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It is shown that a recently developed hybrid modeling approach that combines machine learning (ML) with an atmospheric global circulation model (AGCM) can serve as a basis for capturing atmospheric processes not captured by the AGCM. This power of the approach is illustrated by three examples from a decades‐long climate simulation experiment. The first example demonstrates that the hybrid model can produce sudden stratospheric warming, a dynamical process of nature not resolved by the low resolution AGCM component of the hybrid model. The second and third example show that introducing 6‐hr cumulative precipitation and sea surface temperature (SST) as ML‐based prognostic variables improves the precipitation climatology and leads to a realistic ENSO signal in the SST and atmospheric surface pressure. Plain Language Summary: This paper introduces and tests schemes for efficiently enabling significant expansion of the utility and scope of a recently introduced hybrid modeling technique that combines machine learning with an atmospheric global circulation model (AGCM). Simulation experiments are carried out with an implementation of the approach on a low resolution simplified AGCM. An examination of the simulated atmospheric circulation suggests that the hybrid model can capture dynamical process not captured by the AGCM. Moreover, the addition of precipitation and sea surface temperature (SST) as machine learning predicted physical quantities to the model improves the precipitation climatology and leads to a realistic El Niño‐La Niña signal in the SST and atmospheric surface pressure. Key Points: A hybrid system combining an atmospheric global circulation model (AGCM) with a machine‐learning component can capture processes not captured by the AGCMMachine learning provides a flexible framework to introduce additional prognostic variables into the hybrid modelThe prototype hybrid model tested in the paper is stable and has a realistic climate in decades‐long simulation experiments [ABSTRACT FROM AUTHOR]

The thermospheric neutral density response to the 7–9 September 2017 storms is investigated based on the Swarm satellite observations and the thermosphere‐ionosphere‐electrodynamic general circulation model (TIEGCM) simulation. The Swarm data depicted a prominent interhemispheric asymmetry (IHA) in the afternoon sector during the second storm, a feature that was yet explained. Driven by realistic high‐latitude electric potential and electron precipitation patterns, the TIEGCM is able to reproduce the observed storm‐time neutral density response. The TIEGCM simulation reveals that the differences in the traveling atmospheric disturbances (TADs) is largely responsible for the observed IHA in the neutral mass density response at low and middle latitudes, whereas the difference in mean molecular mass between the two hemispheres may contribute to the IHA in neutral density at higher latitudes. The IHAs in TADs and mean molecular mass are attributed to the IHA in Joule heating dissipation on the night and dawn sides. Plain Language Summary: During geomagnetic storms, thermospheric neutral density can increase drastically due to intense heat inputs. Enhanced neutral density increases the air drag on satellites which could lower their orbits and lead to faster atmosphere reentering of satellites. In addition, enhanced neutral mass density may cause larger uncertainties in orbit prediction which increases the risk of collisions with other space objects. Therefore, it is essential to improve the understanding of storm‐time neutral density variations to improve satellite operations. Recent satellite observations have revealed that thermospheric neutral mass density response can be interhemispherically asymmetric even under equinox conditions when the background density in the two hemispheres is comparable. This paper presents a case study of such an event based on data analysis and numerical simulations to investigate the physical mechanisms behind this intriguing phenomenon. The event took place on 7–9 September 2017 and the most prominent interhemispheric asymmetry of neutral density occurred in the afternoon sector. Our study found that the interhemispheric asymmetry during this event results from the differences in the generation, propagation and interaction of globally propagating atmospheric waves, namely traveling atmospheric disturbances, as well as the difference in mean molecular mass between the northern and southern hemispheres. Key Points: Thermosphere‐ionosphere‐electrodynamic general circulation model captures the observed interhemispheric asymmetry (IHA) in the neutral density response to the 7–9 September 2017 geomagnetic stormsThe IHA in the neutral density response results from the IHA in traveling atmospheric disturbances and mean molecular massThe observed IHA in the neutral density response is not caused by direct Joule heating dissipated at the same local time [ABSTRACT FROM AUTHOR]

The global ocean overturning circulation, critically dependent on the global density stratification, plays a central role in regulating climate evolution. While it is well known that the global stratification profile exhibits a strong dependence to Southern Ocean dynamics and in particular to wind and buoyancy forcing, we demonstrate here that the stratification is also acutely sensitive to the mesoscale eddy energy dissipation timescale. Within the context of a global ocean circulation model with an energy constrained mesoscale eddy parameterization, it is shown that modest variations in the eddy energy dissipation timescale lead to significant variations in key metrics relating to ocean circulation, namely the Antarctic Circumpolar Current transport, Atlantic Meridional Overturning Circulation strength, and global ocean heat content, over long timescales. The results highlight a need to constrain uncertainties associated with eddy energy dissipation for climate model projections over centennial timescales and also for paleoclimate simulations over millennial timescales. Plain Language Summary: The ocean is populated by "eddies", analogous to weather systems in the atmosphere, but occurring on much smaller scales of typically 10–100 km. Recent advances in our understanding of the circulation of the Southern Ocean, which connects all of the major ocean basins to the north, have revealed a crucial role for the energy balance of Southern Ocean eddies. In this paper, we show that the timescale over which energy is removed from Southern Ocean eddies has a dramatic impact on the following: (a) the strength of the Antarctic Circumpolar Current, the largest current in the global ocean; (b) the strength of the Atlantic meridional overturning circulation, responsible in part for the relatively mild climatic conditions over northwestern Europe; and (c) global ocean heat content, a key parameter in the global climate system. These results have significant implications for both past and future climates, and highlight the importance of combining observational, theoretical and modeling efforts to better understand and constrain the energy balance of ocean eddies. Key Points: Key metrics of global ocean circulation (Antarctic Circumpolar Current transport, Atlantic Meridional Overturning Circulation strength, and Ocean Heat Content anomaly) acutely sensitive to an eddy energy dissipation timescaleModest variations in the dissipation timescale has a comparable effect to significant variations in the Southern Ocean wind forcingConstraints on the dissipation timescale critical to longtime integrations of ocean climate models such as paleoclimate scenarios [ABSTRACT FROM AUTHOR]

Conventional long‐range weather prediction is an initial value problem that uses the current state of the atmosphere to produce ensemble forecasts. Purely stochastic predictions for long‐memory processes are "past value" problems that use historical data to provide conditional forecasts. Teleconnection patterns, defined from cross‐correlations, are important for identifying possible dynamical interactions, but they do not necessarily imply causation. Using the precise notion of Granger causality, we show that for long‐range stochastic temperature forecasts, the cross‐correlations are only relevant at the level of the innovations–not temperatures. This justifies the Stochastic Seasonal to Interannual Prediction System (StocSIPS) that is based on a (long memory) fractional Gaussian noise model. Extended here to the multivariate case (m‐StocSIPS) produces realistic space‐time temperature simulations. Although it has no Granger causality, emergent properties include realistic teleconnection networks and El Niño events and indices. Plain Language Summary: For forecasts less than about 10 days, Numerical Weather Prediction (NWP) and General Circulation Models (GCMs) have been highly successful, yet for longer ranges, their skill is disappointing. This has motivated the development of alternatives that are based on either the strong spatial correlations–teleconnection patterns such El Niño events–or on the long memories whereby the atmospheric state at any moment is strongly influenced by its own past. In particular, a model only using the long memory already rivals GCM monthly and seasonal temperature forecasts: The Stochastic Seasonal to Interannual Prediction System (StocSIPS). In this paper, we answer the question of whether StocSIPS skill can be further improved by using teleconnections. We do this by developing the space‐time m‐StocSIPS model that is optimally forecast by StocSIPS. In m‐StocSIPS, spatial co‐predictors do not improve the skill: There is no causal relation between different locations useful for long‐range predictions. Although m‐StocSIPS has strong spatial correlations and reproduces teleconnection patterns including El Niño events, they cannot be used to improve the long‐memory StocSIPS forecasts. The teleconnections "were already used" to build the history at every location, which is enough to produce the optimal forecast. Key Points: Granger causality shows that spatial correlations in temperature cannot be used to improve on memory‐based predictions of infinitely long seriesScaling‐based long‐range stochastic forecasting is a past value problem not an initial value problemReal‐world statistics and teleconnection patterns can be reproduced with stochastic simulations with a total lack of causal relationships [ABSTRACT FROM AUTHOR]

Knowledge of the daytime variability of cloud fraction is pivotal for the accurate determination of the atmosphere's energy balance. Yet, polar orbiting satellites are unable to fully capture daytime variability and individual geostationary satellites only provide measurements for portions of the Earth. In addition, diurnal cloud fraction variations analyzed with General Circulation Models provide results that cannot be reconciled with observations in many situations. Here, we show that the Earth Polychromatic Imaging Camera (EPIC) aboard the Deep Space Climate Observatory (DSCOVR) satellite presents a unique opportunity to examine changes in daytime global cloud fraction resolved at one‐hour frequency. For the first time, we characterize the global daytime variability of clouds with a single sensor, presenting evidence that the fraction of liquid clouds reaches its maximum over continental areas and its minimum over ocean around noon. We compare our results with previous global and regional studies and examine implications for the Earth's energy budget. Plain Language Summary: Cloud coverage changes during the day over every location of the Earth. While those movements might seem random for a particular day, patterns emerge when cloud fraction is evaluated with sufficient data in local times. The Earth Polychromatic Imaging Camera (EPIC) aboard the DSCOVR satellite observes the Earth from approximately 1.5 million kilometers away, capturing the whole sunlit side of the planet at once. Therefore, each one of EPIC's images contains information about daytime cloud fraction at different local times, with early morning and late afternoon in the left and right edges respectively. As EPIC takes between 10‐22 images per day, we can track the daytime evolution of cloud fraction with a single sensor. In this paper, we aggregate seasonally four years of data to show that there are more liquid clouds over land and less over ocean around noon. On the contrary, ice clouds evolve independently of the underlying surface type, with larger cloud fraction in the morning and afternoon and a minimum at noon. Key Points: Global daytime cycles are analyzed with a single sensor for the first time using DSCOVR/EPICLiquid cloud fraction is maximum over land and minimum over ocean around noonIce cloud fraction is higher in the morning and afternoon than around noon independently of the surface type [ABSTRACT FROM AUTHOR]

Sea surface temperature (SST) observations in the North Atlantic since 1870 reveal a region of enhanced warming off the northeastern coast of North America, and a region of cooling to the south of Greenland. It has been hypothesized that these adjacent SST trends are a result of long‐term changes in the buoyancy‐driven ocean circulation—a slowdown of the Atlantic Meridional Overturning Circulation. The impacts of these historical SST trends on the atmosphere are estimated using idealized atmospheric general circulation model experiments in which the global atmosphere is exposed to modern climatological forcing minus the aforementioned regional SST trends. The local response includes a negative North Atlantic Oscillation tendency and southward shift of the wind forcing for the subtropical gyre. Due to planetary wave propagation, the regional SST trends also induce a northward shift of the intertropical convergence zone over the Indian Ocean. Implications for climate feedbacks and projections are discussed. Plain Language Summary: The ocean surface is warming over most of the planet, with a couple of notable exceptions. One is over the North Atlantic Ocean, just south of Greenland, where the temperature of the ocean surface has actually been cooling by about 1°C since 1870. Nearby, extending off the northeastern coastline of North America is a region where the ocean surface has been warming much faster than the global ocean on average—by about 1.5°C since 1870. This side‐by‐side pair of accelerated warming and cooling trends is likely due to a slowdown of the ocean's overturning circulation, which carries large amounts of heat energy from the tropics toward the poles. This paper reveals the effects of those unusual ocean temperature trends in the North Atlantic on the atmospheric circulation using a computer model of the global atmosphere. The model simulations indicate that these ocean temperature trends are causing shifts in the jet stream, changing the way the winds propel the upper ocean currents, and even have impacts quite far away by moving the tropical rain belt northward in the Indian Ocean. Key Points: The impact of historical sea surface temperature trends in the North Atlantic since 1870 is simulated with a global atmospheric modelAdjacent warming and cooling trends in the North Atlantic Ocean induce a negative NAO‐like response and southward‐shifted gyre forcingPropagation of planetary waves away from the North Atlantic induces a northward‐shifted intertropical convergence zone in the Indian Ocean [ABSTRACT FROM AUTHOR]

