Search

Stratification and turbulent mixing have an immense impact on biogeochemical regimes and ecosystem dynamics in stratified large lakes. This study investigates the physical properties of the epi‐ and metalimnion of Lake Biwa (Japan), focusing on the persistent vertical diffusive fluxes due to turbulent mixing in the lower metalimnion and their effects on upward nitrate transport. We conducted 24‐h observations at an offshore station in the summer for three consecutive years to examine the temporal and vertical variations of stratification and turbulence. A mooring system provided long‐term data on stratification and current velocity, while thermal profiles along two offshore transects were collected to investigate lateral changes. Our findings revealed strong stratification in the upper metalimnion, where vertical diffusive fluxes were essentially suppressed. Distinct turbulent mixing layers were identified near the water surface and within the moderately stratified lower metalimnion. Field data and numerical model suggested that the turbulence in the lower metalimnion was driven by shear instability, straining, and/or wave–wave interactions linked with the persistent internal waves that occur even during weak winds. Vertical eddy diffusivity of > 10−5 m2 s−1 in the lower metalimnion was associated with rather strong turbulence, which has not been reported in other large lakes. The elevated turbulence resulted in an upward nitrate flux of 0.2 mmol N m−2 d−1 across the lower metalimnion, indicating that the upward nutrient transport could support primary productivity and play an important ecological role in deep stratified lakes. [ABSTRACT FROM AUTHOR]

Extratropical disturbances are known to impact the genesis and intensification of Mixed Rossby‐Gravity waves (MRGW) in the Western Hemisphere (WH). The study provides observational evidence supporting the wave resonance (WR) theory which attempts to explain the intensification of MRGW by extratropical forcing. Wavenumber‐frequency cospectral analysis and a bulk measure of growth of MRGW estimated using reanalysis data reveal that the extratropical forcing manifested in the form of eddy momentum flux convergence can create eddy kinetic energy (EKE) and aid the intensification of MRGW via WR mechanism during boreal winter season. However, the WR mechanism does not hold during boreal summer season as the extratropical forcing tends to dampen the MRGW. The analysis also reveals that the Doppler‐shifted eastward propagating MRGW in the WH during boreal winter season are not maintained by extratropical forcing, marking another highlight of this study. Plain Language Summary: Mixed Rossby‐Gravity waves (MRGW) are a key component of tropical dynamics and extratropical forcing has been considered as an important factor in governing the growth of MRGW. Wave resonance (WR) theory, as proposed by previous theoretical studies, offers a compelling framework for understanding how extratropical forcing influences MRGW. This study seeks to provide observational evidence supporting the intensification of MRGW by extratropical forcing using the WR framework. Analyses conducted using reanalysis data show that the interaction between MRGW and extratropical forcing generates eddy kinetic energy, which intensifies the MRGW during boreal winter. In contrast, this interaction leads to the attenuation of MRGW during boreal summer season, highlighting the seasonal variability in these dynamics. Interestingly, while Doppler‐shifted eastward propagating MRGW are observed over the Western Hemisphere during boreal winter season, their presence cannot be attributed to extratropical forcing. Overall, this study underscores the importance of extratropical forcing as a crucial factor in modulating the MRGW. Key Points: The study provides observational evidences supporting the growth of Mixed Rossby‐Gravity waves by tropical‐extratropical wave resonanceExtratropical eddy momentum forcing enhances Mixed Rossby‐Gravity wave growth in boreal winter while dampens its growth in boreal summerExtratropical eddy momentum forcing does not explain the existence of Doppler shifted eastward propagating Mixed Rossby‐Gravity waves [ABSTRACT FROM AUTHOR]

The meridional displacements of the East Asian westerly jet (EAJ) exhibit remarkable interannual variability characteristics, significantly modulating the weather and climate over East Asia. Our study aims to refine the thermal‐driven (angular momentum transport) and dynamically driven (atmospheric eddy activities) processes that dominate the interannual meridional motion of the wintertime EAJ. We employ the recently proposed three‐pattern decomposition of global atmospheric circulation (3P‐DGAC) theory to decompose the zonal momentum equation for the purpose of diagnosing the zonal momentum budget of the EAJ from three‐dimensional (3D) horizontal, meridional and zonal circulation perspectives. Results indicate that, in addition to the widely recognised driving mechanisms of angular momentum transported by thermal direct meridional Hadley circulation and horizontal eddy momentum flux convergence, the previously neglected role of local zonal circulation in transporting angular momentum significantly impacts the meridional shift of EAJ. The uneven accumulation of angular momentum transported by asymmetric zonal circulations emerges on the northern and southern sides of EAJ axis, causing an abnormal meridional displacement of EAJ. Notably, the local zonal circulation rising from the Tibetan Plateau and descending across the North Pacific Ocean transported angular momentum to the core and downstream regions of EAJ, thereby significantly accelerating zonal winds and pushing the EAJ northward. Further investigation into the potential mechanisms suggests that anomalous snow depth on the southern Tibetan Plateau is the main factor causing abnormal local zonal circulation. Our study addresses the deficiency in traditional two‐dimensional (2D) circulation decomposition methods that neglect the significant role of zonal circulation in the thermal‐driven process of EAJ, complements the understanding of 3D angular momentum transport mechanisms and reveals potential nonlinear synergies of 3D circulations related to the interannual meridional displacement of EAJ. [ABSTRACT FROM AUTHOR]

This study investigates the causes of shifts in the subsiding edge of the boreal winter Hadley cell (HC) in response to a comprehensive treatment of ocean surface albedo (OSA) in the fully coupled CESM2. The focus is on an in‐depth understanding of the atmospheric dynamical processes that influence the HC subsiding edge. Two sets of experiments were performed: one utilizing the default OSA, and the other employing the comprehensive OSA that accounts for realistic physical mechanisms. The results show that implementing the comprehensive OSA simulates an El Niño‐like warming pattern in reference to the default experiment, which leads to an HC contraction. Examination of zonal mean momentum dynamics in the upper troposphere reveals that variations in meridional winds, crucial for determining the HC extent, are primarily driven by the differences in the horizontal eddy momentum flux derivative. The findings indicate that the equatorward shift in meridional temperature gradients enhances subtropical zonal winds and baroclinicity along their equatorial flanks, amplifying equatorward‐propagating Rossby waves. This, in turn, alters the eddy momentum flux, reshaping the pattern of the derivatives of horizontal eddy momentum flux, constraining meridional winds, and resulting in the equatorward movement of the HC subsiding edge. A scaling theory further supports the results of the HC contraction, showing that the increased subtropical zonal winds and the equatorward shift of the Intertropical Convergence Zone (ITCZ) elevate the atmospheric angular momentum and eventually limit the expansion of the HC. Plain Language Summary: The Hadley cell (HC) is a large‐scale tropical circulation system that exerts a substantial influence on global and regional climates. However, it is necessary to further explain the mechanisms that control the HC edge. This study investigates how the HC descending edge shifts when a comprehensive ocean surface albedo (OSA), including more realistic physical processes, is used in a fully coupled climate model. Two sets of simulations were conducted: one using the default OSA, which neglects certain physical processes, and the other using the comprehensive OSA. The comprehensive OSA experiment simulated an El Niño‐like warming climate in contrast to the default simulation, with equatorward movement of the HC edge. The present study finds that the equatorward shift in the air meridional temperature gradient results in the intensification of the subtropical zonal winds and baroclinic instability along their equatorial flanks, enhancing equatorward Rossby wave activities and affecting the pattern of the horizontal eddy momentum flux. This constrains the meridional winds, causing the HC edge to move equatorward. A scaling theory supports these findings by showing that the stronger subtropical winds and the equatorward shift of the Intertropical Convergence Zone (ITCZ) increase the atmospheric angular momentum and subsequently prevent the HC expanding. Key Points: The El Niño‐like warming pattern due to considering ocean surface albedo physics comprehensively is demonstratedEquatorward shift in temperature gradients alters eddy momentum flux, limits meridional winds, and contracts the Hadley Cell (HC)A scaling theory supports HC contraction with stronger subtropical zonal winds, enhancing angular momentum and limiting its extent [ABSTRACT FROM AUTHOR]

Rewetting peatlands is required to limit carbon dioxide (CO2) emissions, however, raising the groundwater level (GWL) will strongly increase the chance of methane (CH4) emissions which has a higher radiative forcing than CO2. Data sets of CH4 from different rewetting strategies and natural systems are scarce, and quantification and an understanding of the main drivers of CH4 emissions are needed to make effective peatland rewetting decisions. We present a large data set of CH4 fluxes (FCH4) measured across 16 sites with eddy covariance on Dutch peatlands. Sites were classified into six land uses, which also determined their vegetation and GWL range. We investigated the principal drivers of emissions and gapfilled the data using machine learning (ML) to derive annual totals. In addition, Shapley values were used to understand the importance of drivers to ML model predictions. The data showed the typical controls of FCH4 where temperature and the GWL were the dominant factors, however, some relationships were dependent on land use and the vegetation present. There was a clear average increase in FCH4 with increasing GWLs, with the highest emissions occurring at GWLs near the surface. Soil temperature was the single most important predictor for ML gapfilling but the Shapley values revealed the multi‐driver dependency of FCH4. Mean annual FCH4 totals across all land uses ranged from 90 ± 11 to 632 ± 65 kg CH4 ha−1 year−1 and were on average highest for semi‐natural land uses, followed by paludiculture, lake, wet grassland and pasture with water infiltration system. The mean annual flux was strongly correlated with the mean annual GWL (R2 = 0.80). The greenhouse gas balance of our sites still needs to be estimated to determine the net climate impact, however, our results indicate that considerable rates of CO2 uptake and long‐term storage are required to fully offset the emissions of CH4 from land uses with high GWLs. [ABSTRACT FROM AUTHOR]

Roll vortices can have a significant influence on the exchanges of momentum, sensible heat and moisture throughout the boundary layer. They have been shown to reinforce air‐sea interactions under strong wind conditions. This raises the question of how air‐sea exchanges can, in turn, affect the roll vortices. However, representing surface turbulent fluxes during extreme wind conditions is a major challenge in numerical weather prediction and can lead to large uncertainties in surface wind speed. The sensitivity of rolls to different representations of surface fluxes is investigated using large eddy simulations. The study focuses on Mediterranean windstorm Adrian, where rolls are responsible for the transport of strong winds to the surface. Considering the effects of sea spray increases surface heat fluxes and significantly influences the roll morphology. The rolls become narrower and extend over a greater height, while the downward transport of momentum is intensified and results in higher wind speed near the surface. Roll vortices vanish within a few minutes in the absence of momentum fluxes, which maintain the wind shear necessary for their organization. They also quickly weaken without sensible heat fluxes, which sustain the near‐neutral stratification required for their development. In contrast, latent heat fluxes play a minor role. These findings emphasize the necessity of precisely representing the processes occurring at the air‐sea interface, which do not only affect the thermodynamic surface conditions but also the vertical transport of momentum within the windstorm. Plain Language Summary: Roll vortices are coherent and organized swirls that are often observed in the atmospheric boundary layer (the lowest part of the atmosphere). They are important because they can carry strong winds from higher in the atmosphere through the boundary layer toward the surface. For this study, roll vortices are simulated at high spatial resolution in a numerical model for a Mediterranean windstorm. The existence of roll vortices requires significant exchange of both heat and momentum between the sea and the atmosphere. The morphology of roll vortices is highly dependent on air‐sea exchanges, which can be difficult to represent in numerical models under strong wind conditions. In particular, the evaporation of water droplets ejected by strong wind action on the waves may reinforce heat exchanges. When this effect is taken into account, the roll vortices are stronger, taller and narrower. Consequently, the wind speed increases near the surface. These findings highlight the need to better understand the interactions at the air‐sea interface under windstorm conditions, because they act on the formation of damaging winds. Key Points: Large eddy simulations reveal the existence of roll vortices transporting strong winds to the surface in a Mediterranean windstormIncluding the effects of sea spray in surface sensible heat fluxes reduces the size of rolls and increases momentum transportThe results may constrain the representation of turbulent fluxes at the air‐sea interface, which is uncertain under strong wind conditions [ABSTRACT FROM AUTHOR]

