Eli Tziperman

Conifer forests span some of the most climatically contrasting environments on Earth, from energy-limited Boreal systems to water-limited semi-arid ecosystems. Whether their carbon uptake is governed by universal drivers or by site-specific boundary conditions remains unresolved. Using more than two decades of eddy-covariance and multi-depth soil moisture measurements from two climatic end-members of evergreen needleleaf forests, Hyytiälä, Finland (Boreal) and Yatir, Israel (semi-arid Mediterranean), we isolate the ecophysiological controls on carbon uptake by restricting the analysis to photosynthetically active radiation (PAR)-saturated conditions and explicitly separating seasonal dynamics from daily residual variability. For each dataset, we apply Random Forest modelling (tested against baseline Generalized Linear & Additive Models) with SHAP analysis to identify dominant drivers and environmental thresholds. At the seasonal scale, NEP was governed by distinct boundary conditions in each forest. In Hyytiälä, precipitation had dominant control, sustaining evapotranspiration and reflecting a radiation regime characterized by high diffuse fractions. In Yatir, deep soil water availability controlled both the timing and magnitude of productivity, with a critical threshold at ∼15.9 %vol in the deepest measured layer (∼45 cm). This threshold marked the transition from dry-season legacy constraints, where vertical soil potential gradients limit root uptake, to conditions permitting sustained transpiration and productivity. At the daily residual scale, both forests showed strong sensitivity to shortwave radiation and vapour pressure deficit (VPD), despite contrasting climatologies. Elevated VPD reduced peak daily productivity by more than 50% at both sites, although sufficient deep soil moisture mitigated this effect in the semi-arid forest. Notably, both forests exhibited a similar optimal air temperature range (14–20 °C), indicating a conserved physiological optimum despite divergent hydroclimatic limitations. Our results demonstrate that carbon uptake in evergreen needleleaf forests is structured by site-specific hydrological boundary conditions at seasonal scales, while atmospheric stress regulates short-term variability. This scale-dependent hierarchy of controls challenges the notion of universal productivity drivers and highlights the importance of subsurface hydrology and rainfall regime characteristics for predicting forest carbon responses to climate change.

Abstract The past few decades of work on stratosphere–troposphere teleconnections have unearthed a variety of different time scales of both upward and downward propagation and their connection to weather at the surface. In an attempt to identify significant patterns of covariance between the surface and the stratosphere without imposing an expected pattern or time scale, we apply maximum covariance analysis (MCA) with a variable time lag between pairs of tropospheric and stratospheric fields. Using over 60 years of ERA5 reanalysis for Northern Hemisphere winters, we use MCA to pick out the time lags and patterns corresponding to the largest covariance between the surface and the stratosphere. By applying new methods to an existing problem, we both verify certain results from previous literature and unearth new insights into the nature of stratosphere–troposphere teleconnections. We find that the greatest covariance occurs when the surface precedes the stratosphere by up to 9 days, corresponding to a sea level pressure anomaly with one pole over the Gulf of Alaska and another over the Ural blocking high that is followed by changes in stratospheric potential vorticity, zonal wind, and Eliassen–Palm (EP) flux. We find evidence for a downward influence of stratospheric potential vorticity and zonal wind on sea level pressure at a time scale of 3–4 days, with a secondary influence from zonal wind alone at 2–3 weeks. The downward influence is characterized by a weaker (stronger) polar vortex followed by anomalously high (low) sea level pressures over the Arctic Ocean, but it does not produce an appreciable anomaly in minimum surface temperatures. Significance Statement We seek to improve both predictability and fundamental understanding of the linkages between the troposphere, the convectively active layer of the atmosphere responsible for weather, and the stratosphere, the much more stable region just above it. We identify a key time scale of upward influence from the surface to the stratosphere of just over 1 week with distinct precursors at the surface. We also find a downward influence of the stratosphere on the surface at two time scales, the shorter about 3 days and the longer 2–3 weeks. However, this downward influence does not extend to a noticeable impact on minimum surface temperatures.

Evergreen needleleaf forests span a wide climatic range, yet their carbon sequestration is increasingly constrained by climate-driven environmental limits. Building on results presented at EGU 2025, which showed a shift in the dominant seasonal control on productivity from atmospheric moisture in the Boreal Hyytiälä forest (Finland, HYY) to soil moisture in the semi-arid Yatir forest (Israel, YAT), we identify the environmental boundary conditions underlying this contrast.Using PAR-saturated conditions to isolate eco-physiological controls on productivity, we derive key climatic and hydrological thresholds from SHAP-based analyses. In YAT, productivity is strongly constrained by deep soil water availability, with a clear threshold at ~15.8 %vol in the deepest measured soil layer (~45 cm). This threshold reflected a seasonal transition where deep soil moisture shifts from limiting productivity (ineffective water retention and root resistance) to supporting shallow root water uptake and productivity during the wet season. This transition coincides with the seasonal minimum in soil temperature imposing peak root resistance, indicating a compounded control on the onset of productivity in this water-limited ecosystem.In contrast, seasonal productivity in HYY is dominated by precipitation, which both sustains evapotranspiration, closely linked to net ecosystem productivity (R=0.96), and likely reflects a favorable cloud and radiation regime. The high historical ratio of diffuse to direct shortwave radiation in HYY (Sdiff:S ~ 3:4) helps to buffer canopy conductance against high vapor pressure deficit (VPD), consistent with the high sensitivity observed at this site (negative productivity response at VPD > 1 kPa). Such atmospheric constraints are lacking in YAT, where diffuse radiation is limited (Sdiff:S ~ 1:4) and VPD shows an order of magnitude larger range.Despite adaptation to such contrasting environments, both forests exhibit a similar optimal air temperature range for productivity (14–20 °C), which highlights a shared physiological optimum across the divergent environmental limitations. Overall, our results demonstrate that carbon sequestration in these systems is not controlled by universal drivers, but by site-specific boundary conditions, such as deep soil water availability in semi-arid Mediterranean forests and precipitation-linked atmospheric regimes in Boreal forests.

