widespread anvil clouds are generated when heavy convective precipitation occurs in the tropics. These clouds are not only a passive product produced by convection, but they also can subsequently enhance convection by trapping upward infrared radiative flux emitted by the Earth, effectively heating the atmosphere. This additional radiative heating effect can induce upward motion in the tropics, supporting the convective systems by transporting more humid air from below. However, the strength of this cloud‐radiative feedback is hard to estimate because global, continuous observations of surface precipitation are difficult to derive. In this study, the strength of the radiative feedback is calculated using the same product of observed radiative heating against two different observational precipitation products. A newer improved precipitation product yields much weaker radiative feedback strengths for all types of tropical weather systems. In addition, cloud‐radiative heating is found to substantially lag behind precipitation in certain fast, eastward‐propagating tropical rainfall systems in the newer precipitation product, unlike the older one. Why such a lag exists is unclear. The discrepancy of the estimation of cloud‐radiative feedback strengths and properties in the older versus the newer precipitation products indicates that our understanding of mechanisms supporting tropical disturbances is still incomplete. Key Points The updated Global Precipitation Climatology Project (GPCP) precipitation product has more frequent high rain rates, yielding a weaker longwave radiative feedback The updated radiative feedback supports less moistening of the Madden‐Julian oscillation, but imposes stronger planetary scale selection The phase relationship between precipitation and thermodynamic fields in eastward‐propagating tropical waves are sensitive to GPCP versions

The Madden–Julian Oscillation (MJO) is a dominant source of subseasonal atmospheric variability in the tropics and significantly impacts global weather and climate predictability. Changes in its activity and predictability due to human-induced global climate change have profound implications for future global weather prediction. Here we investigate changes in MJO predictability in reanalysis and climate model data and find that MJO predictability has increased over the past century. This increase can be attributed to anthropogenic warming and continues during the twenty-first century in projections. The increased predictability is accompanied by stronger MJO amplitude, more regular oscillation patterns and organized eastward propagation under global warming. Our results suggest that greenhouse warming will increase the predictability of the MJO, with far-reaching consequences for global weather prediction. The Madden–Julian Oscillation (MJO) is a key feature of tropical weather on a multi-weekly timescale. Here, the authors show that the MJO becomes more predictable with climate change, potentially allowing better subseasonal-to-seasonal forecasting.