Atmospheric turbulence over the Arctic sea‐ice surface has been understudied due to the lack of observational data. In this study, we focus on the turbulence kinetic energy (TKE) over sea ice and distinguish its two different vertical structures, the "Surface" type and the "Elevated" type, using observations during the Multidisciplinary drifting Observatory for the Study of Arctic Climate expedition (MOSAiC). The "Surface" type has the maximum TKE near the surface (at 2 m), while the "Elevated" type has the maximum TKE at a higher level (6 m). The TKE budget analysis indicates that the "Elevated" type is caused by the increased shear production of TKE at 6 m. In addition, spectral analysis reveals that the contribution to TKE by horizontal large eddies is enhanced in the "Elevated" type. Finally, how the vertical structure of TKE affects the parameterization of turbulent momentum flux is discussed. Plain Language Summary: In recent years, the Arctic near‐surface temperature has increased at a rate that is 3–4 times faster than the global average, which has significant impacts on the global climate. Explaining this phenomenon and predicting future scenarios are urgently needed. Turbulent motions within the Arctic atmospheric boundary layer over the sea‐ice surface play an important role in determining near‐surface temperature variations, but these turbulent motions and their impacts are not thoroughly understood. To enhance our understanding of the turbulent characteristics of the Arctic boundary layer, the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) was conducted in the central Arctic and collected a wealth of data. Based on the MOSAiC observational data, we investigate the vertical structures of turbulence kinetic energy (TKE) in the surface layer and two different vertical structures of TKE are distinguished. We then compare the production of TKE between these two vertical structures. In addition, we evaluate the performance of parameterization schemes for momentum flux under different vertical TKE structures. Key Points: The vertical structures of turbulence kinetic energy (TKE) over the Arctic sea‐ice surface are investigated using MOSAiC dataBudget analysis and spectral analysis are used to analyze TKE vertical structures near the Arctic sea‐ice surfaceThe TKE vertical structures affect the performance of commonly used turbulence parameterizations [ABSTRACT FROM AUTHOR]

Sea surface temperature anomaly (SSTA) of ocean eddies induces an anomalous air‐sea turbulent heat flux that acts to dampen SSTA. A two‐dimensional SSTA model explores the effect of air‐sea turbulent heat flux, parameterized as SSTA damping, in shaping eddy SSTA patterns. Increased SSTA damping transitions the SSTA pattern from a monopole to dipole, indicating the balance between eddy stirring of the background SST gradient and SSTA damping. The SSTA dipole pattern increases the correlation of eddy velocity and SSTA, but SSTA damping weakens the SSTA, resulting in an optimal damping rate maximizing lateral eddy surface heat transport. Globally, the SSTA damping rate increases toward the equator. In mid‐latitude and high‐latitude regions (e.g., the Kuroshio, the Gulf Stream, and the Southern Ocean), eddy SSTAs are monopoles, while the tropics and subtropics exhibit dipole SSTA patterns due to higher damping rates, facilitating greater lateral eddy heat transport when the SSTA is large. Plain Language Summary: Mesoscale ocean eddies, ranging from tens to hundreds of kilometers, exhibit distinct sea surface temperature anomaly (SSTA) patterns. In regions like the Kuroshio, the Gulf Stream, and the Southern Ocean, eddy SSTA exhibits a monopole pattern, with a single warm or cold core within the eddy. At lower latitudes, a dipole‐like pattern emerges, characterized by a pair of opposite‐sign SSTA surrounding the eddy. Previous studies attribute these SSTA patterns to the lateral stirring of background SST gradients by eddies. We develop a simplified SSTA model to highlight the role of eddy‐induced air‐sea turbulent heat flux in shaping eddy SSTA patterns. Eddy stirring of the background SST gradient generates SSTA, which induces anomalous sensible and latent heat flux that dampens SSTA. In the tropics and subtropics, effective SSTA damping balances the positive and negative SSTA generated by eddy stirring, resulting in a dipole‐like pattern. Conversely, at high latitudes, where SSTA damping is weaker, SSTA maintains its signature, yielding a monopole pattern. The transition from a monopole to a dipole pattern is facilitated by air‐sea heat flux, enhancing the correlation of eddy SSTA and velocity, while reducing SSTA variance, leading to an optimal damping rate that maximizes eddy heat transport. Key Points: Ocean eddies generate a dipole sea surface temperature anomaly (SSTA) pattern when air‐sea turbulent heat flux dampens SSTA counteracting eddy stirring of the background SSTThe dipole pattern enhances lateral eddy heat transport due to increased correlation between the eddies' horizontal velocity and SSTAThe SSTA damping rate due to air‐sea heat flux decreases toward the poles, maximizing lateral eddy heat transport in the subtropics [ABSTRACT FROM AUTHOR]

The Hadley circulation (HC) has been expanding poleward in recent decades. The Coupled Model Intercomparison Project Phase 6 (CMIP6) models predict that the expansion will accelerate in the future, more so in the Southern Hemisphere (SH). However, the extent of the expansion varies widely among the models. We investigate the mechanisms driving the intermodel spread in SH HC expansion predictions. The intermodel spread is obtained by an empirical orthogonal function analysis on the SH HC trend patterns of 16 CMIP6 model simulations using the historical and shared socioeconomic pathway 5–8.5 scenarios. The leading mode, showing a mean meridional stream function anomaly at the poleward SH HC extent, explains 49.73% of the variance and significantly correlates (r = 0.94) with the SH HC expansion. By analyzing the extended Kuo‐Eliassen equation, we find that the intermodel difference in the representation of diabatic heating is responsible for about 14% of the intermodel spread. The meridional eddy momentum and heat fluxes contribute to about 21% and 18% of the intermodel spread, respectively. The models simulating a relatively large SH HC expansion tend to show increased precipitation in the Southern Pacific Convergence Zone, reduced baroclinic instability in the subtropics, and an enhanced poleward shift of jet stream in the midlatitudes. This suggests that the uncertainty in the HC projection may be constrained by reducing the bias in the trend of the mean fields. Plain Language Summary: The Hadley circulation (HC), which affects global climate patterns, is expanding toward the poles. However, different climate models predict varying extents of this expansion, especially in the Southern Hemisphere (SH). We aim to understand why. By analyzing climate model data, we identified key factors influencing the spread in SH HC expansion. Our findings suggest that factors like diabatic heating and meridional eddy momentum play significant roles. Models showing greater SH HC expansion tend to simulate increased precipitation in specific regions and shifts in atmospheric jet streams. Addressing these model biases could help reduce uncertainty in future HC projections. Key Points: The first intermodel stream function trend mode effectively captures the spread of the Southern Hemisphere Hadley Circulation expansionThe intermodel spread in expansion is explained by the spread of the meridional eddy momentum, heat fluxes, and diabatic heatingThe spread of the eddy fluxes and diabatic heating are linked with the changes in precipitation, jet, and static stability [ABSTRACT FROM AUTHOR]

The parameterization of suspended sediments in vegetated flows presents a significant challenge, yet it is crucial across various environmental and geophysical disciplines. This study focuses on modeling suspended sediment concentrations (SSC) in vegetated flows with a canopy density of avH ∈ [0.3, 1.0] by examining turbulent dispersive flux. While conventional studies disregard dispersive momentum flux for avH > 0.1, our findings reveal significant dispersive sediment flux for large particles with a diameter‐to‐Kolmogorov length ratio when dp/η > 0.1. Traditional Rouse alike approaches therefore must be revised to account for this effect. We introduce a hybrid methodology that combines physical modeling with machine learning to parameterize dispersive flux, guided by constraints from diffusive and settling fluxes, characterized using recent covariance and turbulent settling methods, respectively. The model predictions align well with reported SSC data, demonstrating the versatility of the model in parameterizing sediment‐vegetation interactions in turbulent flows. Plain Language Summary: This research focuses on the movement of suspended sediments in rivers, specifically in areas with vegetation. Traditional models cannot depict this process, prompting the development of a new methodology that merges conventional scientific techniques with advanced machine learning. The proposed approach has demonstrated superior performance, particularly in transitional areas between vegetated and non‐vegetated zones. The significance of this study lies in its contribution to modeling an often‐overlooked spatial term (called "turbulent dispersive flux") by showing that its magnitude is much greater than conventionally supposed. This study also advances the current methodology of including physics‐based artificial intelligence to model sediment dynamics in vegetated river systems. The proposed approach is versatile and can be included in the large‐scale transport models. Key Points: Rouse budget without dispersive flux cannot describe coarse sediment concentration in vegetated flowsA machine‐assisted physical closure for turbulent dispersive flux from spatial average is proposedPredicted sediment concentration results agree with reported experimental data in the literature [ABSTRACT FROM AUTHOR]

Diabatic heating due to latent heat release in the storm tracks plays an important but poorly understood role in the midlatitude circulation. To examine how localised diabatic heating affects the circulation, a dry model is used to apply midtropospheric perturbations to the radiative‐equilibrium temperature profile to which the model is relaxed. This allows us to isolate the one‐way causal influence of diabatic heating on the circulation without feedbacks of the circulation onto the heating. By applying switch‐on perturbations at various latitudes, the mechanisms by which an equilibrated state is reached are examined. In all cases, the equilibrated circulation exhibits a dynamically insensitive jet structure with eddies maintaining a region of self‐concentrated baroclinicity, latitudinally shifted away from the heating perturbation. However, the initial response is generally very different. For heating poleward of the jet, there is an initial thermal‐wind adjustment and weakened eddy heat fluxes, followed later by weakened eddy momentum fluxes that maintain an equilibrated equatorward jet shift. For heating equatorward of the jet, the evolution is more complex with an initial strengthening of the eddy heat fluxes that dominantly balance the imposed heating, as well as a weakening of the Hadley cell. Further, the initial thermal‐wind adjustment immediately modifies the subtropical critical lines and eddy momentum fluxes that encourage an ∼15° poleward propagation from the Subtropics to Midlatitudes, yielding an equilibrated poleward jet shift. The overall determining factor in balancing the imposed heating at equilibration is the local climatological heat budget: if the climatological eddy heat fluxes locally warm, such as in mid‐to‐high latitudes, then this effect weakens, whereas if the climatological overturning circulation locally warms, such as in the Subtropics, then this effect weakens. The insensitivity of the equilibrated jet profile to the imposed heating is remarkable given the maintenance mechanisms vary drastically according to heating latitude. [ABSTRACT FROM AUTHOR]