The equatorial jets observed on the Jovian planets—Jupiter, Saturn, Uranus, and Neptune—exhibit extreme zonal flow patterns, manifesting as either strongly prograde (in the gas giants) or strongly retrograde (in the ice giants). Existing theories have often treated gas giants and ice giants separately, primarily focusing on the differences between deep and shallow dynamics. However, gravity measurements from the Juno spacecraft have revealed that Jupiter's convective envelope may share similarities with those of the ice giants, challenging traditional distinctions between these planetary types and highlighting the potential for a unified explanation.We present results from a convection-driven anelastic General Circulation Model that introduces a unifying mechanism to explain the equatorial jets on all four Jovian planets. In these simulations, the convective dynamics and planetary rotation drive the formation of tilted convection columns that extend cylindrically from the deep interior to the outer atmospheric layers. These columns play a crucial role in shaping zonal wind patterns, with the tilting of the convection columns introducing asymmetries in momentum transport that lead to the bifurcation of the flow into either superrotation (prograde jets) or subrotation (retrograde jets) in the equatorial region.Through a detailed analysis of the convection-driven columnar structures, we demonstrate that the equatorial wave properties and the leading-order momentum balance share remarkable similarities across different planetary types. Our findings comprehensively explain the potential for both equatorial superrotation and subrotation under constant physical conditions, thereby elucidating the diverse zonal wind patterns observed on the Jovian planets and providing deeper insight into the mechanisms driving equatorial jet formation. Furthermore, the Juno Microwave Radiometer (MWR) may provide evidence for such tilted convection structures, underscoring the necessity of a thorough understanding of their dynamical contributions.

There is a long history of studies of potential interactions between the El Niño–Southern Oscillation (ENSO) and the quasi-biennial oscillation (QBO). Some suggested that ENSO may modulate QBO phase transitions or amplitude, although identifying a straightforward correlation of the two variability modes has been elusive. Recent studies showed some interesting connections between the surface composites of the two modes, sea surface temperature in particular. However, the observed record is short and noisy, raising the question whether such patterns reflect a robust dynamical coupling or a statistical artifact. In this talk, I will show the observed patterns from ERA5 show and therefore imply. Additionally, I will then discuss how the various high-top CMIP6 models produce (or do not produce) the observed signal. By comparing model output with observations, we assess the extent to which apparent correlations are reproducible by this physical mechanism or can be identified as an artifact.

Internal modes of climate variability, such as El Niño and the North Atlantic Oscillation, can have a strong influence on distant weather patterns, effects that are referred to as “teleconnections”. The extent to which anthropogenic climate change has and will continue to affect these teleconnections, however, remains uncertain. Here, we employ a covariance fingerprinting approach to demonstrate that shifts in teleconnection patterns affecting monthly temperatures between the periods 1960–1990 and 1990–2020 are attributable to anthropogenic forcing. We further apply multilinear regression to assess the regional contributions and statistical significance of changes in five key climate modes: the El Niño–Southern Oscillation, North Atlantic Oscillation, Southern Annular Mode, Indian Ocean Dipole, and the Pacific Decadal Oscillation. In many regions, observed changes exceed what would be expected from natural variability alone, further implicating an anthropogenic influence.

Abstract Internal modes of climate variability, such as El Niño and the North Atlantic Oscillation (NAO), can have strong influences upon distant weather patterns, effects that are referred to as “teleconnections.” The extent to which anthropogenic climate change has and will continue to affect these teleconnections, however, remains uncertain. Here, we employ a covariance fingerprinting approach to demonstrate that shifts in teleconnection patterns affecting monthly temperatures between the periods 1960–1990 and 1990–2020 are attributable to anthropogenic forcing. We further apply multilinear regression to assess the regional contributions and statistical significance of changes in five key climate modes: the El Niño‐Southern Oscillation, NAO, Southern Annular Mode, Indian Ocean Dipole, and the Pacific Decadal Oscillation. In many regions, observed changes exceed what would be expected from natural variability alone, further implicating an anthropogenic influence. Finally, we provide projections of how these teleconnections will alter in response to further changes in climate.

<strong class="journal-contentHeaderColor">Abstract.</strong> Westerly wind bursts (WWBs) have long been known to have a major impact on the development of El Ni&ntilde;o events. In particular, they amplify these events, with stronger events associated with a higher number of WWBs. We further find indications that WWBs lead to a more monotonically increasing evolution of warming events. We consider here a noise-driven recharge oscillator model of ENSO. Commonly, WWBs are represented by a state-dependent Gaussian noise which naturally reproduces the amplification of warm events. However, we show that many properties of WWBs and their effects on sea surface temperature (SST) are not well captured by such Gaussian noise. Instead, we show that conditional additive and multiplicative (CAM) noise presents a promising alternative. In addition to recovering the sporadic nature of WWBs, CAM noise leads to an asymmetry between El Ni&ntilde;o and La Ni&ntilde;a events without the need for deterministic nonlinearities. Furthermore, CAM noise generates a more monotonic increase of extreme warming events with a higher frequency of WWBs accompanying the largest events. This suggests that extreme warm events are better modelled by CAM noise. To cover the full spectrum of warm events we propose a conditional noise model in which the wind stress is modelled by additive Gaussian noise for sufficiently small SSTs and by additive CAM noise once the SST exceeds a certain threshold. We show that this conditional noise model captures the observed properties of WWBs reasonably well.