Reconstruction of the atmospheric circulation from the numerical output of general circulation model (GCM) and reanalysis products often suffers from spurious values resulting in imbalances in the mass, energy, and water transport. A correction hence is needed prior to the analysis of energy transport. Most of the previous correction methods only employ a mass budget adjustment since it is the primary source of error. The present study proposes a new method of mass flux correction by constraining the mass, energy, and water budgets that can be applied to meridional energy transport and overturning circulation. The new method seeks a vertical dependent solution, unlike the conventional barotropic correction procedures. The procedure has been tested for one aquaplanet GCM and a reanalysis product. The method successfully corrects the spurious imbalances in the mean meridional energy transport and circulation. Plain Language Summary: Meridional energy transport is an essential climate diagnostic. However, the calculation of energy transport from climate model output and reanalyses often encounters spurious values due to mass, energy, and water budget imbalances. Although climate models are based on fundamental conservation laws, the numerical models often slightly deviate due to various interpolations, approximations, and low resolution. Traditionally, such imbalances are corrected by adjusting the mass flux to satisfy mass conservation, which corrects the spurious values in energy transport to a certain extent. The present paper proposes a new mass flux correction method that satisfies not only the mass conservation but also the energy and water conservation. Unlike the conventional vertically uniform correction, the present method provides a vertically dependent correction. Moreover, the new mass flux correction can also be applied to correct the mean meridional circulation. The result demonstrates that the new method is a remarkable improvement from the conventional methods. Key Points: The present study proposes a new flux correction method for vertically integrated zonal mean energy transport in the atmosphereThe proposed method satisfies the conservation of mass, energy, and water vapor, which was not a characteristic of most previous methodsUnlike the previous methods, the new approach provides a vertical dependent correction [ABSTRACT FROM AUTHOR]

The National Aeronautics and Space Administration (NASA) Goddard Earth Observing System global circulation model (GCM) is evaluated through a cascade of simulations with increasing horizontal resolution. This model employs a nonhydrostatic dynamical core and includes a scale‐aware, deep convection parameterization (DPCP). The 40‐day simulations at six resolutions (100 km to 3 km) with unvarying model formulation were produced. At the highest resolution, extreme experiments were carried out: one with no DPCP and one with its scale awareness eliminated. Simulated precipitation, radiative balance, and atmospheric thermodynamic and dynamical variables are well reproduced with respect to both observational and reanalysis data. As model resolution increases, the convective precipitation smoothly transitions from being mostly produced by the convection parameterization to the cloud microphysics parameterization. However, contrary to current thought, these extreme cases argue for maintaining, to some extent, the scale‐aware DPCP even at 3‐km scale, as the run relying solely on explicit grid‐scale production of rainfall performs more poorly at this resolution. Plain Language Summary: Global circulation models (GCMs) are the means we have to predict the weather and assess the future climate on daily, seasonal, and even century‐long timescales. GCMs are computational tools that employ approximate forms of the fundamental equations governing the time evolution of the atmosphere. Given the broad spectrum of scales of the atmospheric phenomenon, computational limitations require parameterizations for processes not explicitly resolved at the model computational grid. The next generation of the National Aeronautics and Space Administration (NASA) Goddard Earth Observing System (GEOS) GCM is being developed as a unified, seamless model to be applied across a broad spectrum of spatial and temporal scales of the atmospheric motions. This paper provides an evaluation of relevant aspects of the GEOS forecasts across a pertinent range of horizontal resolution with an unvarying model formulation. We focus specifically on the parameterization of deep convection and evaluate its influence on model results down to the a few kilometers scale. We arrive at the unexpected conclusion that a kilometer‐scale resolution where convection is mostly explicitly resolved perform worse. Key Points: The Goddard Earth Observing System global circulation model is evaluated across a wide spectrum of horizontal resolutionAcross scales, the convective precipitation smoothly transitions from mostly produced by subgrid‐ to grid‐scale model formulationsContrary to current views, poorer results occur when scale‐aware deep convection parameterization is avoided at grid spacings of a few kilometers [ABSTRACT FROM AUTHOR]

The Venusian atmosphere hosts a 10 km deep convective layer that has been studied by various spacecrafts. However, the impact of the strong vertical mixing on the chemistry of this region is still unknown. This study presents the first realistic coupling between resolved small‐scale turbulence and a chemical network. The resulting vertical mixing is different for each species: those with longer chemical timescales will tend to be well‐mixed. Vertical eddy diffusion due to resolved convection motions was estimated, ranging from 102 to 104 m2/s for the 48–55 km convective layer, several orders of magnitude above the typically used value. In the 48–55 km convective layer, the impact of the small‐scale turbulence on the cloud layer boundaries was between 200 m and 1 km. The impact of turbulence on cloud chemistry is consistent with Venus Express/Visible and Infrared Thermal Imaging Spectrometer observations. The observability at the cloud‐top of small‐scale turbulence by VenSpec‐U spectrometer would be challenging. Plain Language Summary: Venus hosts a global sulfuric acid cloud layer between 45 and 70 km. A convective layer is present between roughly 50 and 60 km, with its variability in latitude and local time assessed by observation, with a thicker layer at high latitude and at night. One question that remains unclear is how this turbulence mixes momentum, heat, and chemical species. Especially, the impact of the strong vertical mixing on the chemistry of this region is still unknown. To investigate this topic, we use a convection‐resolving model coupled for the first time with a realistic chemical network. The resulting vertical mixing is different for each species: those with longer chemical timescales will tend to be well‐mixed. 1D and global circulation models use the so‐called vertical eddy diffusion approach to represent turbulent motion, quantified in our model and underestimated in chemistry models. The small‐scale turbulence in the cloud layer causes a variation in the altitude of the top and bottom boundaries of the cloud. Our model shows that the impact of turbulence on cloud chemistry corresponds well to what has been observed by satellites. In the future, the EnVision mission will be able to observe chemical species at the small turbulence scales. Key Points: Estimation for the first time of the spatial and temporal variability of chemical species due to vertical mixingQuantification of the vertical eddy diffusion coefficient, order of magnitude above typical used valuesCloud‐top altitudes change by 0.2–1 km due to vertical convective mixing and gravity waves [ABSTRACT FROM AUTHOR]

Planetary‐scale mountain waves have been observed at the cloud top of Venus and throughout the cloud deck. As they propagate from the surface to the cloud layers, multiple observations and numerical simulations have shown that they grow in size and do not break. However, the fate of mountain waves in the transition region and thermosphere, above the super‐rotating atmosphere, has only been addressed with two‐dimensional models. We conduct for the first time a simulation of mountain waves with a state‐of‐the‐art Venus climate model that includes the thermosphere. We find that mountain waves can propagate up to at least 150 km altitude, well above the transition region. They affect the circulation of the transition region, by reducing winds speeds, and the subsolar‐to‐antisolar circulation. Plain Language Summary: The planet Venus rotates very slowly, with a rotation period of 243 days, while its cloud cover rotates westwards much faster, with a period of 4 days at 70 km altitude, a phenomenon known as superrotation, which is not fully explained yet. Higher up, in the thermosphere, the air flows from the dayside to the nightside, rather than westwards. The thermosphere is difficult to explore by remote sounding due to the low air density, and thus its connection to the surface and the superrotating layer is poorly understood. In 2015, the Venus‐orbiting spacecraft Akatsuki detected a massive standing wave generated at the surface and reaching the superrotating layer, despite the fast zonal winds. Here, we show that this wave also reaches the thermosphere. Key Points: The first simulation of mountain waves with a 3D ground‐to‐thermosphere General Circulation Model is performedMountain waves reach the thermosphere of Venus and change the SS‐AS winds by up to 80 m/s, locally in the afternoonThe vertical wind field above the cloud deck is dominated by the effect of mountain waves [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]

Climate models exhibit significant rainfall bias in mountainous regions. One reason is the insufficient representation of orographic anisotropy in these models. In this study, we implement the orographic drag scheme with 3‐D orographic anisotropy (all flow directions (AFD)) into a general circulation model and investigate its impact on Nanling rainfall simulation where models have systematic dry bias in the summer. It is shown that the AFD alleviated the Nanling mountain rainfall bias by over 60%. This is through an anomalous "lower‐convergence‐higher‐divergence" deceleration pattern of the flow windward of the Nanling Mountains that enhanced vertical motion and low‐level moisture convergence. The results suggest the importance of explicit orographic anisotropy representation in rainfall simulation in mountainous regions. Plain Language Summary: Simulation of the Nanling mountain summer rainfall has shown significant dry bias. In this study, we implemented a scheme considering fully impact of direction‐dependent change of orographic height on mountain flow in a global climate model to examine its effect on this bias. It is shown that the new scheme led to better simulation of the orographic rainfall compared to the original scheme due to improvement in moisture transport and vertical motion. This demonstrates that explicit representation of this effect for all flow directions is important in climate modeling especially in the simulation of the orographic rainfall. Hence, it should be necessary to represent this effect in the drag parameterization. Key Points: Nanling mountain rainfall simulation is improved when an orographic drag scheme is used with anisotropy for all flow directionsThe impact is due to anomalous drag windward of the Mountains that enhanced vertical motion and low‐level moisture convergenceThe results suggest the importance of explicit orographic anisotropy in climate simulations [ABSTRACT FROM AUTHOR]

Maximum sea surface salinity (SSS) anomalies are found in the central Pacific during the eastern Pacific El Niño (EPEN) and located further westward during the central Pacific El Niño (CPEN), but whether these differences affect event strengths is unclear. By performing ocean general circulation model experiments via modifying freshwater flux anomalies, we find salinity effects on surface warming during both types are highly sensitive to zonal locations of SSS anomalies, with the strongest warming induced by the SSS anomalies near the international dateline. Further analysis reveals that vertical mixing and entrainment dominate this temperature sensitivity, with the strongest response to SSS anomalies occurring in the central Pacific. The central‐Pacific SSS anomalies increase EPEN warming by 0.15°C while the westward‐located SSS anomalies make little contribution to CPEN warming. Therefore, the distinct zonal structures of SSS anomalies facilitate stronger EPEN than the CPEN, increasing their difference in intensity by about 10%. Plain Language Summary: The El Niño‐Southern Oscillation (ENSO) is the strongest year‐to‐year climate variability in the planet. The central Pacific El Niño (CPEN) have been recognized in recent decades, with weaker surface warming located more westward, in contrast to the traditional eastern Pacific El Niño (EPEN). Previous studies have underscored various air‐sea processes in shaping these differences, however, the impact of salinity remains unknown. Here based on ocean model experiments, we found the salinity effect on El Niño warming is very sensitive to zonal locations of salinity anomalies. The salinity anomalies located in the central Pacific are more effective in modulating local ocean vertical stratification, weakening the colder subsurface water into the mixed layer and further enhancing the surface warming. Therefore, the central equatorial Pacific‐located salinity anomalies during EPEN contributes to its stronger warming than those west‐located salinity anomalies during CPEN, enhancing the sea surface temperature difference between the two events by about 10%. Our results provide new insight in understanding the ENSO diversity and also its low‐frequency variability, which may be helpful for interpreting more complex model simulations and for and predicting ENSO variations. Key Points: Salinity anomalies in the central Pacific induce the strongest surface warming during both types of El Niño, tapering off to the east and westThe distinct sea surface salinity zonal structures between the two El Niños amplify their difference in sea surface temperature magnitude by about 10%Salinity effects on vertical mixing and entrainment account for the different eastern Pacific and central Pacific El Niño responses [ABSTRACT FROM AUTHOR]