The relaxed eddy accumulation (REA) method is a widely‐known technique that measures turbulent fluxes of scalar quantities. The REA technique has been used to measure turbulent fluxes of various compounds, such as methane, ethene, propene, butene, isoprene, nitrous oxides, ozone, and others. The REA method requires the accumulation of scalar concentrations in two separate compartments that conditionally sample updrafts and downdraft events. It is demonstrated here that the assumptions behind the conventional or two‐compartment REA approach allow for one‐compartment sampling, therefore called a one compartment or 1‐C‐REA approach, thereby expanding its operational utility. The one‐compartment sampling method is tested across various land cover types and atmospheric stability conditions, and it is found that the one‐compartment REA can provide results comparable to those determined from conventional two‐compartment REA. This finding enables rapid expansion and practical utility of REA in studies of surface‐atmosphere exchanges, interactions, and feedbacks. Plain Language Summary: Estimates of emission inventory of chemical compounds from the biosphere remain an indispensable tool in air quality and climate science research. Such inventory requires the measurements of the number of molecules flowing from the biosphere to the atmosphere, or vice‐versa, per unit ground area per unit time. What makes these measurements challenging is that such molecules are being transported rapidly by gusts and swirling (i.e., turbulent) motion in the atmosphere. In theory, this vertical exchange can be measured by a rapidly sampled covariance between vertical velocity and concentration variations. The main drawback is that such covariance requires rapid concentration measurements that are difficult to conduct for a large number of chemical species, although it is standard practice and easier to obtain for carbon dioxide, water vapor, and air temperature. The work here offers an alternative and efficient approach that necessitates measuring the accumulation of molecules in a single compartment, supplemented by knowledge of the velocity statistics. Both velocity and accumulated concentration measurements can be conducted with available instrumentation. Thus, the work here offers a blueprint for efficient sampling of emission rates across the biosphere‐atmosphere interface that can be deployed in upcoming experiments. Key Points: Relaxed eddy accumulation (REA) is used to estimate turbulent fluxes of numerous chemical speciesThe original REA relies on sampling concentrations in two compartmentsA single‐compartment REA is proposed with no loss in accuracy [ABSTRACT FROM AUTHOR]

Ecosystem respiration is a key flux in the terrestrial carbon cycle and is affected substantially by temperature. This work analysed the time series data of nighttime net ecosystem exchange of carbon dioxide (NEEnight) from 196 FLUXNET2015 sites to re‐evaluate the relationships between NEEnight and temperature. A total of 93 sites (48%) were identified to have a unimodal relationship between NEEnight and temperature. Site‐specific apparent optimum temperature parameters were then estimated at these sites. We further assessed the impacts of using exponential or unimodal equations on NEEnight predictions. The predicted NEEnight values at high temperatures were substantially higher from the exponential‐type equations (mean: ~200%) than from the unimodal equation (mean: ~30%), compared to the observed NEEnight. This study calls for using a unimodal equation to predict NEEnight (often considered as nighttime ecosystem respiration, ERnight), which could substantially improve the accuracy and reduce uncertainty in ER estimates, in particular under the scenario of global warming. [ABSTRACT FROM AUTHOR]

The South China Sea is a typical marginal sea characterized by the presence of numerous seamounts. However, the effect of seamounts on the air‐sea CO2 flux has not yet been well studied. In September 2021, the air‐sea CO2 flux was measured directly using eddy covariance (EC), and discrete waterside sampling was conducted. The results indicate that the northern South China Sea is a source of atmospheric CO2. Furthermore, EC measurements show that the seamount emits CO2 at an average rate of 0.34 mmol m−2 hr−1, nearly double that of non‐seamount areas. We suggest that the upwelling around the seamount transports deep water rich in dissolved inorganic carbon to the upper ocean, increasing the partial pressure of CO2 there. In addition, the increase in nutrients caused by the upwelling would increase the concentration of chlorophyll‐a, resulting in a productive area that emits CO2. Plain Language Summary: The South China Sea (SCS) serves as a minor CO2 source, and the air‐sea CO2 flux in its northern region demonstrates challenging spatiotemporal variations. In our investigation, we conducted underway assessments in the northern SCS and validated its emission of CO2, particularly in the vicinity of seamount ocean zones. CO2 emissions may have been intensified by the upward movement of seawater surrounding the seamount region. Key Points: The northern South China Sea emitted CO2 into the atmosphere at a mean rate of 0.28 mmol m−2 hr−1 in September 2021The CO2 flux almost doubled as the seamount was approached, indicating an increase in CO2 emissions near the seamountUpwelling releases high dissolved inorganic carbon, which increases the partial pressure of CO2 on the sea surface around the seamount [ABSTRACT FROM AUTHOR]

Observations of March 2024 Arctic (63°N–90°N) total column ozone set a record high of 477 Dobson Units (DU) against the 1979–2023 satellite era time series. It was about 60 DU higher than average and 6 DU higher than the previous March 1979 471 DU record. Daily Arctic ozone was above average for every day in March 2024, and set record highs from 11–26 March 2024. Microwave Limb Sounder data show this record ozone anomaly was concentrated in the lower stratosphere (10–30 km). These record values developed over the 2023–2024 winter and can be associated with vertically propagating planetary‐scale wave events that caused significant stratospheric warmings. These wave events forced poleward and downward ozone advection into the lower stratosphere, leading to record column ozone levels. The above average levels persisted through August 2024 and across the northern hemisphere. Plain Language Summary: Man‐made chlorofluorocarbons (CFCs) depleted the Earth ozone layer. The 1987 Montreal Protocol curbed CFC growth, but because CFCs have multi‐decadal lifetimes, Arctic ozone is not expected to recover back to 1980 levels until ∼2045. Current high CFC levels combined with persistent and cold polar vortices led to severe Arctic ozone spring depletion in 1997, 2011, and 2020. Contrary to expectations, March 2024 Arctic ozone showed a record high level, dramatically contrasting against the severe depletion events. Meteorological and ozone profile information show that the exceptional 2024 ozone was mainly found in the lowermost Arctic stratosphere, in association with record high lowermost stratospheric temperatures. The ozone levels incrementally increased during the 2023–2024 winter because of large‐scale weather systems that propagated from the troposphere into the stratosphere. Collectively, these weather systems also were at a record level, moving higher ozone concentrations from the mid‐latitudes and upper stratospheric into the Arctic region. This record high ozone would likely have not occurred if CFC levels had not begun slowly declining in response to the Montreal Protocol. Given the absence of high Arctic ozone since the 1970s, the March 2024 record high should be considered a positive harbinger of the future Arctic ozone layer. Key Points: Arctic total column ozone in March 2024 set a record high for the 1979‐present periodPolar lower stratosphere temperatures also set a record high in March 2024 in the MERRA‐2 reanalysis dataA record amount of Rossby waves propagating upward from the troposphere caused the record total ozone and lower stratospheric temperature [ABSTRACT FROM AUTHOR]

The parameterizations of air‐sea turbulent heat flux are one of the major bottlenecks in atmosphere‐ocean coupled model development, which play a crucial role in sea surface temperature (SST) prediction. Recently, neural networks start to be applied for the development of parameterizations of interface turbulent heat flux. However, these new parameterizations are primairily developed for specific regions and have not been tested in real atmosphere‐ocean coupled models. In this study, we propose a new air‐sea heat flux parameterization using a physical‐informed neural network (PINN) based on multiple observational data sets worldwide. Evaluated with an independent observation data set, it is shown that the PINN can significantly reduce the RMSE of latent heat flux by at least about 48.6% compared to three traditional bulk formulas. Moreover, the PINN can be flexibly updated with new observational data by transfer learning. To test the performance of the new parameterization in realistic application, we implement the PINN into a global ocean‐atmosphere coupled model and make seasonal forecasts for the first time. The PINN markedly reduce the errors of equatorial SST forecast, indicating a good performance of the PINN‐based air‐sea turbulent heat flux scheme. Noticeably, due to limited observational data, the NN‐based parameterizations tend to underestimate heat flux at high wind speeds compared with bulk formula‐based parameterizations. With more data available at extreme conditions, the PINN can be improved via transfer learning and need to be futher evaluated. This study suggests that PINN‐based air‐sea heat flux parameterization is promising to improve SST simulation. Plain Language Summary: The air‐sea turbulent heat flux plays a crucial role in advancing marine science and is the key to improving the accuracy of the sea surface temperature (SST) prediction. The traditional parameterizations for air‐sea turbulent heat flux have large deviations in some circumstances and are hard to update since they are developed based on unique observation datasets. The emergence of artificial intelligence offers a fresh avenue to address this issue. In this study, we develop air‐sea heat flux parameterization based on a PINN and multiple observational data sets, which measured air‐sea heat fluxes directly. Our novel parameterization outperforms three bulk formula‐based parameterizations in offline tests and solves the problem of unphysical result of neural networks. The new parameterization also shows great potential in improving the accuracy of SST prediction in multiple online tests. Key Points: We propose a new air‐sea turbulent heat flux parameterization based on physical‐informed neural network (PINN) which is trained on data in situThe new scheme can accurately calculate the air‐sea turbulent heat flux and perform well in a global seasonal forecastThe PINN can be flexibly updated with new observational data by transfer learning [ABSTRACT FROM AUTHOR]

In recent years, there has been a rise in human activities in oceanic areas, making the land–atmosphere interactions over islands a major scientific concern on a global scale. Examining the observation data from offshore areas enables a more comprehensive understanding of the turbulent fluxes in offshore atmospheric environments, patterns of momentum, energy and material exchange between the atmosphere and underlying surface in an oceanic boundary layer, and development of a heterogeneous atmospheric boundary layer. The related findings will assist in developing theoretical models and parameterization schemes to simulate the influence of heterogeneous surfaces on land–atmosphere interactions on the South China Sea Islands. Existing studies on the turbulent fluxes over the South China Sea Islands were mainly conducted on the Nansha Islands, whereas studies on the waters of the South China Sea are scarce. In this study, we used 10 Hz high‐frequency turbulence measurements to calculate the latent and sensible heat fluxes over the South China Sea Islands using the eddy correlation method. These findings were then compared with data from the Dunhuang Gobi, Ordos desert, and Xilingol grassland regions in inland China, along with the observed net radiation and surface heat fluxes. The findings indicate that the energy fluxes over the South China Sea in summer exhibit prominent diurnal variations. The magnitude of either latent or soil heat flux is low, and the net radiation is predominantly transformed into sensible heat flux, which warms the atmosphere. Furthermore, the daily variation curves of sensible and latent heat fluxes are influenced by intermittent turbulence on the islands and reefs, resulting in a less smooth pattern compared with soil heat flux. Although the South China Sea Islands have small land areas and are surrounded by the sea, the land–atmosphere interactions over the underlying surface of this region are similar to those over the underlying surface of grasslands in inland China during summer. The daily mean sensible heat flux on the islands is higher than that in an inland area, and the time lag in its response to sunrise is longer than that in inland areas by approximately 1 h. The overall energy balance ratio is approximately 0.75, c which is in line with the average level, but an energy balance residual of approximately 25% still exists. Furthermore, extreme weather conditions, such as typhoons, can disrupt the diurnal variations of sensible and latent heat fluxes, and the cyclical patterns are subsequently restored. [ABSTRACT FROM AUTHOR]

All ecosystems contain both sources and sinks for atmospheric carbon (C). A change in their balance of net and gross ecosystem carbon uptake, ecosystem‐scale carbon use efficiency (CUEECO), is a change in their ability to buffer climate change. However, anthropogenic nitrogen (N) deposition is increasing N availability, potentially shifting terrestrial ecosystem stoichiometry towards phosphorus (P) limitation. Depending on how gross primary production (GPP, plants alone) and ecosystem respiration (RECO, plants and heterotrophs) are limited by N, P or associated changes in other biogeochemical cycles, CUEECO may change. Seasonally, CUEECO also varies as the multiple processes that control GPP and respiration and their limitations shift in time. We worked in a Mediterranean tree‐grass ecosystem (locally called 'dehesa') characterized by mild, wet winters and summer droughts. We examined CUEECO from eddy covariance fluxes over 6 years under control, +N and + NP fertilized treatments on three timescales: annual, seasonal (determined by vegetation phenological phases) and 14‐day aggregations. Finer aggregation allowed consideration of responses to specific patterns in vegetation activity and meteorological conditions. We predicted that CUEECO should be increased by wetter conditions, and successively by N and NP fertilization. Milder and wetter years with proportionally longer growing seasons increased CUEECO, as did N fertilization, regardless of whether P was added. Using a generalized additive model, whole ecosystem phenological status and water deficit indicators, which both varied with treatment, were the main determinants of 14‐day differences in CUEECO. The direction of water effects depended on the timescale considered and occurred alongside treatment‐dependent water depletion. Overall, future regional trends of longer dry summers may push these systems towards lower CUEECO. [ABSTRACT FROM AUTHOR]