Extreme El Niño events, such as occurred in 1997--1998, can induce severe weather on a global scale, with significant socioeconomic impacts that motivate efforts to understand them better. However, extreme El Niño events are rare, and even in a very long direct numerical simulation (DNS) occur too infrequently for robust statistical characterization. This study seeks to generate extreme El Niño event model data at a lower cost, while preserving statistical fidelity, using a rare event sampling technique, which preferentially devotes computational resources toward extreme events by generating a large, branched ensemble of interrelated trajectories through successive targeted perturbations. We specifically use the ``trying-early adaptive multi-level splitting'' (TEAMS) algorithm, which is well-suited for El Niño's relative timescales of predictability and event duration. We apply TEAMS to the Zebiak-Cane model, an intermediate-complexity ENSO model for which it is feasible to run a long DNS (500000 years) for validation. We compare extreme El Niño event return time estimates from TEAMS to those from the long DNS to assess TEAMS' accuracy and efficiency. We find that TEAMS accurately reproduces the return time estimates of the DNS at about one fifth the computational cost. Therefore, TEAMS is an efficient approach to study rare ENSO events that can be plausibly applied to full-complexity climate models.

Extreme El Niño events, such as occurred in 1997--1998, can induce severe weather on a global scale, with significant socioeconomic impacts that motivate efforts to understand them better. However, extreme El Niño events are rare, and even in a very long direct numerical simulation (DNS) occur too infrequently for robust statistical characterization. This study seeks to generate extreme El Niño event model data at a lower cost, while preserving statistical fidelity, using a rare event sampling technique, which preferentially devotes computational resources toward extreme events by generating a large, branched ensemble of interrelated trajectories through successive targeted perturbations. We specifically use the ``trying-early adaptive multi-level splitting'' (TEAMS) algorithm, which is well-suited for El Niño's relative timescales of predictability and event duration. We apply TEAMS to the Zebiak-Cane model, an intermediate-complexity ENSO model for which it is feasible to run a long DNS (500000 years) for validation. We compare extreme El Niño event return time estimates from TEAMS to those from the long DNS to assess TEAMS' accuracy and efficiency. We find that TEAMS accurately reproduces the return time estimates of the DNS at about one fifth the computational cost. Therefore, TEAMS is an efficient approach to study rare ENSO events that can be plausibly applied to full-complexity climate models.

Westerly wind bursts (WWBs) have long been known to have a major impact on the development of El Niño events. In particular, they amplify these events, with stronger events associated with a higher number and stronger WWBs. We consider here a noise-driven recharge oscillator model of ENSO. Commonly, WWBs are represented by a state-dependent Gaussian noise that naturally reproduces the amplification of warm events. However, we show that many properties of WWBs and their effects on sea surface temperature (SST) are better captured by a conditional additive and multiplicative (CAM) noise, which presents a promising alternative to represent WWBs. In addition to recovering the sporadic nature of WWBs, CAM noise leads to an asymmetry between El Niño and La Niña events without the need for deterministic nonlinearities. Furthermore, CAM noise generates SST dynamics with a higher frequency of WWBs accompanying the largest events. This suggests that extreme warm events are better modelled by CAM noise. To cover the full spectrum of warm events, we propose a conditional noise model in which the wind stress is modelled by additive Gaussian noise for sufficiently small SSTs and by additive CAM noise once the SST exceeds a certain threshold. We show that this conditional noise model captures observed bulk statistical properties of ENSO equally well as the commonly used multiplicative Gaussian red noise model, but additionally better reproduces dynamical signatures such as the increased number of WWBs preceding large El Niño events.

Internal modes of climate variability, such as El Niño and the North Atlantic Oscillation, can have strong influences upon distant weather patterns, effects that are referred to as "teleconnections". The extent to which anthropogenic climate change has and will continue to affect these teleconnections, however, remains uncertain. Here, we employ a covariance fingerprinting approach to demonstrate that shifts in teleconnection patterns affecting monthly temperatures between the periods 1960-1990 and 1990-2020 are attributable to anthropogenic forcing. We further apply multilinear regression to assess the regional contributions and statistical significance of changes in five key climate modes: the El Niño-Southern Oscillation, North Atlantic Oscillation, Southern Annular Mode, Indian Ocean Dipole, and the Pacific Decadal Oscillation. In many regions, observed changes exceed what would be expected from natural variability alone, further implicating an anthropogenic influence. Finally, we provide projections of how these teleconnections will alter in response to further changes in climate.

Westerly wind bursts (WWBs) have long been known to have a major impact on the development of El Niño events. In particular, they amplify these events, with stronger events associated with a higher number and stronger WWBs. We consider here a noise-driven recharge oscillator model of ENSO. Commonly, WWBs are represented by a state-dependent Gaussian noise that naturally reproduces the amplification of warm events. However, we show that many properties of WWBs and their effects on sea surface temperature (SST) are better captured by a conditional additive and multiplicative (CAM) noise, which presents a promising alternative to represent WWBs. In addition to recovering the sporadic nature of WWBs, CAM noise leads to an asymmetry between El Niño and La Niña events without the need for deterministic nonlinearities. Furthermore, CAM noise generates SST dynamics with a higher frequency of WWBs accompanying the largest events. This suggests that extreme warm events are better modelled by CAM noise. To cover the full spectrum of warm events, we propose a conditional noise model in which the wind stress is modelled by additive Gaussian noise for sufficiently small SSTs and by additive CAM noise once the SST exceeds a certain threshold. We show that this conditional noise model captures observed bulk statistical properties of ENSO equally well as the commonly used multiplicative Gaussian red noise model, but additionally better reproduces dynamical signatures such as the increased number of WWBs preceding large El Niño events.