Simulation of the January 2017 period using a gravity‐wave resolving global circulation model (HIAMCM) reveals a predominant eastward propagating diurnal tide with zonal wavenumber three (DE3) in the southern summer mesosphere from about 60 to 90 km height at middle to high latitudes. We provide observational evidence based on MERRA‐2 reanalysis and Sounding the Atmosphere using Broadband Emission Radiometry satellite observations for the validity of this result. The attenuation of the DE3 below the mesopause generates a significant eastward Eliassen‐Palm flux divergence that contributes to the residual circulation. We also show that the diurnal tide in the northern summer mesosphere likely consists of mainly eastward propagating components. These findings contradict the common perception of a weak diurnal tide in the summer mesosphere. Plain Language Summary: Thermal tides represent the strongest wave‐related wind and temperature perturbations in the mesosphere and lower thermosphere. Current wisdom about the morphology of tides is based on linear models and climate models with parameterized gravity waves, predicting a weak westward propagating tide with zonal wavenumber one as the predominant diurnal component in the summer mesosphere. New results based on a high‐resolution model reveal strong eastward propagating diurnal tides in the summer mesosphere. In particular, the eastward component with zonal wavenumber three (DE3) turns out to be the predominant tidal component in the southern summer mesosphere below the mesopause at middle to high latitudes. This finding is in accordance with previous ground‐based lidar observations, as well as with MERRA‐2 reanalysis and analysis of Sounding the Atmosphere using Broadband Emission Radiometry satellite observations. Key Points: Sounding the Atmosphere using Broadband Emission Radiometry satellite observations and MERRA‐2 reanalysis show a significant DE3 tidal component in the southern summer mesosphereThe HIAMCM with resolved gravity waves confirms these observations and shows that the DE3 extends up to ∼90 km at high latitudesThe summer mesospheric DE3 gives a 10%–20% contribution to the eastward Eliassen‐Palm flux divergence that drives the equatorward residual circulation [ABSTRACT FROM AUTHOR]

Wind power input to near‐inertial motions is an important energy source for generating diapycnal mixing in the ocean. However, the distribution and long‐term trend of this input over the Southern Ocean have yet to be quantified. In this study, we investigate the near‐inertial wind power input (WPIi) to the Southern Ocean using a global eddy‐permitting coupled ocean‐sea ice model forced by a high‐resolution atmospheric reanalysis product. Our results reveal a zonally asymmetric distribution of WPIi in the Southern Ocean, with the strongest input in the South Indian Ocean and the weakest in the South Pacific. The integrated WPIi between 30°S and 60°S exhibits a significant positive trend over the past four decades due to the intensification of mesoscale weather systems. The surface mixed‐layer depth is found to modulate the spatial pattern and trend of WPIi by altering the surface near‐inertial currents. Plain Language Summary: Wind fluctuations can excite surface ocean currents that oscillate at frequencies close to the inertial frequency. These near‐inertial motions play an important role in generating turbulent mixing in the ocean. However, the distribution and long‐term trend of wind power input to near‐inertial motions in the Southern Ocean remains unquantified. In this study, we investigate this wind power input using a global ocean circulation model driven by a high‐resolution atmospheric reanalysis data set. Our results reveal a pronounced zonal asymmetry in the distribution of near‐inertial wind power input in the Southern Ocean. Furthermore, this power input has increased significantly over the past four decades due to the intensification of mesoscale weather systems. Results from this study have important implications for understanding Southern Ocean mixing and circulation. Key Points: Distribution of near‐inertial wind power input in the Southern Ocean is zonally asymmetricNear‐inertial wind power input in the Southern Ocean has increased significantly in recent decadesThis increase is primarily driven by the intensification of mesoscale weather systems [ABSTRACT FROM AUTHOR]

In the absence of consistent meteorological data on Mars, the morphology of dunes can be employed to study its atmosphere. Specifically, barchan dunes, which form under approximately unimodal winds, are reliable proxies for the dominant wind directions. Here, we characterize near‐surface winds on Mars from the morphology of >700,000 barchans mapped globally on the planet by a convolutional neural network. Barchan migration is predominantly aligned with known southern‐summer atmospheric circulation patterns—northerly at mid‐latitudes and cyclonic near the north pole—with the addition of an anti‐cyclonic north‐polar component that likely originates from winds emerging from the ice cap. Locally, migration directions deviate from regional trends in areas with high topographic roughness. Notably, obstacles <100 km such as impact craters are efficient at deflecting surface winds. Our database, which provides insights into planetary‐scale aeolian processes on modern‐day Mars, can be used to constrain global circulation models to assist with predictions for future missions. Plain Language Summary: Crescent‐shaped sand dunes are prevalent across the deserts of Mars. Here, we use the physical relationship between the shape of these dunes and the winds that form them to infer the directions of surface winds on Mars on a global scale. We find that dunes typically adhere to the global circulation patterns of Mars' atmosphere, and that local topographic winds are mostly important in areas with high topographic roughness such as inside deep impact craters. Our global wind map can serve to calibrate numerical climate models, which in turn can help us learn about the recent and modern‐day climate of Mars. Key Points: We derive global barchan dune migration directions on Mars using a convolutional neural networkAeolian sediment pathways on Mars are largely controlled by the planet's global circulationSurface winds are locally deflected by topographic obstacles with horizontal scales <100 km [ABSTRACT FROM AUTHOR]

Attributing sources of tropical cyclogenesis (TCG) bias to large‐scale circulation in global circulation models is challenging. Here, we propose the use of empirical orthogonal functions as an approach to understand model bias of TCG. Two leading modes of large‐scale wind circulations in the West Pacific can explain the TCG frequency and location in both climate reanalysis and the MetUM model. In the reanalysis, the two modes distinguish the summer monsoon trough position and the strength of the north Pacific subtropical high. However, in the model, the wind circulations are biased toward the positive phase of simulated modes thus overestimating TCG in the entire Main Development Region. This bias is further related to the north‐eastward shifted monsoon trough and a weakened subtropical high, and overly strong tropics‐subtropics connections. This approach could be deployed more widely to other basins and models to diagnose the causes of TCG bias. Plain Language Summary: General Circulation Models (GCMs) have bias in tropical cyclogenesis (TCG). This bias largely reduces the credibility of GCMs. In this study, we suggest an empirical orthogonal function‐based approach to trace the sources of TCG bias in the western North Pacific more rigorously back to large‐scale wind circulation patterns. We find that TCG bias in both basin‐wide and regional scales is a combination of the two biased circulation patterns, associated with too strong tropics‐subtropics connections. The two biased circulation patterns are also featured with a north‐eastward shifted monsoon trough and a weakened subtropical high. We choose the Met Office climate models to demonstrate the approach. But, it can be applied to other GCMs and basins to better understand TCG bias and inform further model development. Key Points: Multivariate empirical orthogonal functions are used to diagnose model bias of tropical cyclogenesis (TCG) in the West PacificTwo leading modes of large‐scale wind circulations can explain most of TCG variability in both ECMWF fifth generation climate reanalysis and MetUMIn MetUM, positive TCG bias is related to large‐scale wind circulations biased toward the positive phase of the simulated modes [ABSTRACT FROM AUTHOR]

The Atlantic meridional overturning circulation (AMOC) is central to the climate of the Atlantic by redistributing mass, heat, and freshwater. Hydrographic sections help monitor its strength at different latitudes, and inverse box models provide estimates of AMOC, heat, and freshwater transports. We have used all available hydrographic zonal sections at 24.5°N and 30°S over the last 30 years to conclude that single section inverse models agree with monthly outputs from an ocean general circulation model at the time of the cruise. In contrast, inverse models using multiple sections at different latitudes and times of the year for each of the last three decades are more consistent with decadal averages from the same model. Therefore, solutions of inverse models with single sections are affected by aliasing and represent the state of the ocean at the time of cruise. However, aliasing is greatly reduced when using multiple sections to assess low‐frequency variability. Plain Language Summary: Heat and nutrients in the Atlantic Ocean are redistributed through a process called Atlantic meridional overturning circulation, which is being monitored to detect changes in its strength. Hydrographic data offer the possibility to assess this variability, although it can be influenced by the ocean dynamics happening at the time of the cruise. When comparing the results from inverse box models applied to single sections with numerical model output, the best fit appears for the time of the cruise. This reflects that the monthly variation affects the solutions of the inverse model, which can be understood as representative of the duration of the cruise. Inverse models using several sections from cruises carried out in different times of the year and different years average out the local temporal phenomena that can affect the results and better represent the decadal average of the numerical models. Key Points: The Atlantic meridional overturning circulation has been monitored with hydrographic data and now basin‐wide arrays enable the detection of high‐frequency variabilityInverse solutions from single sections are affected by aliasing, as they capture the circulation structure of the time of the cruiseInverse models with multiple sections at different latitudes and times agree with decadal averages from an ocean general circulation model [ABSTRACT FROM AUTHOR]

Low‐frequency (Interannual and longer timescale) variability in sea surface temperature (SST) of the Indian Ocean plays a crucial role in affecting the regional climate. Using a high‐resolution global model simulation, we show that internal oceanic variability is an important cause of the observed low‐frequency variability in the subtropical‐midlatitude south Indian Ocean (SIO) between 20° and 40°S, a marked southward shift in the latitude band of active internal variability for the low‐frequency compared to earlier estimates based on coarser Indian Ocean regional models. Notably, we show that internal variability does not contribute to the observed low‐frequency variability in the Seychelles−Chagos thermocline ridge region. Energy budget analysis shows that baroclinic instability is the primary cause for the internal variability. The slowly growing baroclinic instabilities at low frequency and longer length scale favor Rossby waves' generation, propagating the SST and sea level anomaly signals westward. Plain Language Summary: Ocean internal variability refers to the intrinsic variability arising from nonlinearity of the oceanic system. Considering that the internal variability is not tied with the external forcing, occurrence of internal variability limits the predictability of the oceanic system. Here, we use an eddy‐resolving high‐resolution ocean general circulation model to document the internal variability of sea surface temperature (SST) and sea level in the Indian Ocean on interannual‐to‐longer timescale (referred to as low‐frequency) and understand the processes that drive these variabilities. We show that internal variability in the low‐frequency band has large influence on SST and sea level in the south Indian Ocean in the latitude range of 20° and 40°S, and it is primarily caused by the baroclinic instability associated with the vertical shear between the surface eastward flow of South Indian Counter Current and the subsurface westward flow of Southern Ocean supergyre. Key Points: High‐resolution global ocean general circulation model simulation is used to document internal variability in interannual‐to‐longer timescale and identify processesInternal variability has large influence on the interannual variability of the south Indian Ocean between 20° and 40°SBaroclinic instability associated with the shear between the South Indian Counter Current and subsurface current drives the internal variability [ABSTRACT FROM AUTHOR]

Observations suggest that the tropical Pacific Ocean has lost oxygen since the 1960s leading to the expansion of its oxygen minimum zone (OMZ). Attribution to anthropogenic forcing is, however, difficult because of limited data availability and the large natural variability introduced by the Pacific Decadal Oscillation (PDO). Here, we evaluate the PDO influence on oxygen dynamics and OMZ extent using observations and hindcast simulations from two global ocean circulation models (NEMO‐PISCES, MOM6‐COBALT). In both models, the tropical Pacific oxygen content decreases by about 30 Tmol.decade−1 and the OMZ volume expands by 1.3 × 105 km3.decade−1 during PDO positive phases, while variations of similar magnitude but opposite sign are simulated during negative phases. Changes in equatorial advective oxygen supply, partially offset by biological demand, control the oxygen response to PDO. Observations which cover 39% of the tropical Pacific volume only partially capture spatio‐temporal variability, hindering the separation of anthropogenic trend from natural variations. Plain Language Summary: Human activities cause oxygen loss in the ocean, which leads to the expansion of areas with very low oxygen concentrations located in the tropics called oxygen minimum zones (OMZ). Understanding the dynamics of OMZs is crucial because they produce greenhouse gasses and are unsuitable for the life of most large marine organisms. Quantifying the response of OMZs is however complicated by natural variability that superimposes on human‐induced changes. In the Pacific Ocean, one of the strongest natural variability phenomena is the Pacific Decadal Oscillation. We used data and numerical models to assess the magnitude of oxygen changes caused by this natural phenomena in the tropical Pacific Ocean, and show that they are comparable to that of human‐induced oxygen changes. We highlight that more oxygen data is needed to accurately separate natural variations from human‐induced changes, and that a fraction of the oxygen loss attributed to human activities in prior work could in fact be due to natural variability. Key Points: Pacific Decadal Oscillation (PDO) modulates tropical Pacific oxygen content and oxygen minimum zone volume on decadal time scalesThe PDO‐induced variations are of the same order of magnitude as the anthropogenic deoxygenation signalCurrently available data are too sparse to resolve and isolate the PDO‐induced and anthropogenic signals [ABSTRACT FROM AUTHOR]