Methane (CH4) is a potent greenhouse gas (GHG) with atmospheric concentrations that have nearly tripled since pre‐industrial times. Wetlands account for a large share of global CH4 emissions, yet the magnitude and factors controlling CH4 fluxes in tidal wetlands remain uncertain. We synthesized CH4 flux data from 100 chamber and 9 eddy covariance (EC) sites across tidal marshes in the conterminous United States to assess controlling factors and improve predictions of CH4 emissions. This effort included creating an open‐source database of chamber‐based GHG fluxes (https://doi.org/10.25573/serc.14227085). Annual fluxes across chamber and EC sites averaged 26 ± 53 g CH4 m−2 year−1, with a median of 3.9 g CH4 m−2 year−1, and only 25% of sites exceeding 18 g CH4 m−2 year−1. The highest fluxes were observed at fresh‐oligohaline sites with daily maximum temperature normals (MATmax) above 25.6°C. These were followed by frequently inundated low and mid‐fresh‐oligohaline marshes with MATmax ≤25.6°C, and mesohaline sites with MATmax >19°C. Quantile regressions of paired chamber CH4 flux and porewater biogeochemistry revealed that the 90th percentile of fluxes fell below 5 ± 3 nmol m−2 s−1 at sulfate concentrations >4.7 ± 0.6 mM, porewater salinity >21 ± 2 psu, or surface water salinity >15 ± 3 psu. Across sites, salinity was the dominant predictor of annual CH4 fluxes, while within sites, temperature, gross primary productivity (GPP), and tidal height controlled variability at diel and seasonal scales. At the diel scale, GPP preceded temperature in importance for predicting CH4 flux changes, while the opposite was observed at the seasonal scale. Water levels influenced the timing and pathway of diel CH4 fluxes, with pulsed releases of stored CH4 at low to rising tide. This study provides data and methods to improve tidal marsh CH4 emission estimates, support blue carbon assessments, and refine national and global GHG inventories. [ABSTRACT FROM AUTHOR]

Atmospheric fronts embedded in extratropical cyclones are high‐impact weather phenomena, contributing significantly to mid‐latitude winter precipitation. The three vital characteristics of the atmospheric fronts, high wind speeds, abrupt change in wind direction, and rapid translation, force the induced surface waves to be misaligned with winds exclusively behind the cold fronts. The effects of the misaligned waves under atmospheric cold fronts on air‐sea fluxes remain undocumented. Using the multi‐year in situ near‐surface observations and direct covariance flux measurements from the Pioneer Array off the coast of New England, we find that the majority of the passing cold fronts generate misaligned waves behind the cold front. Once generated, the waves remain misaligned, on average, for about 8 hr. The parameterized effect of misaligned waves in a fully coupled model significantly increases the roughness length (185%), drag coefficient (19%), and air‐sea momentum flux (11%). The increased surface drag reduces the wind speeds in the surface layer. The upward turbulent heat flux is weakly decreased by the misaligned waves because of the decrease in temperature and humidity scaling parameters being greater than the increase in friction velocity. The misaligned wave effect is not accurately represented in a commonly used wave‐based bulk flux algorithm. Yet, considering this effect in the current formulation improves the overall accuracy of parameterized momentum flux estimates. The results imply that better representing a directional wind‐wave coupling in the bulk formula of the numerical models may help improve the air‐sea interaction simulations under the passing atmospheric fronts in the mid‐latitudes. Plain Language Summary: Atmospheric fronts are recurrent weather phenomena in mid‐latitudes, significantly contributing to winter precipitation. They are characterized by high wind speeds, abrupt changes in wind direction, and rapid translation. The passage of the fronts over the ocean can generate strongly misaligned waves with the local wind, particularly behind the cold fronts. The effects of these misaligned waves under atmospheric cold fronts on air‐sea fluxes remain undocumented. Using the long‐term surface observations from the Pioneer Array off the coast of New England, we find that the majority of the passing atmospheric fronts generate misaligned waves behind the cold front, which can remain misaligned, on average, for about 8 hr. By increasing the ocean roughness length in case of misaligned waves in coupled numerical experiments, a significant increase in momentum flux is found, which reduces the surface wind speeds. The misaligned wave effect is not accurately represented in a commonly used wave‐based air‐sea flux algorithm. Yet, by considering this effect in the current formulation, the overall accuracy of parameterized momentum flux estimates is improved. A better representation of the air‐sea interaction in numerical models is crucial for a better understanding of regional and global climate. Key Points: Passing atmospheric cold fronts generate a large area of growing wind‐waves that are misaligned with local windParameterized effect of misaligned waves increases the roughness length, drag and enthalpy coefficients, and wind stressRepresentation of the misaligned wave effect in the bulk formula improves the momentum flux estimates [ABSTRACT FROM AUTHOR]

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

Evapotranspiration (ET) plays a critical role in water and energy budgets at regional to global scales. ET is composed of direct evaporation (E) and plant transpiration (T) where the latter is regulated via stomatal conductance (gsc), which depends on a multitude of plant physiological processes and hydrometeorological forcings. In recent years, significant advances have been made toward estimating gsc using a variety of models, ranging from relatively simple empirical models to more complex and data‐intensive plant hydraulic models. Using machine learning (ML) and eddy covariance flux tower data of 642 site years across 84 sites distributed across 10 land covers globally, here we show that structural constraints inherent in current empirical and plant hydraulic models of gsc limit their effectiveness for predicting ET. These constraints also prevent the models from fully utilizing the available hydrometeorological data at eddy covariance sites. Even if these gsc models are calibrated locally, structural simplifications inherent in them limit their capability to accurately capture gsc dynamics. In contrast, a ML approach, wherein the model structure is learned from the data, outperforms traditional models, thus highlighting that there still is significant room for improvement in the structure of traditional models for predicting ET. These results underscore the need to prioritize improvements in gsc models for more accurate ET estimation. This, in turn, will help reduce uncertainties in the assessments of plants' role in regulating the Earth's climate. Key Points: Current stomatal conductance models underutilize the site‐specific hydrometeorological dataStructural constraints in empirical models are more restrictive compared to plant hydraulic modelsEnhancements are needed for the simplified depiction of the water potential gradient across the root‐xylem‐leaf continuum in plant hydraulic models [ABSTRACT FROM AUTHOR]

We study the impacts of a continental slope on instability and mesoscale eddy fluxes in idealized 3‐layer numerical model simulations. The simulations are inspired by and mimic the situation in the Arctic Ocean's Beaufort Gyre, where anti‐cyclonic winds drive anti‐cyclonic currents that are guided by the continental slope. The forcing and currents are retrograde with respect to topographic Rossby waves. The focus of the analysis is on eddy potential vorticity (PV) fluxes and eddy‐mean flow interactions under the Transformed Eulerian Mean framework. Eddy lateral vorticity fluxes dominate over the continental slope where eddy form stress, that is, vertical momentum flux, is suppressed due to the topographic PV gradient. The diagnosis also shows that while eddy momentum fluxes are up‐gradient over parts of the slope, the total quasi‐geostrophic PV flux is down‐gradient everywhere. We then calculate the linearly unstable modes of the time‐mean state and find that the most unstable mode contains several key features of the observed finite‐amplitude fluxes over the slope, including down‐gradient PV fluxes. When accounting for additional unstable modes, more qualitative features of the observed eddy fluxes in the numerical model are reproduced. Plain Language Summary: The ocean circulation in the Arctic is heavily influenced by the bottom bathymetry. Essentially, currents are steered to follow continental slopes and submarine ridges. This topographic steering makes transfer of properties by ocean currents across continental slopes difficult, and the result is that the deep basins are partially isolated from the continental shelves. Large‐scale oceanic turbulence, or "mesoscale eddies," are able to cross bottom bathymetry, but transport by such eddies is also hampered. In this study, a simplified numerical model is used to learn about how bottom bathymetry impacts eddy transport in and out of the Beaufort Gyre, a wind‐driven large‐scale gyre in the Arctic Ocean's Canada Basin. The gyre is the largest reservoir of fresh waters in the Arctic, and understanding how topography controls the export of this freshwater is thought to be of crucial importance if climate models are to properly simulate a future Arctic Ocean. The study shines light on some key aspects that the models need to capture to get transport across the continental slope right. Key Points: A numerical 3‐layer model is used to study instability and eddy dynamics over the continental slope in an idealized wind‐driven ocean gyreEddy fluxes of potential vorticity are down‐gradient in all three layersLinearized stability calculations are able to reproduce the qualitative features of PV fluxes near the slope [ABSTRACT FROM AUTHOR]

Sea spray, originating from wave breaking under high wind conditions, can significantly affect turbulent heat fluxes at the air–sea interface. Even though polar lows (PLs) can become extreme weather features with gale‐force wind, the impact of sea spray on their development has rarely been investigated and is not considered in operational forecast models. In this study, the impact of sea spray on the development of two PLs over the Barents Sea is studied based on sensitivity experiments with an atmosphere–wave coupled model, where the spray‐mediated heat fluxes are parameterized. The results show that the impact of sea‐spray‐mediated heat fluxes on PL development is sensitive to the surface wind speed. In the case of the stronger PL, the higher surface wind speed results in significantly higher spray‐mediated heat fluxes. Consequently, these spray‐mediated heat fluxes intensify the convection and diabatic heating of the PL, resulting in its intensification. In comparison, the case with a weaker PL experiences less sea spray production and lower spray‐mediated heat fluxes due to its weaker surface wind speeds. Overall, we find that spray‐mediated sensible heat fluxes play an important role in the development of PLs, while the latent heat fluxes induced by sea spray have a relatively minor impact. [ABSTRACT FROM AUTHOR]

Popular evapotranspiration (ET) partitioning methods make assumptions that might not be well‐suited to dryland ecosystems, such as high sensitivity of plant water‐use efficiency (WUE) to vapor pressure deficit (VPD). Our objectives were to (a) create an ET partitioning model that can produce fine‐scale estimates of transpiration (T) in drylands, and (b) use this approach to evaluate how climate controls T and WUE across ecosystem types and timescales along a dryland aridity gradient. We developed a novel, semi‐mechanistic ET partitioning method using a Bayesian approach that constrains abiotic evaporation using process‐based models, and loosely constrains time‐varying WUE within an autoregressive framework. We used this method to estimate daily T and weekly WUE across seven dryland ecosystem types and found that T dominates ET across the aridity gradient. Then, we applied cross‐wavelet coherence analysis to evaluate the temporal coherence between focal response variables (WUE and T/ET) and environmental variables. At yearly scales, we found that WUE at less arid, higher elevation sites was primarily limited by atmospheric moisture demand, and WUE at more arid, lower elevation sites was primarily limited by moisture supply. At sub‐yearly timescales, WUE and VPD were sporadically correlated. Hence, ecosystem‐scale dryland WUE is not always sensitive to changes in VPD at short timescales, despite this being a common assumption in many ET partitioning models. This new ET partitioning method can be used in dryland ecosystems to better understand how climate influences physically and biologically driven water fluxes. Plain Language Summary: We developed a new model to better understand how plants use and lose water in drylands and applied it to seven dryland sites. Our model partitions evapotranspiration—the total water lost to the atmosphere from the Earth's surface— into its components. Evapotranspiration consists of both evaporation from wet surfaces, such as wet soil, and the water lost from plants when they photosynthesize. Currently, models assume a strong relationship between the efficiency with which plants use water ("water‐use efficiency") and the dryness of the atmosphere, but this violates what we know about how plants function in drylands. For example, in drylands many plants are adapted to very dry conditions and their water use can be less sensitive to increasing atmospheric dryness compared to plants from wet environments. Using this new model, we found that plant water‐use efficiency is only correlated with atmospheric dryness some of the time and that evapotranspiration is primary controlled by water lost from plants. This model allows us to better understand the importance of timescale and ecosystem type in governing plant water‐use dynamics and more accurately assess the potential impact of changing climate conditions on dryland water fluxes and ecosystem processes. Key Points: A new evapotranspiration partitioning model (DEPART) was developed using eddy covariance flux tower measurements in a Bayesian frameworkThis method produces daily estimates of transpiration and weekly estimates of plant water‐use efficiency at the ecosystem scaleThis method reveals water‐use efficiency is limited by moisture supply in more arid climates and moisture demand in less arid climates [ABSTRACT FROM AUTHOR]