Internal modes of climate variability, such as El Niño and the North Atlantic Oscillation, can have strong influences upon distant weather patterns, effects that are referred to as "teleconnections". The extent to which anthropogenic climate change has and will continue to affect these teleconnections, however, remains uncertain. Here, we employ a covariance fingerprinting approach to demonstrate that shifts in teleconnection patterns affecting monthly temperatures between the periods 1960-1990 and 1990-2020 are attributable to anthropogenic forcing. We further apply multilinear regression to assess the regional contributions and statistical significance of changes in five key climate modes: the El Niño-Southern Oscillation, North Atlantic Oscillation, Southern Annular Mode, Indian Ocean Dipole, and the Pacific Decadal Oscillation. In many regions, observed changes exceed what would be expected from natural variability alone, further implicating an anthropogenic influence. Finally, we provide projections of how these teleconnections will alter in response to further changes in climate.

The equatorial jets dominating the dynamics of the Jovian planets exhibit two distinct types of zonal flows: strongly eastward in the gas giants (superrotation) and strongly westward in the ice giants (subrotation). Existing theories propose different mechanisms for these patterns, but no single mechanism has successfully explained both. However, the planetary parameters of the four Solar System giant planets suggest that a fundamentally different mechanism is unlikely. In this study, we show that convection-driven columnar structures can account for both eastward and westward equatorial jets, framing the phenomenon as a bifurcation. Consequently, both superrotation and subrotation emerge as stable branches of the same mechanistic solution. Our analysis of these solutions uncovers similarities in the properties of equatorial waves and the leading-order momentum balance. This study suggests that the fundamental dynamics governing equatorial jet formation may be more broadly applicable across the Jovian planets than previously believed, offering a unified explanation for their two distinct zonal wind patterns.

Abstract Nitrogen and phosphorus are the two macro-nutrients that limit biological productivity in the ocean. While the supply of P depends on geological processes, N is biologically supplied from an inexhaustible atmospheric source, but can be limited by micro-nutrients, especially iron. Here we present a record of N and C isotopes over the past 165 Ma in marine sediments to address feedbacks between the N-cycle and productivity. Over most of the last 165 Myr, the fixed N averaged +3.2‰, (−2 and +9‰), but higher in distal areas of the ocean due to limited vertical mixing. Using an isotope box model and a coupled climate model we show that this is caused by winds that induce upwelling changing due to continental meander. Upwelling along low latitude east-west orientated Tethyan coastlines results in low δ 15 N, while upwelling along narrow N-S coastlines as it does today, results in high δ 15 N due to denitrification.

Abstract Despite evidence for interactions between the El Niño‐Southern Oscillation (ENSO) and the Quasi‐Biennial Oscillation (QBO), the correlation between their indices is elusive and unstable over the observational record. We show that in ERA5, DJF composites of La Niña sea‐surface temperatures (SSTs) are positively correlated with SST composites of the QBO's easterly phase (QBOE), and DJF El Niño SST anomalies are correlated with those of the QBO's westerly phase (QBOW). These correlations change coherently with season; the La Niña/QBOE correlation turns strongly negative in May. QBO and ENSO composites of the surface fluxes of latent heat, the surface absorbed short wave radiation, and the outgoing longwave radiation, are also highly correlated, again with a coherent annual cycle. These findings strengthen the evidence for interactions between ENSO and the QBO, highlighting the role of the seasonal cycle, and may be relevant to the interactions of the QBO and the Madden‐Julian Oscillation.

Abstract The recharge oscillator (RO) model has been successfully used to understand different aspects of the El Niño‐Southern Oscillation (ENSO). Fitting the RO to observations and climate model simulations consistently suggests that ENSO is a damped oscillator whose variability is sustained and made irregular by external weather noise. We investigate the methods that have been used to estimate the growth rate of ENSO by applying them to simulations of both damped and self‐sustained RO regimes. We find that fitting a linear RO leads to parameters that imply a damped oscillator even when the fitted data were produced by a model that is self‐sustained. Fitting a nonlinear RO also leads to a significant bias toward the damped regime. As such, it seems challenging to decide whether ENSO is a damped or a self‐sustained oscillation by fitting such models to observations, and the possibility that ENSO is self‐sustained cannot be ruled out.

The equatorial jets dominating the dynamics of the Jovian planets exhibit two distinct types of zonal flows: strongly eastward (superrotation) and strongly westward (subrotation). Existing theories propose different mechanisms for these patterns on gas giants and ice giants, but no single mechanism has successfully explained both. However, the planetary parameters of the four Solar System giant planets suggest that a fundamentally different mechanism is unlikely. In this study, we demonstrate that a convection-driven columnar structure can explain the equatorial jets on all four Jovian planets, framing the problem as a bifurcation phenomenon. Consequently, both superrotation and subrotation emerge as stable branches of the same mechanistic solution. Our analysis of these solutions uncovers similarities in the properties of equatorial waves and the leading-order momentum balance. This study reveals that the underlying dynamics of equatorial jet formation are more universally applicable across the Jovian planets than previously thought, providing a unified explanation for their two distinct zonal wind patterns.