Atmospheric rivers (ARs) are long, narrow synoptic scale weather features important for Earth's hydrological cycle typically transporting water vapor poleward, delivering precipitation important for local climates. Understanding ARs in a warming climate is problematic because the AR response to climate change is tied to how the feature is defined. The Atmospheric River Tracking Method Intercomparison Project (ARTMIP) provides insights into this problem by comparing 16 atmospheric river detection tools (ARDTs) to a common data set consisting of high resolution climate change simulations from a global atmospheric general circulation model. ARDTs mostly show increases in frequency and intensity, but the scale of the response is largely dependent on algorithmic criteria. Across ARDTs, bulk characteristics suggest intensity and spatial footprint are inversely correlated, and most focus regions experience increases in precipitation volume coming from extreme ARs. The spread of the AR precipitation response under climate change is large and dependent on ARDT selection. Plain Language Summary: Atmospheric rivers (ARs) are long and narrow weather features often referred to as "rivers in the sky." They often transport water from lower latitudes to higher latitudes typically across climate zones and produce precipitation necessary for local climates. Understanding ARs in a warming climate is challenging because of the variety of ways an AR can be defined on gridded data sets. Unlike weather features such as tropical cyclones where identification methodologies are similar, algorithms that determine the characteristics of ARs vary depending on the science question posed. Because there is no real consensus on AR identification methodology, we aim to quantify the algorithmic uncertainty in AR metrics and precipitation. We compare 16 different ways of defining an AR on gridded data sets and present the range of possibilities in which an AR could change under global warming. Generally, ARs are projected to increase but the amount of that increase is a function of the algorithm. Across all algorithms and focus regions, AR precipitation is projected to become more extreme. Key Points: High‐resolution historical and future simulations are used to evaluate atmospheric river detection tools (ARDT) uncertaintyARDTs mostly show increases in frequency and intensity of future atmospheric rivers (ARs) but the scale of response is dependent on algorithmic restrictivenessMost regions experience an increase in precipitation volume coming from extreme ARs [ABSTRACT FROM AUTHOR]

El Niño‐Southern Oscillation (ENSO) is often considered as a source of long‐term predictability for extreme events via its teleconnection patterns. However, given that its characteristic cycle varies from two to 7 years, it is difficult to obtain statistically significant conclusions based on observational periods spanning only a few decades. To overcome this, we apply the global flood risk modeling framework developed by Carozza and Boudreault to an equivalent of 1,600 years of bias‐corrected General Circulation Model outputs. The results show substantial anomalies in flood occurrences and impacts for El Niño and La Niña when compared to the all‐year baseline. We were able to obtain a larger global coverage of statistically significant results than previous studies limited to observational data. Asymmetries in anomalies for both ENSO phases show a larger global influence of El Niño than La Niña on flood hazard and risk. Plain Language Summary: El Niño‐Southern Oscillation (ENSO) is one of the most important global climate phenomena. It is well‐known to affect precipitation and temperature in many areas of the world. It is therefore very important for researchers (environmental and climate sciences, economics, etc.), risk managers, decision‐ and policy‐makers to understand the influence of ENSO on flooding. Previous studies analyzed the link between ENSO and flooding but because they were based upon 40 years of data, a lot of uncertainties remained as to how ENSO has any significance on flooding. In this study, we use outputs from a climate model large ensemble that provides 1,600 years of simulated data to determine the impacts of ENSO on flooding. But because it is very difficult to run traditional flood models on 1,600 years of data, we rather leverage a machine learning approach to accelerate computations in a context where the focus is on socioeconomic impacts. We find that ENSO is a significant driver of flooding in more regions than what was previously found. Finally, there appears to be a greater global influence of El Niño than La Niña on flooding. Key Points: We simulated an equivalent of 1,600 years of realistic flood events globally using a statistical model forced with climate model outputsWe found a statistically significant (α = 0.05) influence of El Niño‐Southern Oscillation (ENSO) over 55% of land area for flood occurrence and over 69% for flood impactAsymmetries in anomalies for both ENSO phases show a larger global influence of El Niño than La Niña on flood hazard and risk [ABSTRACT FROM AUTHOR]

Mooring data collected at a flat‐topped seamount suggest the generation of pure inertial waves (PIWs; waves with a dominant frequency equal to the local inertial frequency f) by low‐frequency flows over large‐scale topography. Energetic PIWs were observed within a narrow depth range (∼100 m) near the seafloor at the edge of the summit. These waves could be associated with low‐frequency flows. A two‐dimensional nonhydrostatic model was used to show that the observed PIWs are most likely internal wave beams generated by low‐frequency flows over the seamount. Two types of PIWs were identified via observation and model. The first is a PIW that can only travel horizontally. The other propagates upward, with super‐inertial intrinsic frequency that is Doppler‐shifted by the flows to f. Nonlinear triadic interactions among waves with the frequencies [0, f, f] may transfer energy from mean flows to PIWs, promoting energy decay of geostrophic flows over large‐scale topography. Plain Language Summary: Near‐inertial waves (NIWs) are intrinsic motions of the ocean caused by Earth's rotation. Understanding their generation and evolution is key to parameterizing NIWs and the associated mixing in global ocean circulation models. This study presents novel observations suggesting that energetic pure inertial waves (PIWs; i.e., NIWs with a dominant frequency appearing at the local inertial frequency) are generated by low‐frequency flows over large‐scale seamount topography in the abyssal ocean. The nonlinear forcing of low‐frequency flows due to their acceleration near the seamount summit is suggested to be essential for generating PIWs. These findings provide further insight into NIWs in the abyssal ocean, which is important for understanding the distribution of NIWs and the energy decay of geostrophic flows over topography. Key Points: Energetic pure inertial waves (PIWs) were observed within a narrow depth range near the seafloor at a large abyssal seamountNear‐bottom‐enhanced PIWs stem from nonlinear forcing of low‐frequency flows over the seamountLow‐frequency flows over the seamount generate two types of PIWs: nonvertically propagating and upward‐propagating [ABSTRACT FROM AUTHOR]

We present high‐resolution simulation results of the response of the ionosphere/plasmasphere system to the 15 January 2022 Tonga volcanic eruption. We use the coupled Sami3 is Also a Model of the Ionosphere ionosphere/plasmasphere model and the HIgh Altitude Mechanistic general Circulation Model whole atmosphere model with primary atmospheric gravity wave effects from the Model for gravity wavE SOurces, Ray trAcing and reConstruction model. We find that the Tonga eruption produced a "super" equatorial plasma bubble (EPB) extending ∼30° in longitude and up to 500 km in altitude with a density depletion of 3 orders of magnitude. We also found a "train" of EPBs developed and extended over the longitude range 150°–200° and that two EPBs reached altitudes over 4,000 km. The primary cause of this behavior is the significant modification of the zonal neutral wind caused by the atmospheric disturbance associated with the eruption, and the subsequent modification of the dynamo electric field. Plain Language Summary: The Hunga Tonga‐Hunga Ha'apai volcanic eruption occurred on 15 January 2022 at 04:14 UT and generated a massive atmospheric disturbance that caused major effects in the ionosphere worldwide. Using a high‐resolution coupled ionosphere/thermosphere model we show that the changes in the thermospheric winds strongly modified the electrodynamics of the ionosphere. This led to the development of a "train" of equatorial plasma bubbles (EPBs), regions of very low electron density, in the western Pacific sector. Moreover, two EPBs reached unusually high altitudes, over 4,000 km. Key Points: Modeling of the Tonga volcanic eruption show equatorial plasma bubbles (EPBs) develop in the Pacific sectorA large equatorial bubble formed below 500 km roughly 30° in longitudeEPBs rose to very high altitudes (>4,000 km) [ABSTRACT FROM AUTHOR]

Recent studies have suggested that the Madden‐Julian oscillation (MJO) could be generated as part of atmospheric adjustment to localized equatorial heating in models properly resolving moist convection. Here we use the Super‐parameterized Community Atmosphere Model (SPCAM) to study atmospheric response to transient sea surface warming in the equatorial Indian Ocean, which leads to the excitation of an MJO event, robust across different experiments, in addition to the expected equatorial Rossby and Kelvin waves. A moist static energy (MSE) budget analysis suggests that longwave and surface turbulent latent heat flux anomalies are predominantly responsible for the MJO excitation; however, these terms oppose its eastward propagation. In contrast, advection of MSE generally weakens the MJO amplitude, but contributes to its eastward propagation. These results highlight the role of the MJO in the moist atmospheric adjustment to localized tropical heating, with implications for the MJO mechanisms and prediction. Plain Language Summary: The Madden‐Julian oscillation (MJO) is a large‐scale eastward‐propagating precipitation system in the tropical atmosphere, which has strong impacts on weather and climate in the tropics and beyond. Here we investigate the excitation of an MJO event in response to a localized transient sea surface warming in the equatorial Indian Ocean using the Super‐parameterized Community Atmosphere Model (SPCAM), a numerical atmospheric general circulation model that simulates cumulus convection explicitly. We find that in addition to equatorial waves expected from the classical theories of equatorial atmospheric dynamics, a robust MJO event is generated in response to the imposed sea surface warming. An energy budget analysis is conducted to understand the mechanisms for initiation and eastward propagation of this MJO event. The study highlights the importance of the MJO in the atmospheric response to tropical heating, with implications for the MJO prediction, as our results suggest that warm sea surface temperature anomalies in the equatorial Indian Ocean can initiate MJO events. Key Points: In Super‐parameterized Community Atmosphere Model, a robust Madden‐Julian oscillation (MJO) event is excited in response to transient sea surface warming in the equatorial Indian OceanLongwave and latent heat flux anomalies are predominantly responsible for the MJO excitation, which however oppose its eastward propagationAdvection of moist static energy generally weakens the MJO amplitude but contributes to its eastward propagation [ABSTRACT FROM AUTHOR]

Heatwaves are persistent temperature extremes associated with devastating impacts on human societies and ecosystems. In the midlatitudes, amplified quasi‐stationary Rossby waves have been identified as a key mechanism for heatwave occurrence. Amplified waves with preferred longitudinal locations lead to concurrent extremes in specific locations. It is therefore important to identify the essential components in the climate system that contribute to phase‐locking of wave patterns. Here, we investigate the role of dry atmospheric dynamics and topography in causing concurrent heatwaves by using an idealized general circulation model. Topography is included in the model experiments as a Gaussian mountain. Our results show that amplified Rossby waves exhibit clear phase‐locking behavior and a decrease in the zonal phase speed when a large‐scale localized topographic forcing is imposed, leading to concurrent heat extremes at preferred locations. Plain Language Summary: Heatwaves are among the most deadly natural disasters. Since climate projections indicate an increase in the severity and frequency of heatwaves, it is important to understand which processes are responsible for their occurrence. Heatwaves in midlatitudes tend to be associated with atmospheric waves, characterized by a strong meandering of the jet stream. Occasionally, waves tend to reduce their longitudinal propagation speed along with an amplification of their amplitude in preferred locations. This behavior is known as phase‐locking and can lead to extreme weather events, occurring simultaneously in different regions, as for example, during the Russian heatwave and Pakistan flooding in 2010. Here, we investigate the role of large‐scale mountains in driving concurrent heat extremes. We use simulations from an idealized atmospheric model with an idealized mountain, and keeping only the essential atmosphere dynamics represented. In the model, topography alone leads to the occurrence of phase‐locked circumglobal waves and localized heatwaves. The eastward velocity of the waves is substantially reduced due to topography, which can be linked to an increase in heatwaves in specific areas. This research lays the basis for understanding the fundamental factors that lead to concurrent extreme weather events, which is important to improve their forecasts. Key Points: The inclusion of topography in an idealized model setup yields global‐scale slow‐moving Rossby waves with preferred longitudinal locationsWhen these slow‐moving Rossby waves amplify they lead to an increased frequency of concurrent heatwaves in preferred longitudinal locationsIn the model, zonal wavenumbers 5 and 6 exhibit the strongest anomalies, which strongly impact temperature and heatwave frequency [ABSTRACT FROM AUTHOR]