Terrestrial carbon uptake and water availability have coupled feedbacks; specifically water uptake for plant growth and soil drying via transpiration. While we might expect this coupling over time at arid sites, climatic water availability also widely covaries geographically with biomass variables that control photosynthetic rates. Using eddy covariance data globally, we find convex, positively‐covarying relations between carbon uptake and a turbulent flux metric controlled by land surface moisture (r = 0.73 monthly across sites) at the site level. We estimate a general, empirical relationship based on site‐wise water‐carbon dynamics. Most sites, and the general relationship, show strong power‐law dependence, implicating the role of sub‐seasonal land‐cover dynamics. We also find that long‐term mean carbon/water states follow a similar convex relationship to the site‐specific temporal dynamics. We discuss opportunities and caveats for space‐for‐time frameworks of carbon/water feedback processes globally. Plain Language Summary: The amount of carbon dioxide that plants take from the air depends on how plants respond to water and water stress. At the same time, plants also control the loss of water from the landscape through transpiration. While we think of individual stressed plants in dry conditions as being very sensitive to the time‐variability in water available to them, we find here that the average carbon uptake by plants across climate zones is similarly related to climatic water availability. Water availability and carbon uptake rates seem not to depend strongly on location, so that most locations behave quite similarly, across many climates. This can be explained by similar structural changes in the vegetation canopy in response to water stress, whether it be over time at a site or across regions with different mean climate conditions. Key Points: Landscape carbon uptake displays strong relationships with landscape evaporative fractionThese relations are non‐linear both at single sites and across bioclimates at eddy covariance tower sitesChanges in structural canopy‐scale variables (e.g., leaf‐area) may dominate the coupling of water and carbon cycles similarly in both space and time [ABSTRACT FROM AUTHOR]

Aerosol‐cloud‐precipitation interactions are a leading source of uncertainty in estimating climate sensitivity. Remote marine boundary layers where accumulation mode (∼100–400 nm diameter) aerosol concentrations are relatively low are very susceptible to aerosol changes. These regions also experience heightened Aitken mode aerosol (∼10–100 nm) concentrations associated with ocean biology. Aitken aerosols may significantly influence cloud properties and evolution by replenishing cloud condensation nuclei and droplet number lost through precipitation (i.e., Aitken buffering). We use a large‐eddy simulation with an Aitken‐mode enabled microphysics scheme to examine the role of Aitken buffering in a mid‐latitude decoupled boundary layer cloud regime observed on 15 July 2017 during the Aerosol and Cloud Experiments in the Eastern North Atlantic flight campaign: cumulus rising into stratocumulus under elevated Aitken concentrations (∼100–200 mg−1). In situ measurements are used to constrain and evaluate this case study. Our simulation accurately captures observed aerosol‐cloud‐precipitation interactions and reveals time‐evolving processes driving regime development and evolution. Aitken activation into the accumulation mode in the cumulus layer provides a reservoir for turbulence and convection to carry accumulation aerosols into the drizzling stratocumulus layer above. Further Aitken activation occurs aloft in the stratocumulus layer. Together, these activation events buffer this cloud regime against precipitation removal, reducing cloud break‐up and associated increases in heterogeneity. We examine cloud evolution sensitivity to initial aerosol conditions. With halved accumulation number, Aitken aerosols restore accumulation concentrations, maintain droplet number similar to original values, and prevent cloud break‐up. Without Aitken aerosols, precipitation‐driven cloud break‐up occurs rapidly. In this regime, Aitken buffering sustains brighter, more homogeneous clouds for longer. Plain Language Summary: Aerosols, small particles in the atmosphere associated with ocean biology, sea spray, land, and human‐produced emissions, influence cloud brightness and, by suppressing precipitation and subsequent break up, cloud lifetime. Understanding aerosol‐cloud‐precipitation interactions is critical in understanding how aerosols influence the climate system. This study examines how the very smallest aerosol particles modify cloud formation, brightness, and lifetime over the North Atlantic ocean. We utilize a recent set of aircraft and satellite observations from a dedicated field campaign as well as a detailed model that resolves fine‐scale interactions important to cloud development. After comparing the model to real‐world observations, we test how modifying the amount of small particles impacts the cloud brightness and lifetime. We find that the small particles are able to offset precipitation removal of larger particles, helping clouds to last longer and stay brighter. Key Points: Observations of mid‐latitude decoupled low clouds constrain a large‐eddy simulation investigating aerosol‐cloud‐precipitation interactionsBoundary layer Aitken activation and turbulent and convective fluxes restore accumulation mode aerosols against precipitation lossesAitken buffering acts to sustain brighter, more homogeneous clouds for longer [ABSTRACT FROM AUTHOR]

A significant and striking seesaw pattern of winter surface air temperature (SAT) has emerged, featuring pronounced warming Arctic and cooling Eurasian (referred to as WACE). This study investigates the subseasonal SAT modes across the mid‐ and high‐latitudes of Eurasia and their possible mechanisms based on daily reanalysis data from 1979 to 2022. Our results reveal that Eurasian winter SAT exhibits two distinct subseasonal modes, characterized by a correlated southeastward propagation of temperature and geopotential height anomalies (GHAs) in the middle and lower troposphere. Notably, the subseasonal SAT anomalies with eight phases constrained by the hydrostatic equilibrium, originate from the GHAs in the Arctic stratosphere and then transfer to the East Asia. The sixth phase of the transmitted subseasonal SAT mode is proved to be the key transition phase from the WACE pattern to its counterpart. Further analysis indicates that the strength of the transmitted subseasonal SAT mode is controlled by the tripolar sea surface turbulent heat flux anomalies over the north Atlantic. Plain Language Summary: Over recent decades, Earth's changing climate has brought about some significant temperature anomalies, particularly in the Arctic and mid‐latitude regions. This has led to severe socio‐ecological consequences, including increased damage to our ecosystems. A noticeable pattern in winter temperature is the warm Arctic‐cold Eurasian mode, which has been observed on multiple time scales. Here we show, on the subseasonal time scale, during the winter in Eurasia, there are two different patterns of temperature changes, and they move together toward the southeast in the troposphere. One of these patterns, called WACE, goes through a repeating cycle from the Arctic to East Asia. We specifically looked at the reversal phase of this cycle, where we found that changes in the stratosphere above the Arctic region kickstart the process, and then the turbulent heat near the surface contribute to the changes in the polar region by triggering a Rossby wave. Key Points: The detailed southeastward propagation of a transmitted subseasonal Eurasia winter surface air temperature (SAT) mode is revealedThe subseasonal SAT mode originates from the geopotential height anomaly in Arctic stratosphere constrained by the hydrostatic equilibriumThe strength of the subseasonal SAT mode is controlled by the tripolar sea surface turbulent heat flux anomalies over the North Atlantic [ABSTRACT FROM AUTHOR]

Air‐sea interaction in late boreal winter is studied over the extratropical North Atlantic (NA) during 1960–2020 by examining the relationship between sea‐surface temperature (SST) and total turbulent heat flux (THF). The two quantities are positively correlated on interannual timescales over the central‐midlatitude and subpolar NA, suggesting the atmosphere on average drives SST and THF variability is independent of SST. On decadal timescales and over the central‐midlatitude NA the correlation is negative, suggesting ocean processes on average drive SST and THF variability is sensitive to SST. The correlation is positive over the subpolar NA. There, interannual and decadal THF variability is governed by the North Atlantic Oscillation (NAO). During the major late 20th and early 21st century SST increase in the subpolar NA diminishing oceanic heat loss associated with a weakening NAO was observed. This study suggests that the atmosphere is more sensitive to SST over the central‐midlatitude than subpolar NA. Plain Language Summary: The relationship between the sea‐surface temperature (SST) and air‐sea heat exchange, is studied over the extratropical North Atlantic (NA) for late boreal winter during 1960–2020. This relationship provides information about the roles of atmospheric and oceanic processes in driving SST variations. We consider two regions, the central‐midlatitude (35°N–50°N) and subpolar (50°N–60°N) NA. Over both regions, the atmosphere tends to drive the variations on the short interannual timescales. On the longer decadal timescales and over the central‐midlatitude NA, oceanic processes tend to drive the SST anomalies that in turn influence the air‐sea heat exchange. Air‐sea heat exchange over the subpolar NA is mostly driven by the North Atlantic Oscillation on interannual and decadal timescales, which is the leading mode of internal atmospheric variability in winter. This study suggests that the atmosphere is more sensitive to SST over the central‐midlatitude than subpolar NA. Key Points: Regional variation in the nature of air‐sea interaction over the extratropical North Atlantic (NA) north of 35°NTimescale dependence in relationship between sea‐surface temperature (SST) and turbulent heat flux over the central‐midlatitude NAThe atmosphere is more sensitive to SST variability over the central‐midlatitude than subpolar NA [ABSTRACT FROM AUTHOR]

Extensive regions in the permafrost zone are projected to become climatically unsuitable to sustain permafrost peatlands over the next century, suggesting transformations in these landscapes that can leave large amounts of permafrost carbon vulnerable to post‐thaw decomposition. We present 3 years of eddy covariance measurements of CH4 and CO2 fluxes from the degrading permafrost peatland Iškoras in Northern Norway, which we disaggregate into separate fluxes of palsa, pond, and fen areas using information provided by the dynamic flux footprint in a novel ensemble‐based Bayesian deep neural network framework. The 3‐year mean CO2‐equivalent flux is estimated to be 106 gCO2 m−2 yr−1 for palsas, 1,780 gCO2 m−2 yr−1 for ponds, and −31 gCO2 m−2 yr−1 for fens, indicating that possible palsa degradation to thermokarst ponds would strengthen the local greenhouse gas forcing by a factor of about 17, while transformation into fens would slightly reduce the current local greenhouse gas forcing. Plain Language Summary: Arctic and sub‐arctic regions on the southern border of the permafrost zone often feature peatlands with a patchy surface of peat mounds, thaw ponds, and surrounding fens. As the permafrost underneath peat mounds thaws, these areas transform and can change their emission or uptake of greenhouse gases like CO2 and methane. Assessing this gas exchange on the patchy surface is difficult because our measurement techniques cannot directly observe the variability in space and time. We collected 3 years of gas exchange measurements at a Norwegian permafrost peatland and developed a new method using a collection of uncertainty‐aware neural networks to predict the greenhouse gas exchange of different surface types. Our work suggests that large amounts of methane are emitted by ponds and fens, while the elevated peat mounds have almost no methane emissions. For CO2, we see that ponds are strong emitters, while fens take up substantial amounts as their vegetation absorbs this gas. We are still unsure when the peat mounds will collapse and if they turn into ponds or fens, but we can say that pond formation would give a 17 fold increase in greenhouse gas emissions, while fen formation would slightly reduce today's emissions of permafrost peatlands. Key Points: Eddy covariance fluxes are disaggregated for different surfaces using Bayesian neural networks to derive uncertainty‐aware carbon balancesWhile palsa areas have a near‐zero annual methane balance, the fens and ponds that form upon palsa degradation emit large amounts of methaneFens compensate for methane emissions with strong annual CO2 sinks, while ponds appear as strong, yet uncertain, CO2 emission hotspots [ABSTRACT FROM AUTHOR]