Abstract In the warm, equable climate of the Eocene, constraints on CO 2 levels and low-latitude temperatures have generally precluded climate models from recreating key features of the climate, especially the above-freezing winter temperatures in the continental interiors suggested by fossil evidence of frost-intolerant species at high latitudes. Several cloud feedbacks have been suggested as mechanisms for enhanced wintertime warming, including a breakup of subtropical stratocumulus cloud decks at high CO 2 concentrations. It has been suggested that this breakup could lead to 8 K of global average warming, but how this low-latitude cloud feedback translates to high-latitude warming is not obvious and warrants quantification with a global climate model. In this study, we use cloud-locking experiments in the Community Earth System Model, version 2 (CESM2), in which homogeneous subtropical stratocumulus clouds are prescribed or completely removed to investigate the maximum warming achieved by a breakup of subtropical stratocumulus clouds in both a preindustrial and a high CO 2 climate. We use the present-day continental configuration and vegetation to make these results applicable to a future warm climate. We find that in the most dramatic case, the stratocumulus breakup leads to a significant globally averaged warming of about 4.5 K and contributes to some reduction in below-freezing days in the continental interiors at high latitudes. The resulting warming is limited by stabilizing low-cloud feedbacks induced elsewhere following the breakup. We conclude that a stratocumulus breakup may have played a nonnegligible role in past warm climates, even if it cannot, on its own, explain the key features of the Eocene.

Abstract Changes in extreme weather events are a potentially important aspect of anthropogenic climate change (ACC), yet they are difficult to attribute to ACC because the record length is often similar to, or shorter than, extreme-event return periods. This study is motivated by the “World Weather Attribution” (WWA) initiative and, specifically, their approach of fitting extreme value distribution functions to local observations. They calculate the dependence of distribution parameters on global mean surface temperature (GMST) and use this dependence to attribute extreme events to ACC. Applying this method to preindustrial climate simulations with no time-varying greenhouse gas forcing, we still find a strong dependence of distribution parameters on GMST. This dependence results from internal climate variability (e.g., ENSO) affecting both extreme events and GMST. Therefore, dependence on GMST does not necessarily imply an effect of ACC on extremes. We further consider whether an extreme value, normal, or lognormal distribution better represents the data, if a GMST dependence of distribution parameters is justified using a likelihood ratio test, and if a meaningful attribution is possible given uncertainties in GMST dependence. We find, for example, that an attribution of Australia’s 2020–21 bushfires to ACC is difficult due to the effects of internal variability. For the 2019–21 drought in Madagascar, we find that the small number of available data points precludes a meaningful attribution analysis. Overall, we find that the effects of internal climate variability on GMST and the uncertain relationship between GMST and regional extremes may lead to inaccurate attribution conclusions using the part of the WWA approach examined here.

The recharge oscillator (RO) model has been successfully used to understand different aspects of the El Niño-Southern Oscillation (ENSO). Fitting the RO to observations and climate model simulations consistently suggests that ENSO is a damped oscillator whose variability is sustained and made irregular by external weather noise. We investigate the methods that have been used to estimate the growth rate of ENSO by applying them to simulations of both damped and self-sustained RO regimes. We find that fitting a linear RO leads to parameters that imply a damped oscillator even when the fitted data were produced by a model that is self-sustained. Fitting a nonlinear RO also leads to a significant bias toward a damped regime. As such, it seems challenging to conclude whether ENSO is a damped or a self-sustained oscillation by fitting such models to observations, and the possibility that ENSO is self-sustained cannot be ruled out.

The recharge oscillator (RO) model has been used to describe and understand different aspects of the El Ni&amp;#241;o Southern Oscillation (ENSO). One application involves fitting the RO model to observations or model output to identify if ENSO is a self-sustained or a damped oscillation driven by external weather noise such as westerly wind bursts. Fitting the linear recharge oscillator to observations and climate model simulations consistently yields an asymptotically stable system. This suggests that ENSO can be represented by a damped oscillator whose variability is sustained and made irregular by external stochastic forcing. We investigate the accuracy of methods that have been used to estimate the recharge oscillator parameters and their implied period and growth rate for ENSO using simulations of both linear and nonlinear recharge oscillators. Ultimately, we find that fitting the RO does not allow for robustly differentiating between a damped or a self-sustained regime. Specifically, we find that fitting a linear RO leads to parameters that imply a damped oscillator even when the fitted data were produced by a model that is self-sustained. As such, it seems challenging&amp;#160; to conclude whether ENSO is a damped or a self-sustained system by fitting the recharge oscillator model to observations. It is therefore possible that ENSO could be described instead by a self-sustained oscillator.&amp;#160;

The equatorial jets observed on the Jovian planets - Jupiter, Saturn, Uranus, and Neptune - exhibit extreme equatorial zonal flow patterns, manifesting as either strongly prograde (in the gas giants) or strongly retrograde (in the ice giants). Existing theories have often treated gas giants and ice giants separately, primarily focusing on the differences between deep and shallow dynamics. However, recent gravity measurements suggest that the convective envelope of Jupiter may be similar to those of the ice giants, challenging the traditional distinctions between these planet types.We present results from a numerical simulation that introduces a mechanism capable of explaining the equatorial jets on the ice giants in a manner analogous to those on the gas giants. In these simulations, as shown theoretically by Busse et al., the convective dynamics and planetary rotation drive the formation of tilted convection columns. These columns, extending cylindrically from the deep interior to the outer atmospheric layers, play a crucial role in shaping the zonal wind patterns. In this study, the tilting of the convection columns introduces asymmetries in momentum transport, leading to a bifurcation of the flow into either superrotation (prograde jets) or subrotation (retrograde jets).Through a detailed analysis of the convection-driven columnar structures, we demonstrate that the equatorial wave properties and the leading-order momentum balance share remarkable similarities between the two types of solutions. Our findings comprehensively explain the potential for both superrotation and subrotation solutions under constant physical conditions, thereby potentially explaining the diverse zonal wind patterns observed on the Jovian planets and providing a deeper understanding of the mechanisms driving equatorial jet formation.