The consecutive occurrence of meteorological dry and wet extremes has been receiving increasing attention due to potentially larger social and environmental impacts than single extremes. However, the changing characteristics of transitions between dry and wet periods remain poorly understood. Here we investigate the dynamic evolution of dry‐to‐wet transitions in response to climate warming, using the Standardized Precipitation Evapotranspiration Index as well as observations and general circulation models for the periods of 1954–2014 and 2040–2100. We find that approximately three‐fifths of global land area are projected to experience an accelerated dry‐to‐wet transition. Southern Asia has been experiencing the most severe dry‐to‐wet transitions and is projected to suffer more frequent, more intense, and accelerated dry‐to‐wet transitions. The increasing potential evapotranspiration (PET) variability plays an important role in accelerating the dry‐to‐wet transition in Southern Asia, while precipitation and PET variabilities contribute to the intensification of dry‐to‐wet transitions in Southern North America. Plain Language Summary: The consecutive occurrence of droughts and floods has widespread impacts on agriculture, the ecosystem, and the environment. Here we examine the changes in frequency, intensity, and elapsed time of transitions between dry and wet periods under a warming climate, based on observations and an ensemble of 10 Coupled Model Intercomparison Project Phase 6 climate simulations. We find that approximately 59% of global land area are expected to experience a shorter transition time between dry and wet periods. Southern Asia suffers the most severe dry‐to‐wet transition. Furthermore, our findings reveal that enhanced potential evapotranspiration (PET) variability contributes to the accelerated transition between dry and wet periods over Southern Asia, and the acceleration of dry‐to‐wet transitions in Southern North America is associated with an increase in precipitation and PET variabilities as climate warms. Key Points: Approximately three‐fifths (59%) of global land area are projected to experience accelerated transition between dry and wet periodsSouthern Asia suffers the most from severe transition between dry and wet periodsEnhanced precipitation and potential evapotranspiration variabilities contribute to the accelerated dry‐to‐wet transitions [ABSTRACT FROM AUTHOR]

Systematic biases in General Circulation Model (GCM) simulations require some adjustment before their use in change assessment and adaptation management studies. GCM simulations of the Coupled Model Intercomparison Project 6, although outperform the previous generations of GCMs, exhibit persistent biases in magnitude, variability, and frequency across a range of variables of interest. Here, we propose a novel continuous wavelet‐based bias correction (CWBC) approach to address such biases in the time‐frequency domain. The correction focuses on the magnitude and frequency of the modeled time series, as interpreted via the time‐varying spectrum ascertained using the continuous wavelet transform. The approach is applied to correct systematic biases in the time series of Niño 3.4 sea surface temperature and Arctic sea‐ice extent. The application of CWBC successfully reproduces observed attributes in the bias‐corrected time series of both climate variables for the current climate simulation along with providing a sensible projection for the future. Plain Language Summary: The latest generation of General Circulation Models outperforms older versions in simulating the current and future climate. However, biases in magnitude, frequency, variability, and persistence related characteristics still remain in model simulations. The nested time based and other frequency analysis‐based bias correction approaches, for example, a fast Fourier transform or a discrete wavelet‐based bias correction, offer a good alternative to correct the biases. However, they cannot capture the underlying components of climate variables in the non‐dyadic spectrum. Keeping this in mind, we present here a continuous wavelet transform based bias correction approach to obtain the underlying information of climate variables at a finer spectrum resolution. The applications of continuous wavelet‐based bias correction algorithm show remarkable improvement in the amplitude and frequency of two example datasets, namely, a Coupled Model Intercomparison Project 6 (CMIP6) sea surface temperature simulation and the ensemble mean of CMIP5 Arctic sea‐ice extent simulations, for the current climate and more sensible correction for future climate simulations. Key Points: Systematic biases exist in the magnitude and frequency of climate events simulated by the modelsA continuous wavelet transform‐based method for identifying and correcting biases in the time‐frequency domain is presentedTime series of Niño 3.4 sea surface temperature and Arctic sea‐ice extent is used to demonstrate the usefulness of the approach [ABSTRACT FROM AUTHOR]

A robust simulation of tropical Pacific Ocean decadal‐scale zonal wind stress trends can increase the confidence in projections of global surface temperature and regional sea level rise, yet coupled general circulation models simulate weaker trends than observed. When forced with observed sea surface temperatures, the atmospheric component of these models still simulates a weaker zonal wind stress trend during 1992–2008 (and 1992–2011) than observed. Yet, this decadal wind trend bias is not evident at the 850 hPa level. We show that the modelled wind trend bias is related to deficiencies in monthly wind stress variability. Furthermore, the strength of the connectivity between the surface and 850 hPa was also an indicator of the wind stress trend. Models that simulated a more realistic wind stress trend tend to simulate a stronger Pacific zonal sea level pressure gradient intensification than observed and a South Pacific Convergence Zone shift like that observed. Plain Language Summary: From early 1990s to late 2010, the equatorial trade winds strengthened in the Pacific Ocean. This coincided with a rapid rise in sea level in the western tropical Pacific and a slowdown in global surface temperature warming. This long‐term change in the Pacific had a large impact, but ocean‐atmosphere models cannot produce a change of a similar strength as observed. It is difficult to determine whether the ocean or atmosphere components of the model are at fault. This study looks at factors contributing to the inability of models to simulate trade wind strengthening by focusing on the atmosphere component of the model. We find that improving the month‐to‐month response of wind to sea surface temperatures may improve the strength of long‐term wind changes. Improvements in wind changes may also be made if models improve their connection between winds higher in the atmosphere and those at the surface. Models that have stronger wind changes have a better representation of south tropical Pacific rainfall changes, but also rely on a stronger than observed sea level pressure response. Key Points: Atmosphere‐only models, like coupled models, struggle to simulate tropical Pacific wind stress trends of similar magnitude to observedModels with weaker wind trends tend to have a weaker monthly wind response to sea surface temperatures and a weaker link to winds aloftModels with strong trends have a better South Pacific Convergence Zone shift but a too strong sea level pressure gradient [ABSTRACT FROM AUTHOR]

Among mechanisms accounting for atmospheric pCO2 drawdown during glacial periods, processes operating in the North Atlantic (NA) and Southern Ocean (SO) have been proposed to be critical. Their individual and synergic effects during a course of glaciation, however, remain enigmatic. We conducted simulations to examine these effects at idealized glacial stages. Under early‐glacial‐like conditions, cooling in the SO can trigger an initial pCO2 drawdown while the associated sea ice expansion has little impact on air‐sea gas exchange. Under later glacial‐like conditions, further cooling in the NA enhances ocean carbon uptake due to a stronger solubility pump, and the SO‐induced stronger deep stratification prevents carbon exchange between the deep and upper ocean. Meanwhile, strengthened dust deposition increases the SO contribution to the global biological pump, and CO2 outgassing is suppressed by fully extended sea ice cover. More carbon is then stored in the deep Pacific, acting as a passive reservoir. Plain Language Summary: CO2 is one of the most important "greenhouse" gases that drive global climate changes. Tens of thousands of years ago, during the glacial time (known as the "ice age"), atmospheric CO2 was much lower than today. Research has shown that processes in different ocean regions, such as the Southern Ocean (SO) and North Atlantic (NA), made essential contributions to the glacial CO2 drawdown. However, the interplay between these processes remains unclear. Here, using an ocean general circulation model coupled with an atmospheric box that includes active air‐sea CO2 exchange, we examined the key processes at idealized stages of a glacial cycle. We found that: at an early stage, surface cooling in the SO triggers the CO2 decrease by shortening the time for air‐sea CO2 exchange; during a late stage, the SO and NA cooling act collaboratively to store more carbon in the deep ocean, where the SO plays a more determining role. Pacific seems to be a passive carbon pool during glaciation. Sea ice expansion hinders CO2 outgassing increasingly over the course of glaciation. Further CO2 decrease is achieved by a larger contribution of the SO to the global biological carbon pump. Key Points: The stepwise glacial atmospheric pCO2 decrease is linked to a Southern Ocean (SO)‐controlled synergy of interhemispheric mechanismsSea ice prevents CO2 outgassing increasingly from the early‐ to later‐glacial timeThe SO contribution to the global biological carbon pump might increase from interglacial to glacial periods [ABSTRACT FROM AUTHOR]

The Nadir and Occultation for MArs Discovery (NOMAD)/UV‐visible (UVIS) spectrometer on the ExoMars Trace Gas Orbiter provided observations of ozone (O3) and water vapor in the global dust storm of 2018. Here we show in detail, using advanced data filtering and chemical modeling, how Martian O3 in the middle atmosphere was destroyed during the dust storm. In data taken exactly 1 year later when no dust storm occurred, the normal situation had been reestablished. The model simulates how water vapor is transported to high altitudes and latitudes in the storm, where it photolyzes to form odd hydrogen species that catalyze O3. O3 destruction is simulated at all latitudes and up to 100 km, except near the surface where it increases. The simulations also predict a strong increase in the photochemical production of atomic hydrogen in the middle atmosphere, consistent with the enhanced hydrogen escape observed in the upper atmosphere during global dust storms. Plain Language Summary: Global dust storms are rare but impactful events on Mars, occurring about once in a decade. Previous investigations found how water vapor is redistributed throughout the entire atmosphere in a dust storm. Photolysis of water vapor by sunlight produces highly reactive species that destroy ozone (O3). Here we present O3 measurements taken by the NOMAD/UVIS instrument on the ExoMars Trace Gas Orbiter in the 2018 global dust storm. After advanced data filtering, they demonstrate how O3 in the middle atmosphere was much reduced compared to one Mars year later when no dust storm occurred. 3D atmospheric model simulations of atmospheric chemistry in the global dust storm confirm this planet‐wide O3 destruction, and help to understand the involved processes. The simulations also predict a strong increase in production of atomic hydrogen in the middle atmosphere, that can explain the observed increased hydrogen atmospheric escape during global dust storms. Key Points: NOMAD ozone (O3) data filtering during the 2018 global dust storm shows strong O3 destruction compared to one year later with no dust storm3D simulations of atmospheric chemistry in the 2018 global dust storm are presented to understand impact on odd hydrogen and odd oxygenThe model confirms middle‐atmospheric O3 destruction in the dust storm and predicts increased photochemical production of hydrogen [ABSTRACT FROM AUTHOR]

The influence of atmospheric composition on the climates of present‐day and early Earth has been studied extensively, but the role of ocean composition has received less attention. We use the ROCKE‐3D ocean‐atmosphere general circulation model to investigate the response of Earth's present‐day and Archean climate system to low versus high ocean salinity. We find that saltier oceans yield warmer climates in large part due to changes in ocean dynamics. Increasing ocean salinity from 20 to 50 g/kg results in a 71% reduction in sea ice cover in our present‐day Earth scenario. This same salinity change also halves the pCO2 threshold at which Snowball glaciation occurs in our Archean scenarios. In combination with higher levels of greenhouse gases such as CO2 and CH4, a saltier ocean may allow for a warm Archean Earth with only seasonal ice at the poles despite receiving ∼20% less energy from the Sun. Plain Language Summary: The composition of the atmosphere, especially the abundance of greenhouse gases, famously influences Earth's climate system. We use a climate model to show that the composition of the ocean can also have a major impact on surface temperature and ice cover. We focus specifically on the amount of salt dissolved in seawater, and we find that saltier oceans tend to result in warmer climates. These effects are modest today, but salt may be a key ingredient for early Earth habitability in the distant past when the Sun was less bright. Key Points: Saltier oceans result in warmer climates with less sea iceWarming with increasing salinity is strongly affected by changing ocean dynamicsA saltier ocean may have helped keep early Earth warm when the Sun was less luminous [ABSTRACT FROM AUTHOR]