Turbulent fluxes play a critical role in atmospheric science and are usually calculated from the eddy covariance system. However, the presence of motions of larger scale and the bias from observational instruments often affects the procurement of turbulent fluxes. Based on the Hilbert–Huang transform, the properties of transport can be defined and used to distinguish non‐turbulent motions from the observational data, and a new way of decomposing the variables is thereby put forward to reconstruct the turbulent flux series. To quantify the influence of non‐turbulent motions on the calculation of turbulent flux, the non‐turbulent motions extracted from the five‐level turbulence data of the Tianjin 255‐m meteorological tower from July 1 to August 31, 2017 are examined. The results reveal that the presence of non‐turbulent motion can lead to a universal overestimation of turbulent flux, and the degree of overestimation increases with the complexity and the intensity of non‐turbulent motion. According to the consequences above, an empirical relationship, together with the corresponding coefficients, is given to provide a guidance on the correction of turbulent fluxes in practical use, such as the simulation of atmospheric turbulence and the parameterization in meteorological and climate models. [ABSTRACT FROM AUTHOR]

The response of the North Atlantic large‐scale circulation to El Niño–Southern Oscillation (ENSO) exhibits distinct differences between early (November–December) and late (January–February) winter. However, the reasons for this are unclear, particularly regarding the early winter response. Here we examine the role of storm‐track dynamics in influencing the intraseasonal variability of the ENSO teleconnection to the North Atlantic. During late winter there a broad weakening of the eddy heat flux upstream of the North Atlantic storm track during the El Niño phase, which is associated with a broad southward jet shift across North America and the North Atlantic. The late winter response is reinforced by synoptic eddies through enhanced cyclonic wave breaking, consistent with previous studies. However, a stronger teleconnection occurs during early winter. There are modest changes in the North Atlantic eddy heat flux, but strong changes in the upper‐level storm track associated with ENSO, with increased anticyclonic wave breaking during El Niño reinforcing the jet across the central North Atlantic. During early winter there are less frequent northern eddy‐driven jet occurrences in El Niño years and more frequent northern eddy‐driven jet occurrences in La Niña years. These poleward North Atlantic jet excursions typically follow peaks in the eddy heat flux; however, in El Niño years this relationship breaks down and the jet does not transition to the northern position as frequently, despite no clear changes in the upstream eddy heat flux. Composite analysis reveals that precursor storm‐track anomalies upstream over the eastern North Pacific/North America are important in suppressing the poleward jet excursions. These precursors map onto the seasonal mean North Pacific storm‐track anomalies during El Niño. Measured across all years, there is a clear relationship between the mean early winter eastern North Pacific storm‐track activity and eastern North Atlantic eddy‐driven jet, which can explain the early winter ENSO teleconnection to the North Atlantic. [ABSTRACT FROM AUTHOR]

The North Atlantic Oscillation (NAO) is a dominant atmospheric variability in the Northern Hemisphere that has a substantial impact on weather and climate on various time scales. Here, we investigate the role of energy conversion terms day‐by‐day during the NAO life cycle. The relative timing and contribution of the energy conversion terms are quantified by projecting the terms onto the eddy total energy, eddy kinetic energy (EKE), and eddy available potential energy (EAPE) patterns associated with the NAO. The results show a remarkable phase dependence in the growth and maintenance mechanisms. For positive NAOs, the initial growth is driven by the barotropic interactions between the eddies propagating over North America. This suggests that a non‐local growth mechanism plays an important role in the initiation of positive NAOs. In contrast, it is the baroclinic processes that initiate negative NAOs. The conversion of the mean APE into the EAPE and then into the EKE, processes which include eddy heat fluxes and vertical motions, results in the relatively local growth of negative NAOs. During the mature phase, the largest source of energy is the conversion of the mean APE into EAPE. Part of this is converted to EKE, making a substantial contribution to the maintenance of the EKE. This process is particularly important for negative NAOs. [ABSTRACT FROM AUTHOR]

In the southwest Pacific, a meandering jet-stream in the upper troposphere is sometimes found at -30° S during austral winters and is usually treated as a sub-tropical jet (STJ) due to its low latitude. For two contrasting cases, we have conducted analyses from two perspectives to identify the STJ and PFJ: first, using previously published qualitative criteria to identify jet-cores and second, investigating the jet-stream axes of STJ and PFJ identified using 2-PVU curves. The results showed that the chosen meandering jet-stream case at -30° S was a merged, and for a time, a superposed STJ and PFJ. Downstream of the jet-streak, the PFJ split to the south and the STJ to the east. This is in significant contrast to the horizontally well-separated jet-stream case chosen in this study. Some processes likely contributing to the superposition of the STJ and PFJ were analyzed and discussed. The movement of PFJ that was closely associated with the movement of the low over the Tasman Sea and the convection in and near the tropical region may have played dominant roles. [ABSTRACT FROM AUTHOR]

Turbulent fluxes of heat, momentum, and humidity in the atmospheric boundary layer are pivotal to the evolution of geology, weather and climate, and the possibility of life. Here we extend recent advances in calculating these near‐surface turbulent fluxes in the Earth's atmospheric boundary layer to any terrestrial planetary body with an atmosphere. These improvements include: (a) incorporating Monin‐Obukhov similarity functions that encompass the entire range of atmospheric stability expected on terrestrial planetary bodies, (b) accounting for the additional shear associated with buoyant plumes under unstable conditions, (c) using surface renewal theory to calculate transfer rates within the interfacial layer adjacent to the surface, and (d) explicitly accounting for key humidity effects that become especially important when a volatile is more buoyant than the ambient gas (e.g., on Mars where H2O is lighter than CO2). We tested and validated our model using in situ data collected on Earth, Mars, and Titan under a wide range of atmospheric stability, pressure, and surface roughness conditions. The model shows up to 71% better agreement with measurements compared to methods commonly used on Mars for evaporation/sublimation. Compared to previous estimates for H2O ice on Mars, our model predicts up to 1.5–190x lower latent heat fluxes under stable atmospheric conditions (depending on the wind speed) and 1.78x higher latent heat fluxes under unstable conditions. Our results provide improved constraints on the stability of ice on Mars and will help determine whether ice can melt under present‐day conditions. Plain Language Summary: As air flows over a surface, the resulting turbulent eddies cause the air to mix. The intensity of turbulence generated dictates the rate at which energy is given to, or taken away from the surface. If there are volatiles such as liquid water at the surface, then the magnitude of the turbulent fluxes determines how long the volatiles will remain stable before evaporating or freezing. We applied recent advances made on Earth to develop a model for predicting turbulent fluxes and evaporation rates on any planetary body with an atmosphere. To check whether our simulations are accurate, we compared them with measurements made on Earth, Mars and Titan. We found that our simulations agreed up to 71% better with measurements compared to previously developed models used for Mars evaporation. Our simulations predict significantly higher or lower rates of evaporation when compared to previous estimates, depending on atmospheric conditions. These results provide improved constraints on the stability of ice on Mars and will help determine whether ice can melt under present‐day conditions. Key Points: We present an improved model to predict atmospheric turbulent fluxes and evaporation/sublimation rates on any terrestrial planetary bodyThe model shows up to 71% better agreement with measurements compared to methods commonly used on Mars for evaporation and sublimationOur results provide improved constraints on the stability of Martian ice and will help determine whether ice can melt on Mars at present [ABSTRACT FROM AUTHOR]

Jupiter's equatorial eastward zonal flows reach wind velocities of ∼100 m s−1, while on Saturn they are three times as strong and extend about twice as wide in latitude, despite the two planets being overall dynamically similar. Recent gravity measurements obtained by the Juno and Cassini spacecraft uncovered that the depth of zonal flows on Saturn is about three times greater than on Jupiter. Here we show, using 3D deep convection simulations, that the atmospheric depth is the determining factor controlling both the strength and latitudinal extent of the equatorial zonal flows, consistent with the measurements for both planets. We show that the atmospheric depth is proportional to the convectively driven eddy momentum flux, which controls the strength of the zonal flows. These results provide a mechanistic explanation for the observed differences in the equatorial regions of Jupiter and Saturn, and offer new understandings about the dynamics of gas giants beyond the Solar System. Plain Language Summary: In this study, we investigate the strong eastward jet around the equator of Jupiter and Saturn. Despite the planets being similar, Saturn's winds are stronger and cover a wider area in latitude. Recent spacecraft measurements revealed that Saturn's winds go much deeper into its interior than Jupiter's. Using numerical simulations, we find that the depth of the atmosphere is crucial in determining the strength and width of these winds. We show that the depth is related to a specific turbulent flow, dictating the strength of the jets. These findings explain why Jupiter and Saturn have different equatorial zonal wind patterns and provide new insights into the behavior of giant planets outside the Solar System. Key Points: Through 3D numerical simulations, we deduce that the flow depth of gas giants significantly influences their equatorial dynamicsEquatorial flows are driven by eddy fluxes perpendicular to the axis of rotation, and these fluxes are proportionate to the flow depthThe zonal flow depth of Jupiter and Saturn, inversely proportional to their 3:1 mass ratio, leads to the corresponding ratio in flow strength [ABSTRACT FROM AUTHOR]

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

Using 2‐year platform observations, this study investigates seasonal characteristics of sea land breeze (SLB) and how it influences air‐sea turbulent heat fluxes (THFs) in the coastal areas of East China Sea (ECS) in different seasons. Unlike other SLB studies, this study uses hourly observation on a sea platform to explore SLB's effect on both air‐sea latent heat and sensible heat transferring. The results show that sea wind (SW) does not have an obvious seasonal variation pattern while land wind (LW) is stronger in autumn and winter. The SLB day number shows a clear seasonal variation pattern, which accounts for 38.04% and 18.23% of summertime and wintertime days, reaching its peak and bottom respectively. The latent heat flux (LHF) and sensible heat flux (SHF) are high in autumn and winter while low in summer. The SLB‐contributed LHF and SHF reach peaks in autumn and winter, which are 61.07 and 7.39 W/m2 respectively. The contribution importance of SLB on air‐sea sensible/latent heat transferring is highest in summer while lowest in winter. On SLB days, the SHF decreases significantly by at least about 50% while LHF decreases moderately in all seasons, among which spring witnesses an inversion of sensible heat transferring direction. The warming effect of SLB is mainly responsible for the slump of SHF on SLB days. Multiple factors including relative humidity (RH), background wind field and in situ radiation cause the LHF decrease together, whose changing range varies with season. Plain Language Summary: Sea land breeze (SLB) has a great impact on regional environment and meteorological fields. Turbulent heat flux (THF), including sensible heat flux (SHF) and latent heat flux (LHF), is fundamentally engaged in nearly every atmosphere‐ocean interaction process and undoubtedly serve as an important driving force of global atmospheric and oceanic circulation as well as a sensitive variable when facing global climate change. However, there are few studies relating SLB to the variation of THF in the near coastal region, which is a sensitive‐area to climatic changes under the effects of both natural and human variabilities. In this study, instead of using land‐based data like other SLB studies, we investigate SLB's effects on air‐sea THFs in different seasons based on sea‐based data. We find that SLB's role in transferring air‐sea energy in form of THF is most important in summer among all seasons. The SHF decreases significantly while LHF decreases moderately on SLB days in all four seasons. The warming effect of SLB is mainly responsible for the slump of SHF on SLB days, while the external factors such as background wind field, relative humidity, and in situ radiation are responsible for the LHF decrease on SLB days. Key Points: The peak SLB‐contributed LHF and SHF are 61.1 W/m2 in autumn and 7.4 W/m2 in winter, respectivelyThe SHF decreases significantly while LHF decreases moderately on SLB days in four seasonsThe warming effect of SLB is mainly responsible for the slump of SHF on SLB days [ABSTRACT FROM AUTHOR]