Evergreen-needle forests are among the most adaptive ecosystems, spanning from the cold-wet Boreal to the hot-dry Mediterranean, and can provide insights into differential responses in productivity and carbon storage potential across a geographic range. Using 20 years of flux-tower data from contrasting Boreal (Hyyti&amp;#228;l&amp;#228;, Finland; HYY) and semi-arid (Yatir, Israel; YAT) conifer forests, NEE sensitivity to key environmental and climate drivers was examined. We analyzed both the seasonal and the variability-driven changes in NEE with Machine Learning modeling (Random Forest; RF) and SHAP analysis and compared the results against baseline GLM and GAM outputs. &amp;#160;All models explained the seasonality in NEE well (RMSE0.95). However, the RF model had the advantage of capturing complex feature interactions on variability-driven NEE, with the simplicity in interpretability of the GLM (R2 values of 0.59-0.67 for RF, 0.63-0.67 for GAM, and 0.34-0.55 for GLM; with similar results in RMSE). Both forests share the sensitivity of the variability-driven changes in NEE to short- and long-wave radiation and precipitation (57%-82% of mean SHAP), but are predominantly limited by radiation duration (HYY) or intensity (YAT) in the productive season. Seasonal variations in NEE were uniquely dominated by soil water content (SWC) at the 45 cm layer in YAT (55% of meanSHAP) and by VPD in HYY (69% of meanSHAP). Based on these controlling factors, we demonstrate that observed trends in rain events that recharge deep soil layers in YAT lead to a reduction in carbon sequestration potential of 5.5 g-C/m2/year (3% of the annual mean). In contrast, no discernible trends in VPD, rainfall events, nor radiation in the productive season in HYY indicated any such changes in sequestration potential during this period. Yet, the compounding effects of a hot-dry month in tandem with a wet and warm month could reduce mean sequestration by ~70% (194 g-C/m2) in HYY, as demonstrated in summer 2020. The results indicate that across large climatic gradients, conifer forests show a shift in the predominant factor influencing NEE in the productive season between soil moisture and atmospheric moisture on the seasonal time scale, yet the variability response is consistently controlled by radiation-limiting factors.

Abstract. In spite of decades of research, the role of climate feedbacks in the Pleistocene glacial cycles is still not fully understood. Here, we calculate the surface mass balance (SMB) of the Laurentide Ice Sheet (LIS) throughout the last deglaciation using the isotope-enabled transient climate model experiment (iTraCE). A surface energy balance framework is used to calculate yearly melt, and a parameterization of the refreezing of snow melt and liquid precipitation is incorporated. The SMB calculated from iTraCE overestimates the total ice mass loss rate in comparison to the ICE-6G reconstruction from the Last Glacial Maximum (LGM; 21 ka) until about 15–14 ka; subsequently, the fully forced climate model experiment better fits the ICE-6G ice volume loss rate. We find the melt rate for the LIS to be primarily set by the small residual of large net shortwave and longwave radiative fluxes. The melt, and hence the SMB, are very sensitive to small changes in the albedo and downwelling longwave radiation. By increasing albedo by a mere 1.9 % or by decreasing downwelling longwave radiation by only 1.45 % (well within the uncertainty range of these variables), the large overestimation of the rate of mass loss deduced from the SMB compared to reconstructed rates of mass loss from 19–15 ka can be eliminated. The inconsistency of the climate model-derived, offline SMB calculation and the ice mass reconstructions exists irrespective of the role of ablation caused by ice flow, which cannot be calculated using this analysis. The extreme sensitivity of the melt rate suggests that General Circulation Models (GCMs) still struggle to reliably calculate the SMB, presenting a significant roadblock in our attempt to understand the Pleistocene ice ages.

Abstract In spite of the mean warming trend over the last few decades and its amplification in the Arctic, some studies have found no robust decline or even a slight increase in wintertime cold air outbreaks over North America. But fossil evidence from warmer paleoclimate periods indicates that the interior of North America never dropped below freezing even in the depths of winter, which implies that the maintenance of cold air outbreaks is unlikely to continue indefinitely with future warming. To identify key mechanisms affecting cold air outbreaks and understand how and why they will change in a warmer climate, we examine the development of North American cold air outbreaks in both a preindustrial and a roughly 8×CO 2 scenario using the Community Earth System Model, version 2 (CESM2). We observe a sharp drop-off in the wintertime temperature distribution at the freezing temperature, suppressing below-freezing conditions in the warmer climate and above-freezing conditions in the preindustrial case. The disappearance of Arctic sea ice and loss of the near-surface temperature inversion dramatically decrease the availability of below-freezing air in source regions. Using an air parcel trajectory analysis, we demonstrate a remarkable similarity in both the dynamics and diabatic effects acting on cold air masses in the two climate scenarios. Diabatic temperature evolution along cold air outbreak trajectories is a competition between cooling from longwave radiation and warming from boundary layer mixing. Surprisingly, while both diabatic effects strengthen in the warmer climate, the balance remains the same, with a net cooling of about −6 K over 10 days. Significance Statement We compare a preindustrial climate scenario to a much warmer climate circa the year 2300 under high emissions to understand the physical processes that influence the coldest wintertime temperatures and how they will change with warming. We find that enhanced warming in the Arctic, and particularly over the Arctic Ocean due to the loss of wintertime sea ice, dramatically reduces the availability of cold air to be swept into North America. By tracing these cold air masses as they travel, we also find that they experience the same total amount of cooling in the much warmer climate as they did in the preindustrial climate even though many of the individual heating and cooling processes have gotten stronger.