The season‐dependent impacts of the tropical North Atlantic (TNA) sea surface temperature anomaly (SSTA) on subsequent El Niño‐Southern Oscillation (ENSO) evolution were investigated through observational and modeling studies. The results indicate that, although the maximum amplitude of the TNA SSTA occurs during boreal spring, the TNA SSTA in boreal summer generates a stronger rainfall response in situ, which can further induce a significantly stronger zonal wind anomaly over the equatorial western Pacific via Kelvin and Rossby wave processes. The cause of a stronger precipitation response in boreal summer is attributed to the northward migration of the climatological Atlantic warm pool and the Inter‐Tropical Convergence Zone. Idealized Coupled General Circulation Model experiments further demonstrate that a persisting TNA SSTA forcing up to boreal summer is critical in conveying the TNA impact to subsequent ENSO evolutions in the Pacific. Plain Language Summary: Some recent studies have suggested that the sea surface temperature anomaly (SSTA) over the Tropical North Atlantic (TNA) from boreal spring can influence the El Niño‐Southern Oscillation (ENSO) evolution in the subsequent winter. Observational evidence shows that the TNA SSTA usually peaks during the springtime and decays during the summertime. Therefore, much attention is paid to the boreal spring when investigating the influence of the TNA SSTA on ENSO. However, although the summertime TNA SSTA is weaker than the springtime, due to the Atlantic mean state modulation, the summertime TNA SSTA can induce a stronger rainfall response locally, which can produce a more significant atmospheric response over the equatorial western Pacific to favor the development of the ENSO. Further numerical simulations suggest that the TNA SSTA forcing in boreal summer is crucial in inducing the cold SSTA over the Pacific in the subsequent winter, even though its amplitude is weaker than that in boreal spring. Our results indicate that a special attention should be paid to the amplitude of the summertime TNA forcing in addition to the peak time TNA forcing in boreal spring in real‐time ENSO forecast. Key Points: Tropical North Atlantic sea surface temperature anomaly (TNA SSTA) peaks in boreal spring but the TNA‐induced rainfall anomaly is stronger in boreal summerThe stronger summer TNA rainfall response to the weaker TNA SSTA is due to the northward shift of the Atlantic mean warm pool and Inter‐Tropical Convergence ZoneThe persisting TNA SSTA till boreal summer is crucial in conveying the impact of the TNA SSTA on El Niño‐Southern Oscillation in the subsequent winter [ABSTRACT FROM AUTHOR]

Thermal tides in the Martian atmosphere are analyzed using temperature profiles retrieved from nadir observations obtained by the TIRVIM Fourier‐spectrometer, part of the Atmospheric Chemistry Suite onboard the ExoMars Trace Gas Orbiter. The data is selected near the northern summer solstice at solar longitude (LS) 75°–105° of Martian Year 35. The observations have a full local time coverage, which enables analyses of daily temperature anomalies. The observed zonal mean temperature is lower by 4–6 K at ∼100 Pa, but higher toward the summer pole, compared to the Laboratoire de Météorologie Dynamique (LMD) Mars General Circulation Model (GCM). Wave mode decomposition shows dominant diurnal tide and important semi‐diurnal tide and diurnal Kelvin wave, with maximal amplitudes of 5, 3, and 2.5 K, respectively, from tens to hundreds of Pa. The results generally agree well with the LMD Mars GCM, but with noticeable earlier phases of diurnal (∼1 hr) and semi‐diurnal (∼3 hr) tides. Plain Language Summary: Unlike the Earth, daily temperature variation on Mars is as large as tens of degrees because of its thin atmosphere. The sunlight absorbed by the Martian surface and dust in the atmosphere leads to dramatic temperature increase in the lower atmosphere during daytime. Such large and regular changes can trigger temperature waves, and some modes of them can propagate into higher altitudes, where they become the major factor controlling the daily temperature variation. In this work, temperature profiles obtained using thermal‐infrared spectra are analyzed. Zonal mean temperature is compared with numerical simulations of the Martian atmosphere. Different types of the wave modes are computed through decomposition. Results from the observation agree well with model prediction when the observation mechanisms are taken into consideration. Estimation of the strength of these waves can be improved in the future with improved design of observation strategies. Key Points: Thermal tides in the Martian atmosphere are investigated using temperature profiles retrieved from TIRVIM nadir observationsDiurnal tide dominates daily temperature variations; semi‐diurnal tide and diurnal Kelvin wave are also importantObservations agree well with numerical simulations, but suggest phases of diurnal and semi‐diurnal tides earlier than predicted [ABSTRACT FROM AUTHOR]

Titan, the largest moon of Saturn, is characterized by gigantic linear dunes and an active dust cycle. Much like on Earth, these aeolian processes are caused by the wind‐driven saltation of surface grains. It is still unclear, however, how saltation on Titan can occur despite the typically weak surface winds and the potentially cohesive surface grains. Here, we explore the hypothesis that saltation on Titan may be sustained at lower wind speeds than previously thought, primarily through granular splash rather than aerodynamic lifting of surface grains. We propose a saltation mass flux parameterization for Titan and use it to quantify sediment transport with a general circulation model. The results suggest that Titan's prevailing circulation can generate highly intermittent yet significant saltation, with mass fluxes of the order of 104 kg m−1 year−1, and that Titan dunes may be formed primarily by fine grains, approximately 0.1 mm in size. Plain Language Summary: The Cassini‐Huygens mission has revealed that Titan's landscape evolution and dust cycle may be controlled by the wind‐driven transport of surface grains, known as saltation. It is still unclear, however, how saltation can occur on Titan despite the weak winds and the potential stickiness of the surface grains. Using a combination of experiments, theory, and modeling, we find that, like saltation on Mars, saltation on Titan can be sustained at much lower wind speeds than those required to lift grains from the surface. Accordingly, the prevailing weak winds on Titan may be capable of driving intermittent yet significant sediment transport. Key Points: Intermittent saltation on Titan can be sustained at lower wind speeds than previously thoughtThe grains forming Titan dunes may be primarily in the size range 0.05–0.1 mmYearly sediment transport rates on Titan are of the order of 104 kg m‐1 per Titan year [ABSTRACT FROM AUTHOR]

Previous studies have revealed the potential importance of salinity in El Niño‐Southern Oscillation (ENSO) asymmetry, but the responsible mechanisms remain unclear. Here, we investigate how the zonal structure of surface salinity anomalies affects ENSO intensity and asymmetry by modifying freshwater flux in ocean general circulation model simulations. Results show that the amplitudes of El Niño and La Niña are both highly sensitive to zonal patterns of salinity anomalies, with the strongest sea surface temperature change occurring when maximum salinity anomalies are located near 170°W. Furthermore, the effect of salinity anomalies in the central Pacific on El Niño warming is larger than those in the western Pacific on La Niña cooling. Thus, the asymmetric salinity anomalies strengthen the temperature asymmetry between El Niño and La Niña. Temperature budget analysis shows that vertical mixing and entrainment due to salinity‐induced changes in stratification are a major response to different zonal patterns of freshwater flux forcing. Plain Language Summary: Salinity has been suggested to play active roles in the development of ENSO events by affecting vertical stratification. Recent studies found that maximum salinity anomalies are located in the central equatorial Pacific (CEP) during El Niño and in the western equatorial Pacific (WEP) during La Niña. This pattern suggests a role for salinity in ENSO temperature asymmetry, but the underlying mechanisms are unclear. In this study, we conduct a series of sensitivity experiments to investigate salinity effects on ENSO intensity and asymmetry using an ocean general circulation model. Results show that intensities of both El Niño and La Niña are highly sensitive to the zonal patterns of salinity anomalies in the tropical Pacific. Salinity anomalies have the largest impacts on the development of ENSO events when they are located in the CEP near 170°W. Therefore, salinity anomalies in the CEP contribute to stronger warming during El Niño while those in the WEP lead to relatively weaker cooling during La Niña, which strengthens the sea surface temperature asymmetry between El Niño and La Niña. Our experimental results further show that changes in vertical mixing and entrainment are a major factor in the temperature response to salinity anomalies. Key Points: El Niño‐Southern Oscillation (ENSO) intensity is sensitive to the zonal location of sea surface salinity (SSS) anomalies and becomes strongest when they are located in the central PacificAsymmetric zonal structure of SSS anomalies strengthens the asymmetry of sea surface temperature (SST) anomalies between El Niño and La NiñaVertical mixing and entrainment dominate SSS‐related SST changes during ENSO cycle [ABSTRACT FROM AUTHOR]

Reproducing the Madden‐Julian Oscillation (MJO) remains a challenge in many climate models. This study compares the MJO simulation skills in 17 pairs of Coupled Model Intercomparison Project Phase 5 (CMIP5) and Coupled Model Intercomparison Project Phase 6 (CMIP6) simulations. Generally, the MJO characteristics are better reproduced in CMIP6, their inter‐model spreads are obviously reduced in CMIP6. However, most CMIP6 models still underestimate the frequency of MJO initiation over the Indian Ocean and the MJO amplitude, exaggerate the barrier effect of the Maritime Continent (MC) on MJO propagation. Models with lower MJO simulation skills in their CMIP5 versions show improvements in CMIP6, while other models tend to show degraded MJO simulation skills in CMIP6. The possible reasons for the apparent improvements of MJO simulations from CMIP5 to CMIP6 in six models was further explored. It was found that the enhanced land precipitation over the MC prior to the MJO convection entering this region is more obvious in CMIP6. Plain Language Summary: The Madden‐Julian Oscillation (MJO) influences global weather and climate as it moves eastward over the equatorial regions, playing an essential role in bridging the gap between the weather forecast and climate prediction. However, most of the general circulation models cannot realistically reproduce the MJO. This study explores whether the newly released Coupled Model Intercomparison Project Phase 6 (CMIP6) models can simulate the MJO better than CMIP5 using a method that identifies MJO events by tracking their precipitation. Through comparing 17 pairs of CMIP5 and CMIP6 simulations, we found that most CMIP6 models still struggle to simulate the MJO. They tend to underestimate the number of MJO events starting over the Indian Ocean, the strength of the MJO amplitude, and the number of MJO events that propagate through the Maritime Continent (MC). But the inter‐model spread in simulating the MJO is obviously reduced in CMIP6. Models that struggle more in simulating the MJO in their CMIP5 versions show more obvious improvements in simulating the MJO. The improved MJO simulation in CMIP6 is mainly reflected by the increased possibility of the MJO propagating through the MC. The possible reason is that the enhanced land precipitation before the MJO enter the MC is better reproduced in CMIP6. Key Points: The Madden‐Julian Oscillation (MJO) simulation skills in 17 pairs of CMIP5 and CMIP6 simulations were compared by tracking individual MJO eventsCMIP6 models still struggle to reproduce the observed MJO characteristics, but the multi‐model spreads are reducedModels with improved MJO simulation show enhanced land precipitation over the Maritime Continent ahead of the MJO convection [ABSTRACT FROM AUTHOR]

The Interdecadal Pacific Variability (IPV) has global climate effects but its decadal prediction is a challenge. Here, we use linear inverse models to study the optimal growth of the IPV and reveal important precursor patterns. We find that the optimal growth of the IPV exists in observations due to interference among various sea surface temperature (SST) decadal variations. Small SST anomalies extending from the northeastern subtropical Pacific to the central tropical Pacific, in concert with thermocline dynamics, can develop into a mature phase of the IPV after ∼3 years. Furthermore, the initial SST anomalies lag the Atlantic Multidecadal Variability (AMV) by up to a decade, suggesting the potential importance of the AMV in IPV decadal predictability. As climate models commonly underestimate the AMV trans‐basin effect, our study calls for more efforts on reducing the model bias to improve IPV decadal prediction. Plain Language Summary: The Interdecadal Pacific Variability (IPV), the leading decadal mode in the Pacific Ocean, can modulate global climate system with broad ecological and socioeconomic influences. However, as partly the residual of El Niño‐Southern Oscillation that shows predictability lower than 2 years, the IPV may be hard to be predicted several years ahead. Here, by using a method called optimal growth, we reveal that an ∼3‐year growth of IPV variance is associated with northeastern subtropical Pacific SST variability and ocean dynamics. Specifically, the Atlantic Multidecadal Variability (AMV), a main climate mode in the Atlantic Ocean, can provide potential decadal predictability to the optimal growth of the IPV. This trans‐basin effect is, however, underestimated in general circulation models that are commonly used for climate prediction. Hence, our study implies that reducing the model bias of the AMV trans‐basin effect will lead to more reliable IPV decadal prediction. Key Points: The Interdecadal Pacific Variability (IPV) exhibits ∼3‐year optimal growth, a time length beyond the upper bound of El Niño‐Southern Oscillation predictabilityThe optimal growth of the IPV is associated with northeastern subtropical sea surface temperature variability and pan‐tropical Pacific thermocline dynamicsThe Atlantic Multidecadal Variability leads the optimal growth of the IPV by up to a decade, an important factor for IPV decadal prediction [ABSTRACT FROM AUTHOR]