The zonal‐mean subtropical westerly jet (SWJ) in boreal winter shows a significant northward shift trend under recent climate change. Previous studies proposed thermal forcing—represented by the thermal wind associated with the temperature gradient—and the driving effect of the eddy momentum flux (EMF) convergence that leads to the eddy‐driven jet as explanations for this process; however, their relative importance in influencing the SWJ shift requires further investigation. In this study, we examined the roles of thermal forced and eddy‐driven jet components in the zonal‐mean northward SWJ shift. We also investigated the role of Hadley circulation because its poleward boundary is related to the zonal‐mean SWJ. Results suggest that thermal forced component plays a major role, while EMF‐driven component plays a secondary role. Specifically, the subtropical warming, which is primarily influenced by enhanced adiabatic downward motion of the Hadley circulation, increases the meridional temperature gradient and the associated thermal wind poleward of the SWJ. It also reduces atmospheric static stability aloft and converges the EMF on the poleward side of the climatological SWJ. Enhanced meridional temperature gradient and EMF convergence on the poleward side push the SWJ northward. Results from further mathematical analysis indicate that thermal forced and eddy‐driven zonal wind components account for 72% and 28% of the shift distance, respectively. In addition to elucidating the relative importance of thermal and EMF forcings, this study emphasizes the critical role of the subtropical warming driven by the intensified local descending branch of the Hadley circulation in shifting the zonal‐mean SWJ. Plain Language Summary: Both the thermal forced and eddy‐driven perspectives are widely used in literature to understand the northward shift of subtropical westerly jet (SWJ) under climate change. The former is related to the temperature structure, while the latter is related to the eddy momentum flux convergence. This study aims to investigate their relative importance in the northward shift of SWJ. By using a simple decomposition, this study shows that the subtropical westerly jet can be viewed as the sum of the thermal forced and eddy‐driven jet components. Results suggest that the thermal forced effect plays a major role in shifting the SWJ, while the eddy‐driven effect plays a secondary role. Here, it should be pointed out that the term thermal forced jet in this study refers in particular to the jet induced by the meridional gradient of temperature field, which is different from the term thermally driven jet caused by diabatic heating in some studies. This study can help readers grasp the main processes in understanding the SWJ shift, and therefore can be used in fields such as emergent constraints, that is, using the thermal forced jet to constrain the future projection of the SWJ. Key Points: The thermal forced (eddy‐driven) wind plays a major (secondary) role in shifting the subtropical westerly jet under recent climate changeThermal forced and eddy‐driven effects are related to subtropical warming which mainly comes from the enhanced adiabatic sinking motion [ABSTRACT FROM AUTHOR]

Turbulence in very stable boundary layers is typically unsteady and intermittent. The study implements a stochastic modeling approach to represent unsteady mixing possibly associated with intermittency of turbulence and with unresolved fluid motions such as dirty waves or drainage flows. The stochastic parameterization is introduced by randomizing the mixing lengthscale used in a Reynolds average Navier‐Stokes (RANS) model with turbulent kinetic energy closure, resulting in a stochastic unsteady RANS model. The randomization alters the turbulent momentum diffusion and accounts for sporadic events of possibly unknown origin that cause unsteady mixing. The paper shows how the proposed stochastic parameterization can be integrated into a RANS model used in weather‐forecasting and its impact is analyzed using neutrally and stably stratified idealized numerical case studies. The simulations show that the framework can successfully model intermittent mixing in stably stratified conditions, and does not alter the representation of neutrally stratified conditions. It could thus present a way forward for dealing with the complexities of unsteady flows in numerical weather prediction or climate models. Plain Language Summary: Limited computer resources lead to a simplified representation of unresolved small‐scale processes in weather forecasting and climate models, through parameterization schemes. Among the parameterized processes, turbulent fluxes exert a critical impact on the exchange of heat, water and carbon between the land and the atmosphere. Turbulence theory was, however, developed for homogeneous and flat terrain, with stationary conditions. At nighttime or in cold environment, turbulence is typically non‐stationary, weak and intermittent and the classical theory fails. Part of the intermittent mixing is due to turbulence enhancement by small‐scale wind variability. In the following, a random modeling approach is used to enhance turbulent mixing due to small‐scale wind variability and intermittency of mixing. The proposed approach is shown to be a viable approach to represent the effect of small‐scale variability of mixing for different atmospheric flow conditions. Key Points: A stochastic parameterization of turbulence is implemented in a Reynolds average Navier‐Stokes (RANS) model to represent unsteady mixingThe introduced stochastic perturbations of the mixing length enable the simulation of intermittent turbulence in the stable boundary layerThe stochastic unsteady RANS model does not alter the simulation of neutral conditions [ABSTRACT FROM AUTHOR]

Using a combination of 20‐year (1999–2018) remotely‐sensed air‐sea heat flux products and altimeter‐based eddy atlas, we investigate the signature of mesoscale eddies on sea surface temperature (SST) and air‐sea turbulent latent and sensible fluxes, or simply, turbulent heat fluxes (THFs), in the North Indian Ocean. On average, eddy‐induced THF feedback can approach ∼40 W m−2 k−1 for warm‐core anticyclones (AEs) and ∼28 W m−2 k−1 for cold‐core cyclones (CEs) at their extreme values. In addition to these conventional SSH‐SST coherent eddies and their imprints as monopoles in heat fluxes, a comparable proportion of SSH‐SST incoherent eddies (cold‐AEs and warm‐CEs) are surprisingly active in this region, which offset the monopolar paradigm of coherent eddy‐induced THF anomalies or develop a dipole structure when combined with these conventional eddies. In terms of seasonality, the aggregation of SSH‐SST coherent and incoherent eddies in the Arabian Sea develops concentrated monopoles within eddy contours in both summer and winter, with a damped THF located farther away from the eddy core in winter. In the Bay of Bengal, a strong compensation between SSH‐SST coherent and incoherent eddies is observed in summer that leads to null net fluxes, while the winter‐time THF composite of these two eddy types displays a dipolar structure which was described as eddy‐stirring effect in the literature. Plain Language Summary: The typical turbulent feature of the ocean surface, as depicted from satellite images, is often referred to as eddies that are crucial to the evolution of ocean states under climate change. With two data sources, both of which originate from satellite‐based derivations, we investigate how mesoscale eddies (with spatiotemporal scales of ∼100 km and ∼1 month) contribute to air‐sea heat exchanges and related processes in the North Indian Ocean. The seasonality of sea surface conditions is of great importance to behaviors and proportions of different eddy types in this region. Specifically, unconventional eddies, characterized as cold‐core anticyclones and warm‐core cyclones, are surprisingly active in the Arabian Sea and Bay of Bengal. This atypical feature implies that a thorough integration of dynamic and thermodynamic processes in understanding the ocean mesoscale is necessary. Key Points: Eddy‐induced SST‐THF coefficient can approach ∼40 and ∼28 W m−2 k−1 for warm anticyclones and cold cyclonesSSH‐SST incoherent eddies (warm cyclones and cold anticyclones) are comparable in number to coherent/conventional eddiesSeasonal variation of eddy compositions leads to monopolar, dipolar and canceled patterns of air‐sea net fluxes [ABSTRACT FROM AUTHOR]

The Connecticut River plume is influenced by energetic ambient tides in the Long Island Sound receiving waters. The objectives of this modeling study are (a) characterizing the spatial heterogeneity of turbulent buoyancy fluxes, (b) partitioning turbulent buoyancy fluxes into bottom‐generated and interfacial shear contributions, and (c) quantifying contributions to plume‐integrated mixing within the tidal plume. The plume formed during ambient flood tides under low river discharge, spring tides, and no winds is analyzed. Turbulent buoyancy fluxes (B) and depth‐integrated B through the plume (Bd) are characterized by pronounced spatial heterogeneity. Strong mixing (Bd ∼ 10−5‐10−4 m3/s3) occurs near the mouth, in the nearfield plume turning region, over shoals, and nearshore shallow areas. Low to moderate mixing (Bd ∼ 10−8‐10−6 m3/s3) occupies half the plume. Buoyancy fluxes are first partitioned based on the depth of the shear stress minimum between plume‐generated and bottom‐generated shear maxima. Four other tested partitioning methods are based on open channel flow and stratified shear flow parameterizations. Interfacial and bottom‐generated shear contribute to different areas of intense and moderate mixing. All methods indicate a significant plume mixing role for bottom‐generated mixing, but interfacial mixing is a bigger contributor. Plume‐integrated total and interfacial mixing peak at max ambient flood and the timing of peak bottom‐generated mixing varies among partitioning methods. Two‐thirds of the mixing occurs in concentrated intense mixing areas. A parameter space with the ambient tidal Froude number and plume thickness to depth ratio as axes indicates many tidally modulated plumes are moderately to dominantly influenced by bottom‐generated tidal mixing. Plain Language Summary: A plume of freshwater flows from the Connecticut River into Long Island Sound. Strong tidal currents influence the plume. How freshwater river plumes mix is an important area of research. This study explores where mixing occurs in the plume and which processes contribute to the mixing. A realistic computer simulation of the Connecticut River plume is analyzed. The strongest mixing areas are near the river mouth, in an area beyond the mouth where the plume turns, and over shallow waters. Mixing created by faster plume speeds relative to the surrounding waters is the most important contributor. Mixing driven by tidal currents interacting with the stationary bottom is a significant secondary contributor. The importance of this tidal contribution increases for faster tidal flow and plumes reaching closer to the bottom. Key Points: Turbulent buoyancy fluxes span several orders of magnitude over the river plumePlume‐generated interfacial shear is the most important mixing contributor overallBottom‐generated mixing importance increases with tidal currents and plume thickness [ABSTRACT FROM AUTHOR]

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

Parameterization of subgrid‐scale processes is a major source of uncertainty in global atmospheric model simulations. Global storm‐resolving simulations use a finer grid (less than 5 km) to reduce this uncertainty by explicitly resolving deep convection and details of orography. This study uses machine learning to replace the physical parameterizations of heating and moistening rates, but not wind tendencies, in a coarse‐grid (200 km) global atmosphere model, using training data obtained by spatially coarse‐graining a 40‐day realistic geography global storm‐resolving simulation. The training targets are the three‐dimensional fields of effective heating and moistening rates, including the effect of grid‐scale motions that are resolved but imperfectly simulated by the coarse model. A neural network is trained to predict the time‐dependent heating and moistening rates in each grid column using the coarse‐grained temperature, specific humidity, surface turbulent heat fluxes, cosine of solar zenith angle, land‐sea mask and surface geopotential of that grid column as inputs. The coefficient of determination R2 for offline prediction ranges from 0.4 to 0.8 at most vertical levels and latitudes. Online, we achieve stable 35‐day simulations, with metrics of skill such as the time‐mean pattern of near‐surface temperature and precipitation comparable or slightly better than a baseline simulation with conventional physical parameterizations. However, the structure of tropical circulation and relative humidity in the upper troposphere are unrealistic. Overall, this study shows potential for the replacement of human‐designed parameterizations with data‐driven ones in a realistic setting. Plain Language Summary: Numerical models used for projecting climate change impacts must use ad‐hoc assumptions about the effects of unresolved small‐scale processes. These assumptions contribute to uncertainty in predicting how rainfall and temperature will change in the future. Expensive fine‐grid simulations which eliminate the need for some of these assumptions are possible to run for shorter (month‐to year‐long) duration. We use such a simulation to train a data‐driven representation of the effects of processes, like clouds, which are poorly simulated by a cheaper coarse‐grid model. The data‐driven representation (a neural network) predicts rates of temperature and moisture change in each column using inputs from that grid column. This approach has been previously shown to work for models with idealized boundary conditions, but not for the realistic setting we use. When this neural network is used in a coarse‐resolution model, the realism of many global skill metrics is as good or better than a baseline model with traditional representation of small‐scale processes. However, some features are degraded, such as the time‐evolving pattern of rainfall in the tropics and humidity in the upper atmosphere. This work is a first step toward the use of data‐driven representations of unresolved processes in realistic global atmospheric models. Key Points: Effective sources of heat and moisture are computed from a global storm‐resolving simulation accounting for semi‐resolved dynamicsA neural network is trained to predict columns of the effective sources using profiles of temperature and specific humidityWhen used online, stable month‐long simulations are possible although skill is not yet comparable to a previous corrective approach [ABSTRACT FROM AUTHOR]