The meridional extent of marine ice during the Neoproterozoic snowball Earth events is debated. Banded iron formations associated with the Sturtian glaciation are considered evidence for a completely ice-covered, ferruginous ocean (hard snowball). Here, using an ocean general circulation model with thick sea glaciers and Neoproterozoic biogeochemistry, we find that circulation in a partially ice-covered ocean (soft snowball) yields iron deposition patterns similar to the observed distribution of Sturtian banded iron formations. Neoproterozoic banded iron formations formed in partially glaciated oceans where iron-rich and oxygenated water masses met, according to ocean modelling.

Westerly wind bursts (WWBs), a westerly anomaly in equatorial winds in the Pacific, occur before every major El Ni&amp;#241;o event, yet major aspects of their mechanism are still not fully understood. Proposed mechanisms include cyclones approaching the equator, eastern-propagating convective heating, and wind-induced surface heat exchange, which amplifies WWBs near their peaks (Fu and Tziperman, 2019). To better understand WWB dynamics, we study their composite momentum budget using reanalysis and examine the role of convective heating and other factors. We find that many WWBs are not directly explained by nearby tropical cyclones or convective precipitation. We study their momentum budget before, during, and after the peak of the event, finding different balances at each stage. A comparison of the deduced balance to that in atmospheric general circulation climate models should add confidence in their ability to simulate this important factor in El Ni&amp;#241;o's development.

Abstract Glacial‐interglacial oscillations exhibit a periodicity of approximately 100 Kyr during the late Pleistocene. Insolation variations are understood to play a vital role in these ice ages, yet their exact effect is still unknown; the 100 Kyr ice ages may be explained in two different ways. They could be purely insolation‐driven, such that ice ages are a consequence of insolation variations and would not have existed without these variations. Or, ice ages may be self‐sustained oscillations, where they would have existed even without insolation variations. We develop several observable measures that are used to differentiate between the two scenarios and can help to determine which one is more likely based on the observed proxy record. We demonstrate these analyses using two representative models. First, we find that the self‐sustained model best fits the ice volume proxy record for the full 800‐Kyr time period. Next, the same model also shows a 100 Kyr peak consistent with observations, yet the insolation‐driven model exhibits a dominant 400 Kyr spectral peak inconsistent with observations. Our third measure indicates that midpoints in ice volume during terminations do not always occur during the same phase of insolation in both observations and the self‐sustained scenario, whereas they do in the insolation‐driven scenario. While some of these results suggest that the self‐sustained ice ages are more consistent with the observed record, they rely on simple representations of the two scenarios. To draw robust conclusions, a broader class of models should be tested using this method of producing observable differences.

Abstract Coastal upwelling, driven by alongshore winds and characterized by cold sea surface temperatures and high upper-ocean nutrient content, is an important physical process sustaining some of the oceans’ most productive ecosystems. To fully understand the ocean properties in eastern boundary upwelling systems, it is important to consider the depth of the source waters being upwelled, as it affects both the SST and the transport of nutrients toward the surface. Here, we construct an upwelling source depth distribution for parcels at the surface in the upwelling zone. We do so using passive tracers forced at the domain boundary for every model depth level to quantify their contributions to the upwelled waters. We test the dependence of this distribution on the strength of the wind stress and stratification using high-resolution regional ocean simulations of an idealized coastal upwelling system. We also present an efficient method for estimating the mean upwelling source depth. Furthermore, we show that the standard deviation of the upwelling source depth distribution increases with increasing wind stress and decreases with increasing stratification. These results can be applied to better understand and predict how coastal upwelling sites and their surface properties have and will change in past and future climates.

Coastal upwelling, driven by alongshore winds and characterized by cold sea surface temperatures and high upper-ocean nutrient content, is an important physical process sustaining some of the oceans' most productive ecosystems. To fully understand the ocean properties in eastern boundary upwelling systems, it is important to consider the depth of the source waters being upwelled, as it affects both the SST and the transport of nutrients toward the surface. Here, we construct an upwelling source depth distribution for parcels at the surface in the upwelling zone. We do so using passive tracers forced at the domain boundary for every model depth level to quantify their contributions to the upwelled waters. We test the dependence of this distribution on the strength of the wind stress and stratification using high-resolution regional ocean simulations of an idealized coastal upwelling system. We also present an efficient method for estimating the mean upwelling source depth. Furthermore, we show that the standard deviation of the upwelling source depth distribution increases with increasing wind stress and decreases with increasing stratification. These results can be applied to better understand and predict how coastal upwelling sites and their surface properties have and will change in past and future climates.