Sea surface height (SSH) along the west coast of Australia is key to local climate and is strongly forced by remote surface wind variability related to El Niño Southern Oscillation (ENSO) in the tropical Pacific Ocean. This study provides a method to predict interannual variability in SSH along the west coast of Australia using a simple 1.5‐layer dynamical ocean model forced by a statistical atmospheric model for ENSO‐related winds. The model has realistic coastlines and is driven by reanalysis surface winds regressed onto an ENSO index. The model when run in hindcast mode to predict past variability can simulate tide gauge observations at Fremantle along the west coast of Australia up to 13 months in advance, which outperforms persistence. We conclude that this methodology can be useful as a baseline for gauging the performance of more sophisticated forecast models for predicting SSH variations along the west coast of Australia. Plain Language Summary: Sea surface height (SSH) along the west coast of Australia is key to regional climate and is strongly forced by remote surface wind variability related to El Niño Southern Oscillation (ENSO) in the tropical Pacific Ocean. Previous studies predicted interannual variability in SSH in this region using sophisticated ocean‐atmosphere coupled general circulation models, but their ocean models had coarse horizontal resolution, required to reduce computational burden. This study provides a much simpler method to predict SSH variability along the west coast of Australia using a simple ocean dynamical model with realistic coastlines forced by ENSO‐related atmospheric winds. Our model, run in hindcast mode to predict past SSH variability, is able to simulate SSH anomalies along the west coast of Australia up to 13 months in advance. A true forecast system to predict future variations would also require prediction of ENSO. However, this methodology can be useful as a baseline for gauging the performance of more sophisticated model forecast systems. Key Points: Interannual variability in sea level along the west Australian coast can be predicted up to 13 months in advance using a simple ocean modelTo illustrate, the model is run in hindcast mode forced remotely by Pacific surface winds related to El Niño Southern OscillationModel hindcasts generally outperform persistence forecasts in terms of anomaly correlation and root‐mean‐squared differences [ABSTRACT FROM AUTHOR]

A general circulation model is used to study the interaction between parameterized gravity waves (GWs) and large‐scale Kelvin waves in the tropical stratosphere. The simulation shows that Kelvin waves with substantial amplitudes (∼10 m s−1) can significantly affect the distribution of GW drag by modulating the local shear. Furthermore, this effect is localized to regions above strong convective organizations that generate large‐amplitude GWs, so that at a given altitude it occurs selectively in a certain phase of Kelvin waves. Accordingly, this effect also contributes to the zonal‐mean GW drag, which is large in the middle stratosphere during the phase transition of the quasi‐biennial oscillation (QBO). Furthermore, we detect an enhancement of Kelvin‐wave momentum flux due to GW drag modulated by Kelvin waves. The result implies an importance of GW dynamics coupled to Kelvin waves in the QBO progression. Plain Language Summary: The variability of the tropical atmosphere at altitudes of about 18–40 km is dominated by a large‐amplitude long‐term oscillation of wind, the quasi‐biennial oscillation, which has a broad impact on the climate and seasonal forecasting. This oscillation is known to be driven by various types of atmospheric waves with multiple spatial scales. Using a numerical model, this study reports a process of interaction between those waves on different scales, which has not been illuminated before. The result implies a potential importance of this process in the progression of the quasi‐biennial oscillation. Proper model representations of these multiscale waves and tropical convection are required to simulate this process. Key Points: Kelvin waves affect the longitudinal and vertical distribution of parameterized gravity‐wave drag in the stratosphere significantlyThis effect can make contribution to the zonal mean of gravity‐wave drag, thereby affecting the quasi‐biennial oscillation progressionGravity‐wave drag modulated by Kelvin waves also alters the Kelvin‐wave momentum flux in the middle stratosphere [ABSTRACT FROM AUTHOR]

Quantifying effective radiative forcing due to aerosol‐cloud interactions (EERFACI) remains a largely uncertain process, and the magnitude remains unconstrained in general circulation models. Previous studies focus on the magnitude of ERFACI arising from all cloud types, or examine it in the framework of dynamical regimes. Aerosol forcing due to aerosol‐cloud interactions in the HadGEM3‐GA7.1 global climate model is decomposed into several global observational cloud regimes. Regimes are assigned to model gridboxes and forcing due to aerosol‐cloud interactions is calculated on a regime‐by‐regime basis with a 20‐year averaging period. Patterns of regime occurrence are in good agreement with satellite observations. ERFACI is then further decomposed into three terms, representing radiative changes within a given regime, transitions between different cloud regimes, and nonlinear effects. The total global mean ERFACI is −1.03 Wm−2. When decomposed, simulated ERFACI is greatest in the thick stratocumulus regime (−0.51 Wm−2). Plain Language Summary: The effect of anthropogenic aerosol emissions on clouds is highly uncertain in climate models. Many previous attempts to reduce this uncertainty have focused on examining all cloud types as a whole. This work sets out a framework to examine one measure of aerosol‐cloud interactions when the effect is split by different cloud types. This framework is applied to the HadGEM3‐GA7.1 climate model. It is found that thick stratocumulus clouds exhibit the strongest aerosol‐cloud interactions, especially those found off the west coast of both North and South America, and West Africa. It is hoped that this will lead to a greater understanding of how these interactions manifest themselves in different cloud types, and that this methodology will promote the use of constraints on specific cloud types, to provide potentially greater reductions in the aforementioned uncertainty. Key Points: The majority of effective radiative forcing in HadGEM3‐GA7.1 comes from stratocumulus cloudsForcing from marine stratocumulus clouds is highly sensitive to aerosol perturbationsDecomposing radiative forcing by cloud regimes can be a useful technique to gain insights into climate model predictions [ABSTRACT FROM AUTHOR]

A better understanding of the many interacting processes governing the evaluation of ice in natural clouds is required to improve the representation of ice clouds in global circulation models. Recent studies suggest a dominant role of vapor growth processes in determining the temperature dependence of cloud top ice sizes and shapes. Using airborne cloud remote sensing along with reanalysis data, here we show that observed cloud top ice effective radii and estimated normalized growth rates at cloud top highly correlate with an approximately linear relationship, which is consistent with a conceptual model also presented. Furthermore, significant differences in crystal shape characteristics and scattering asymmetry parameters are found between sub‐ and super‐saturated cloud tops over ocean, although not over land. These results provide valuable observational targets for studying ice formation and evolution processes using models, while also helping interpretation of satellite observations of ice microphysical properties at cloud tops. Plain Language Summary: The sizes and shapes of ice crystals in cold clouds influence how these clouds evolve and how much sunlight they reflect. Ice crystal shapes and sizes are affected by numerous interacting physical processes. A better understanding on the relative importance of each of these processes is key to improve the representation of ice clouds in climate models. Recent work suggests that the variation of ice crystal shapes and sizes is largely determined by the relatively simple process of ice crystals growing directly from water vapor. Here, we use data from a remote sensor mounted on a high‐altitude aircraft to infer information about ice crystal sizes and shapes at the tops of convective clouds as a function of top height. By combining this data with water vapor information from a model, we show that the ice crystal sizes highly correlate with ice growth rates predicted by a simple conceptual model based on ice growing directly from water vapor. Furthermore, we find that ice crystal shapes differ significantly in tops where vapor growth is expected compared to where ice is expected to sublimate. These results can help improve ice cloud modeling and the interpretation of satellite observations of ice clouds. Key Points: Cloud top ice effective radii are shown to highly correlate with normalized ice vapor growth rates at cloud top conditionsOver ocean, observed cloud‐top crystal properties differ significantly between sub‐ and supersaturated conditionsA conceptual model based on basic growth theory and ice properties is consistent with these observations [ABSTRACT FROM AUTHOR]

Theoretical studies have shown that the solar eclipse can have significant impacts on the thermospheric mass density, which, however, has not been confirmed from the observational perspective. In this study, we present direct observations of the thermospheric density responses to three solar eclipses based on the measurements of Gravity Recovery and Climate Experiment (GRACE) and Gravity field and steady state Ocean Circulation Explorer (GOCE). It was observed that the eclipses induced about 20% and 25% density depletions at GRACE altitudes (360 and 480 km, respectively) and about 10% depletions at GOCE altitudes (∼270 km). Moreover, the eclipse could generate large‐scale traveling atmospheric disturbances (TADs), which propagate globally even from the duskside to the dawnside after the eclipse ended. Those thermospheric responses could be generally reproduced by Thermosphere Ionosphere Electrodynamics General Circulation Model (TIEGCM). However, the simulated densities recover more rapidly than the observations at the duskside. This study provides observational evidence to validate the results from theoretical models and further bring insights into the mechanism of eclipse effects on the ionosphere‐thermosphere system. Plain Language Summary: A solar eclipse is a celestial event in which the Sun is obscured by the moon. As a result, the reduced solar radiation cast by the shadow leads to a decrease in the ionization rate and temperature of the upper atmosphere. Nevertheless, the eclipse‐effect on the neutral atmosphere was rarely studied in detail due to a lack of measurements. In this work, the first direct observations of the eclipse‐effect on the neutral density from multiple LEO satellite measurements were presented. It was found that the eclipse induced not just a localized neutral density depletion, but even a large‐scale density perturbation that propagated globally from the dayside to the night sector after the eclipse ended. This study would contribute to improving our understanding of the ionosphere‐thermosphere coupling process, and also the prediction of thermospheric density in the upper atmosphere and the associated drag force of LEO satellites. Key Points: Direct observations of the thermospheric mass densities in response to solar eclipses were presented based on Gravity Recovery and Climate Experiment (GRACE) and Gravity field and steady state Ocean Circulation Explorer (GOCE) measurementsThe eclipse‐induced traveling atmospheric disturbances (TADs) were observed to propagate globally from the day side to the night side after the eclipse endedThe simulations generally agree with the observations except a more rapid density recovery at dusk side [ABSTRACT FROM AUTHOR]

Due to limited resolution and inaccurate physical parameterizations, weather and climate models consistently develop biases compared to the observed atmosphere. Using the FV3GFS model at coarse resolution, we propose a method of machine learning corrective tendencies from a hindcast simulation nudged toward observational analysis. We show that a random forest can predict the nudging tendencies from this hindcast simulation with moderate skill using only the model state as input. This random forest is then coupled to FV3GFS, adding corrective tendencies of temperature, specific humidity and horizontal winds at each timestep. The coupled model shows no signs of instability in year‐long simulations and has significant reductions in short‐term forecast error for 500 hPa height, surface pressure and near‐surface temperature. Furthermore, the root mean square error of the annual‐mean precipitation is reduced by about 20%. Biases of other variables remain similar or in some cases, like upper‐atmospheric temperature, increase in the year‐long simulations. Plain Language Summary: After initialization from a realistic snapshot of the atmosphere, weather and climate models inevitably develop prediction errors compared to the real world. This decreases the usefulness of forecasts. These errors arise from the coarse resolution of the numerical models and from the uncertain treatment of small‐scale processes. We propose a method to reduce these errors by training a machine learning model to correct for them as the atmospheric model proceeds. We show that a random forest can make reasonably skillful predictions of the required correction using a snapshot of the model state as input. When we make a forecast with the machine‐learning corrected model, equally skillful predictions of important midtropospheric and surface variables are possible half‐a‐day to a day further into the future. The pattern of precipitation predicted by the machine learning corrected model is also more realistic, with a decrease in excessive rainfall over high mountains. On the other hand, the corrected model develops larger errors in temperature in the high latitudes, particularly in the lower stratosphere. Key Points: Nudging an atmospheric model toward observations is a good way to estimate state‐dependent biasesMachine learning of state‐dependent biases improves hindcast skill of a coarse‐resolution general circulation model (GCM)Bias‐corrected year‐long simulations are stable and reduce time‐mean precipitation pattern errors [ABSTRACT FROM AUTHOR]