Data plays a central role in data‐driven methods, but is not often the subject of focus in investigations of machine learning algorithms as applied to Earth System Modeling related problems. Here we consider the problem of eddy‐mean interaction in rotating stratified turbulence in the presence of lateral boundaries, where it is known that rotational components of the eddy flux plays no direct role in the sub‐grid forcing onto the mean state variables, and its presence is expected to affect the performance of the trained machine learning models. While an often utilized choice in the literature is to train a model from the divergence of the eddy fluxes, here we provide theoretical arguments and numerical evidence that learning from the eddy fluxes with the rotational component appropriately filtered out, achieved in this work by means of an object called the eddy force function, results in models with comparable or better skill, but substantially reduced sensitivity to the presence of small‐scale features. We argue that while the choice of data choice and/or quality may not be critical if we simply want a model to have predictive skill, it is highly desirable and perhaps even necessary if we want to leverage data‐driven methods to aid in discovering unknown or hidden physical processes within the data itself. Plain Language Summary: Data‐driven methods are increasingly being utilized in various problems relating to the numerical modeling of the Earth system. While there are many investigations focusing on the machine learning algorithms or the problems themselves, there have been relative few investigations into the impact of data choice or quality, given the central role of data. We consider here the impact of the choice of data for a particular problem relevant to ocean modeling, that of eddy‐mean interaction, where it is known that the training data generically contains a component that plays no role in the eddy‐mean interaction, and its presence in the training phase is expected to degrade the model performance. We provide arguments and evidence that one choice is preferable over a more standard choice utilized in related research. While the choice of data choice and/or quality may not be critical if we simply want a data‐driven model to be skillful, we argue it is highly desirable, possibly even a necessity, if we want to leverage data‐driven methods as a means to aid in discovery of unknown or hidden physical processes within the data itself. Key Points: Investigated the dependence of convolution neural networks on the choice of training data for geostrophic turbulenceModels are trained on eddy fluxes with rotational component filtered out by means of an eddy force functionResulting models as accurate but less sensitive to small‐scale features than models trained on divergence of eddy fluxes [ABSTRACT FROM AUTHOR]

Internal waves drive ocean mixing and enhance the transport of heat, momentum and other tracers in shelf seas. We collected observations of mixing over a 30‐day period from three cross‐shore moorings placed on the 330, 200 and 150 m isobaths on the offshore side of a pelagic ridge on the Australian North West Shelf. The region is forced by energetic surface and internal tides, exhibits non‐linear internal waves, experiences flow‐topography interactions, and is subject to episodic intense wind events. This complex forcing drove energetic diapycnal mixing at all sites. We identified five dominant internal wave forcing categories: mode‐1 waves at low‐frequency (time scales from double the buoyancy period to 4 hr), mode‐1 waves at high‐frequency (HF) (time scales between the buoyancy period and double the buoyancy period), mode‐2 waves, internal bores, and internal hydraulic jumps. Overall, just 15% of mixing events accounted for 90% of the total observed heat flux over the record. Mixing during internal wave events accounted for as much as 50% of the total heat flux in some locations. Of the internal wave categories, HF mode‐1 waves were the most significant contributors to the total heat flux at all sites (∼20%). On the other hand, internal bores made significant contributions to mixing only at the 200 and 150 m moorings; they made no contribution to mixing at the 330 m mooring. At the shallowest mooring, the different internal wave categories all made similar contributions to the total flux, indicating an increasingly complicated relationship between the evolving internal wavefield and the mixing. Plain Language Summary: Internal waves propagate along the density gradients found beneath the ocean's surface layer, analogous to surface waves propagating along the sharp density gradient where air and water meet. These waves play an important role in the distribution of nutrients, heat, contaminants, and other tracers in the ocean, especially in coastal regions where the waves break. The density structure of the ocean, the tidal and wind forcing, and the seabed features result in many different types of internal waves, each of which travel and break differently. In this work, we examine the mixing caused by different types of internal waves as they travel up and over a subsurface ridge on the Australian North West Shelf. We found that most of the significant mixing resulted from relatively rare events, which often occurred during internal wave forcing events. The magnitude of mixing increased in shallower waters due to internal waves breaking and causing energetic turbulent flows. However, the wave types that were the most significant for mixing changed depending on the location on the shelf and the depth. High‐frequency internal waves were generally the most significant contributor to mixing. Internal bores, a class of waves moving upslope near the seabed, did dominate the total ocean mixing near‐bottom at some locations. Key Points: Energetic but short‐lived nonlinear internal wave events drove most of the vertical turbulent heat flux over the month‐long recordInternal wave events evolved over relatively short time scales and relatively short spatial scalesEnergetic internal wave events contribute significantly to mixing in shelf seas [ABSTRACT FROM AUTHOR]

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

Latent and sensible heat flux observations are essential for understanding land–atmosphere interactions. Measurements from the eddy covariance technique are widely used but suffer from systematic energy imbalance problems, partly due to missing large eddies from sub‐mesoscale transport. Because available energy drives the development of large eddies, we propose an available energy based correction method for turbulent flux measurements. We apply our method to 172 flux tower sites and show that we can reduce the energy imbalance from −14.99 to −0.65 W m−2 on average, together with improved consistency between turbulent fluxes and available energy and associated increases in r2 at individual sites and across networks. Our results suggest that our method is conceptually and empirically preferable over the method implemented in the ONEFlux processing. This can contribute to the efforts in understanding and addressing the energy imbalance issue, which is crucial for the evaluation and calibration of land surface models. Plain Language Summary: Eddy covariance measurements are key to understanding the exchange of energy and water between the Earth's surface and the atmosphere, which helps us validate Earth system models that predict how the land interacts with the atmosphere. However, these measurements often show an energy imbalance problem, meaning that the measured turbulent energy does not fully account for all the energy entering the system. For two decades, scientists have been using advanced simulations and multi‐tower measurements to find out why this happens, and have found that the movements of airflow in a horizontal direction play a large role. Taking this knowledge into account, we propose a simple, data‐driven method to make these measurements more accurate. This new approach reduces the error not just at one eddy covariance site, but at multiple sites around the globe, and it's also effective at reflecting the energy changes that occur with daily weather events like rain. Key Points: Observed systematic imbalance of energy flux (∼17%) across the network of eddy covariance sitesA theoretically motivated correction method based on available energy variations is proposedThe available energy correction method has conceptual and empirical advantages compared to the method implemented in the ONEFlux pipeline [ABSTRACT FROM AUTHOR]

How convective boundary‐layer (CBL) processes modify fluxes of sensible (SH) and latent (LH) heat and CO2 (Fc) in the atmospheric surface layer (ASL) remains a recalcitrant problem. Here, large eddy simulations for the CBL show that while SH in the ASL decreases linearly with height regardless of soil moisture conditions, LH and Fc decrease linearly with height over wet soils but increase with height over dry soils. This varying flux divergence/convergence is regulated by changes in asymmetric flux transport between top‐down and bottom‐up processes. Such flux divergence and convergence indicate that turbulent fluxes measured in the ASL underestimate and overestimate the "true" surface interfacial fluxes, respectively. While the non‐closure of the surface energy balance persists across all soil moisture states, it improves over drier soils due to overestimated LH. The non‐closure does not imply that Fc is always underestimated; Fc can be overestimated over dry soils despite the non‐closure issue. Plain Language Summary: Large swirling motions, called large turbulent eddies, efficiently transport water vapor, carbon dioxide, and heat up and down throughout the convective boundary layer (CBL). To what extent scalar fluxes in the atmospheric surface layer (ASL) are modulated by large turbulent eddies from the top of the CBL (i.e., top‐down eddies) remains a recalcitrant problem in many fields spanning atmospheric sciences, hydrology, ecology, and climate change. Here, high‐resolution computational simulations of the CBL show that scalar fluxes in the ASL linearly change with height across soil wetness conditions largely due to changes in the interactions of top‐down processes and bottom‐up surface exchange. Such linear height‐dependence of the fluxes indicates that reported fluxes from direct turbulent measurements in the ASL are not identical to their sought surface values. As a result, the non‐closure of the surface energy balance occurs across all soil moisture conditions but improves as soil becomes dry. CO2 measured fluxes are underestimated over wet soils and overestimated over dry soils, which has its implication when interpreting CO2 exchanges from global flux measuring networks utilizing turbulence theories. Height dependence of fluxes, which confirms that the constant flux layer assumption is not routinely satisfied, is a fundamental reason for the non‐closure. Key Points: Asymmetric flux transport by bottom‐up and top‐down processes leads to varying flux divergence/convergence (FDC) in the surface layerLatent heat and CO2 fluxes are underestimated when soil is wet and overestimated when dry, but sensible heat flux is always underestimatedNon‐closure of the surface energy balance is regulated by varying FDC and improves for dry soils due to overestimated latent heat flux [ABSTRACT FROM AUTHOR]

Atmospheric numerical models play a crucial role in operational weather forecasting, as well as in improving our understanding of atmospheric dynamics via research studies. Maximising their accuracy is of paramount importance. Use of advective flux schemes greater than O7 in atmospheric models is largely undocumented, with no studies considering O3–O17 fluxes with formal accuracy‐preserving high‐order interpolation, pressure gradient/divergence, and subgrid‐scale (SGS) turbulent fluxes. Higher‐order numerical approximations can reduce truncation, amplitude and phase errors, and potentially improve model accuracy and effective resolution. Here, simulations are presented using very‐high‐order O3–O17 fluxes, with/without high‐order O2–O18 Lagrangian interpolations, pressure gradient/divergence approximations, and SGS turbulent fluxes for a two‐dimensional, highly‐viscous (Re ∼ 100) diffusion‐limited, nonlinear colliding‐plumes problem using 25–200 m spatial resolutions. The highest‐order flux schemes coupled with higher‐order interpolations, pressure gradient/divergence and SGS flux approximations produced the best solutions, with higher‐order fluxes and interpolations being most important. Overall solution convergence of order about O1–O2 with mode‐split (fast sound/slow advective waves) O3 Runge–Kutta temporal schemes was negatively impacted by order at most O1 temporal convergence with SGS fluxes, divergence damping, and especially spatial filters, compared to about order O3 convergence with these inactivated. While very‐high‐order schemes were shown to improve solution accuracy, few cost‐effective higher‐order highly‐viscous test problem solutions (higher order vs finer resolution) were found using theoretical floating‐point operations (FPO) with Courant‐Friedrichs‐Lewy (CFL)‐limited or constant stable Courant number‐based time steps. However, employing central processing unit (CPU) time, rather than FPOs, demonstrated there was reduced computational burden using higher‐order approximations. We conclude that O9–O17 flux schemes with or without high‐order (≥O4) interpolations, pressure gradient/divergence approximations, and SGS fluxes can improve atmospheric model solution accuracy, without prohibitive computation costs, compared to O3–O7 flux with O2 interpolations, pressure gradient/divergence approximations, and SGS fluxes. [ABSTRACT FROM AUTHOR]