Possible roles of large‐scale precipitation on model simulations of the Madden‐Julian Oscillation (MJO) were investigated using the Large‐scale Precipitation Tracking (LPT) method. Individual LPT systems and eastward propagating MJO LPT systems were identified in both observations and 25 general circulation model (GCM) simulations. LPT systems show dominant eastward propagation over the Indian Ocean in the observation, whereas LPT systems are too stationary in GCM simulations. The MJO statistical signals in the model simulations are represented by the occurence frequencies of LPT systems with a size of ∼4–9 × 106 km2 (∼20–30° in longitude and latitude) and a strength of ∼15–18 mm d−1. Growth rate in size of LPT systems in early stage determines the size of LPT systems, which differentiates the MJO statistical signals among the GCM simulations. Comprehensive diagnostics of MJO simulations in GCMs should include both individual LPT systems as essential elements and the MJO statistical signals. Plain Language Summary: The Madden‐Julian Oscillation (MJO) is the dominant mode of intraseasonal variabilities in the tropics and represents a major source of subseasonal predictability. A distinct feature of the MJO is its eastward propagating large‐scale precipitating systems from the tropical Indian Ocean to the western‐central Pacific. However, this feature is not well‐reproduced by most general circulation models (GCMs). In this study, we explore possible reasons for why GCMs struggle to simulate the MJO eastward propagation by investing the Large‐scale Precipitation Tracking (LPT) systems. The results suggest that the problems of models in simulating the MJO are rooted in the LPT systems. The model capability of producing sufficient LPT systems that are large in size (∼4–9 × 106 km2) and strong in strength (∼15–18 mm d−1) is essential for simulating the MJO. It is particularly important for models to capture the growth rate in size of LPT systems within the first several days after their initiation. Key Points: Madden‐Julian Oscillation (MJO) statistical signals in general circulation model simulations depend on the size of large‐scale precipitation tracking (LPT) systemsGrowth rate in the size of LPT systems at early stage determines the model simulated MJO statistical signalsComprehensive diagnostics of MJO simulations should include LPT systems as essential elements of the MJO [ABSTRACT FROM AUTHOR]

A moist General Circulation Model is used to investigate the forcing of the Asian monsoon and the associated upper level anticyclone by land‐sea contrast, net horizontal oceanic heat transport, and topography. The monsoonal pattern is not simply the linear additive sum of the response to each forcing; only when all three forcings are included simultaneously does the monsoonal circulation extend westward to India. This nonadditivity impacts the location of the upper level anticyclone, which is shifted eastward and weaker if the forcings are imposed individually. Sahelian precipitation, and also austral summer precipitation over Australia, southern Africa, and South America, are likewise stronger if all forcings are imposed simultaneously. The source of the nonlinearity can be diagnosed using gross moist stability, but appears inconsistent with the land‐sea breeze paradigm. This non‐additivity implies that the question of which forcing is most important may be ill‐posed in many regions. Plain Language Summary: Monsoons dominate the climate in many regions of the tropics and subtropics, and are characterized by rainy summer and drier winter seasons. This rainfall is crucial for agriculture, among other societal implications, in heavily populated regions of the world. The processes leading to regional confinement of the monsoons are investigated using an intermediate complexity moist General Circulation Model. We find that a linear perspective cannot account for the monsoons; only when land‐sea contrast, orography, and ocean heat transport are included simultaneously does the monsoonal circulation extend westward to India. A similar nonlinearity is evident for Sahelian precipitation, and also for austral summer precipitation over Australia, southern Africa, and South America. Key Points: Monsoons are due to a non‐additive response to three forcings: land‐sea contrast, orography, and ocean heat transportThe non‐additivity in precipitation leads to a non‐additive response of the upper level stationary waves and Asian monsoon anticycloneGross moist stability can account for this effect, but not the land‐sea breeze paradigm [ABSTRACT FROM AUTHOR]

Bias correction of General Circulation Model (GCM) is now an essential part of climate change studies. However, the climate change trend has been overlooked in majority of bias correction approaches. Here, a novel signal processing‐based approach for correcting systematic biases in the time‐varying trend of GCM simulations is proposed. The approach corrects for systematic deviations in spectral attributes of raw GCM simulations using discrete wavelet transforms. The order one and two moments of the underlying trend represented by the lowest frequency of wavelet component are corrected to ensure continuity in the corrected time series from the current to the future simulation period. The approach is applied to correct two data sets that exhibit opposite time‐varying trends representing the global mean sea level (GMSL) and the Arctic sea‐ice extent. Results indicate that bias in trend is corrected, while continuity in time and observed variability at all frequencies in current climate simulations are maintained. Plain Language Summary: GCMs are an essential tool to assess climate change impacts. However, they exhibit systematic biases which restrict their direct use. A wide range of alternatives for correcting biases has been proposed. Most such approaches are unable to correct biases in trend and variability attributes together. When a variability correction is applied, it reduces biases in trend, however, introduces a discontinuity in trend between current and future climate bias‐corrected simulations. We present an approach for correcting systematic biases in trend and variability to ensure continuity of GCM simulations from the current to the future. The application of our approach to two data sets exhibiting opposite trends ‐ the GMSL and the Arctic sea ice extent ‐ shows a remarkable improvement that maintains continuity overtime, corrects bias in trends, and preserves observed variability across the frequency spectrum in current period GCM simulations. Key Points: Tradition alternatives for bias correction distort continuity in corrected seriesA discrete wavelet transform based signal processing alternative for correcting trend and variability bias is proposedThe approach is demonstrated to correct trends in global mean sea level and Arctic sea ice extent simulations for the future [ABSTRACT FROM AUTHOR]

Many of the current, Coupled Model Intercomparison Project 6 (CMIP6), General Circulation Models (GCMs) show climate sensitivity higher than currently accepted uncertainty ranges. There is a weak correlation between increases in vertical resolution and in climate sensitivity from CMIP5. In particular, the MO Hadley Centre GCM's vertical resolution has more than doubled, and its climate sensitivity has also increased substantially. We therefore compare estimates of climate sensitivity from the CMIP6 model HadGEM3‐GC3.1‐LL, with 85 levels, and a version with 242 levels. This is far higher resolution than in any previously published simulations with a mainstream GCM, though still less than many scales important for clouds. The climate sensitivity and feedbacks, including the cloud feedback, change little. This suggests that vertical resolution did not drive recent increases in GCM climate sensitivity, though this result should be further tested in other GCMs and over a broader range of resolutions. Plain Language Summary: "Climate sensitivity" is how much climate is warmed, in the global and time average, by more CO2 in the air, largely from burning fossil fuels. However, it remains very uncertain. General Circulation Models (GCMs) are our most detailed and physically based models of climate, widely used in many sorts of study of possible climate change. "All models are wrong, but some are useful"—their complexity can make it hard to understand and so assess their behavior. They also have to approximate many physical processes on smaller scales—particularly cloud. More recent GCMs tend to have higher climate sensitivity, many higher than was ever thought likely. Cloud processes seem largely responsible. A possible cause is increased vertical resolution (calculations being done on more levels through the atmosphere) in the newer GCMs. There is a correlation between increased vertical resolution and increased climate sensitivity, but this could be by chance. We have therefore compared one new‐generation GCM with its standard vertical resolution and with 3 times higher (considerably higher than any previously published mainstream GCM work). The climate sensitivity barely changes, and the processes involved, including cloud processes, are clearly working almost identically. But other GCMs might be quite different. Key Points: Many Coupled Model Intercomparison Project 6 (CMIP6) General Circulation Models (GCMs) have climate sensitivities larger than the Intergovernmental Panel on Climate Change uncertainty range or other assessments, largely thanks to cloud feedbacksThis increase in sensitivity is correlated with an increase in vertical resolution—particularly important for cloud processesHowever, tripling the vertical resolution in one CMIP6 GCM, we found that climate sensitivity and feedbacks barely change [ABSTRACT FROM AUTHOR]

We report on the direct measurements of zonal winds around 80 km altitude during the 2018 planet-encircling dust event (PEDE) by infrared (IR) heterodyne spectroscopy. The observed Doppler shifts assume intense retrograde (easterly) winds (208 ± 17 m s-1, 159 ± 20 m s-1, 211 ± 20 m s-1 on June 21, June 27, August 31, 2018, respectively) in the equatorial region during the 2018 PEDE. This is significantly stronger than those during non-storm conditions reported by the previous study (Sonnabend et al., 2012, https://doi.org/10.1016/j.icarus.2011.11.009). The substantial retrograde wind during the PEDE is qualitatively consistent with the predictions by the Mars general circulation models (MGCMs), however, the observed wind on 31, August, are of a larger magnitude. We evaluated the mechanism of acceleration using the output from a high-resolution MGCM. We find out that the stronger winds are related to strengthening the meridional circulation across the equator and forcing by gravity waves. Plain Language Summary Planet-encircling dust events (PEDE) are spectacular phenomena that occasionally occur in the atmosphere of Mars. The atmospheric circulation on Mars is strongly influenced by dust events, which affect not only the lower atmosphere, but also the mesosphere. The ground-based mid-IR heterodyne spectroscopy was able to observe zonal winds around 80 km during the 2018 PEDE. We found intense retrograde (easterly) winds at the equator, which were much larger than those during non-storm conditions reported by the previous study. This study suggests that the intense retrograde winds during the PEDE were likely caused by the enhanced meridional circulation and smallscale gravity waves. [ABSTRACT FROM AUTHOR]

Given uncertainty in the processes involved in polar amplification, elucidating the role of poleward heat and moisture transport is crucial. The Polar Amplification Model Intercomparison Project (PAMIP) permits robust separation of the effects of sea ice loss from sea surface warming under climate change. We utilize a moist isentropic circulation framework that accounts for moisture transport, condensation, and eddy transport, in order to analyze the circulation connecting the mid‐latitudes and the Arctic. In PAMIP's atmospheric general circulation model experiments, prescribed sea ice loss reduces poleward heat transport (PHT) by warming the returning moist isentropic circulation at high latitudes, while prescribed warming of the ocean surface increases PHT by strengthening the moist isentropic circulation. Inter‐model spread of PHT into the Arctic reflects the tug‐of‐war between sea‐ice and surface‐warming effects. Plain Language Summary: A major conundrum in current climate science is to understand what Arctic changes imply for the climate and environment in mid‐latitude regions. The Polar Amplification Model Intercomparison Project (PAMIP) designed a set of climate model experiments to specifically answer this question in a carefully designed, idealized framework. PAMIP's approach is to separate historic and projected climate change into parts associated with Arctic sea ice loss and ocean surface warming and investigate how these two contributions can influence the atmosphere. To isolate these effects, only models can be used, because, in reality, sea ice loss and ocean surface warming are strongly linked together. This letter focuses on what the PAMIP experiments imply for the transport and redistribution of heat and moisture in the atmosphere. In PAMIP, we learn that Arctic sea ice loss causes the atmosphere to reduce the transport of dry and cold air away from the Arctic while ocean warming causes more transport of moist warm air toward the Arctic. These two effects are in a tug‐of‐war, suggesting that climate change can cause a mix of competing impacts on the global energy transport from the tropics to the Arctic. Key Points: Sea ice loss exports static energy from the Arctic by warming the equatorward branch of the global mass circulationSea surface warming imports static energy into the Arctic by increasing the mid‐latitude mass transport, overwhelming the sea ice effectThere is more spread amongst models for the effect of sea‐surface warming than for sea ice loss [ABSTRACT FROM AUTHOR]