Abstract Arctic sea‐ice loss is influenced by multiple positive feedbacks, sparking concerns of accelerated loss in the coming years or even a tipping point, where a sea‐ice equilibrium disappears at a given CO 2 value and sea ice rapidly evolves to a new steady state. Such a tipping point would imply a bi‐stability of the Arctic climate—where multiple steady‐state Arctic climates are possible at the same CO 2 value. Previous works have sought to establish the existence of bi‐stability using a range of models, from zero‐dimensional sea ice thermodynamic models to fully coupled global climate models, with conflicting results. Here, we present a new model of the Arctic that includes both sea‐ice thermodynamics and key atmospheric feedbacks in a simple framework. We exploit the model's simplicity to identify physical mechanisms that control the timing and extent of sea‐ice bi‐stability, and the abruptness of ice loss. We show that longwave radiation feedbacks can have a strong influence on Arctic surface climate from atmospheric temperature increases alone, even without major contributions from clear‐sky moisture or convective clouds suggested previously. While winter sea‐ice bi‐stability is robust to changes in uncertain model parameters in this study, summer sea ice is more sensitive. Finally, our model indicates that positive feedbacks may modulate the CO 2 threshold of sea‐ice loss and the width of bi‐stability much more strongly than the abruptness of loss. These results lead to a comprehensive understanding of the conditions that favor Arctic sea‐ice bi‐stability, particularly the role of atmospheric feedbacks, in both future and past climates.

Changes in extreme weather events are a potentially important aspect of anthropogenic climate change (ACC), yet, are difficult to attribute to ACC because the record length is often similar to, or shorter than, extreme-event return periods. This study is motivated by the ``World Weather Attribution'' initiative (WWA) and, specifically, their approach of fitting extreme value distribution functions to local observations. They calculate the dependence of distribution parameters on global mean surface temperature (GMST) and use this dependence to attribute extreme events to ACC. Applying this method to preindustrial climate simulations with no time-varying greenhouse gas forcing, we still find a strong dependence of distribution parameters on GMST. This dependence results from internal climate variability (e.g., ENSO) affecting both extreme events and GMST. Therefore, dependence on GMST does not necessarily imply an effect of ACC on extremes. We further consider whether an extreme value, normal, or log-normal distribution better represents the data; if a GMST-dependence of distribution parameters is justified using a likelihood ratio test; and if a meaningful attribution is possible given uncertainties in GMST dependence. We find, for example, that an attribution of Australia's 2020--2021 Bushfires to ACC is difficult due to the effects of internal variability. For the 2019--2021 drought in Madagascar we find that the small number of available data points precludes a meaningful attribution analysis. Overall, we find that the effects of internal climate variability on GMST and the uncertain relationship between GMST and regional extremes may lead to inaccurate attribution conclusions using the part of the WWA approach examined here.

Abstract. Abrupt and irreversible winter Arctic sea ice loss may occur under anthropogenic warming due to the disappearance of a sea ice equilibrium at a threshold value of CO2, commonly referred to as a tipping point. Previous work has been unable to conclusively identify whether a tipping point in winter Arctic sea ice exists because fully coupled climate models are too computationally expensive to run to equilibrium for many CO2 values. Here, we explore the deviation of sea ice from its equilibrium state under realistic rates of CO2 increase to demonstrate for the first time how a few time-dependent CO2 experiments can be used to predict the existence and timing of sea ice tipping points without running the model to steady state. This study highlights the inefficacy of using a single experiment with slow-changing CO2 to discover changes in the sea ice steady state and provides a novel alternate method that can be developed for the identification of tipping points in realistic climate models.

Abstract We examine the hypothesis that the observed connection between the stratospheric quasi-biennial oscillation (QBO) and the strength of the Madden–Julian oscillation (MJO) is modulated by the sea surface temperature (SST)—for example, by El Niño–Southern Oscillation (ENSO). A composite analysis shows that, globally, La Niña SSTs are remarkably similar to those that occur during the easterly phase of the QBO. A maximum covariance analysis suggests that MJO power and SST are strongly linked on both the ENSO time scale and the QBO time scale. We analyze simulations with a modified configuration of version 2 of the Community Earth System Model, with a high top and fine vertical resolution. The model is able to simulate ENSO, the QBO, and the MJO. The ocean-coupled version of the model simulates the QBO, ENSO, and MJO, but does not simulate the observed QBO–MJO connection. When driven with prescribed observed SST anomalies based on composites for QBO east and QBO west (QBOE and QBOW), however, the same atmospheric model produces a modest enhancement of MJO power during QBOE relative to QBOW, as observed. We explore the possibility that the SST anomalies are forced by the QBO itself. Indeed, composite Hovmöller diagrams based on observations show the propagation of QBO zonal wind anomalies all the way from the upper stratosphere to the surface. Also, subsurface ocean temperature composites reveal a similarity between the western Pacific and Indian Ocean subsurface signal between La Niña and QBOE.

Abstract It has been suggested that the ice shell of Jupiter's moon Europa may drift non‐synchronously due to tidal torques. Here we argue that torques applied by the underlying ocean are also important and can result in non‐synchronous rotation. The resulting spin rate can be slightly slower than the synchronous angular rate that would have kept the same point of the ice shell facing Jupiter. We develop an ice shell rotation model, driven by ocean stress calculated using a high‐resolution state‐of‐the‐art ocean general circulation model, and take into account the viscoelastic deformation of the ice shell. We use the ice shell model results together with observed limits on the ice shell drift speed to constrain ice shell parameters such as effective viscosity, which is currently uncertain by at least four orders of magnitude. Our results suggest, at best, sluggish ice shell convection. Depending on the relaxation time scale of the ice shell and on the ocean currents, the ice shell may exhibit negligible drift, constant drift, or oscillatory drift superimposed on random fluctuations. The expected rotation rate exceeds ∼30 m/yr; future spacecraft observations can be used to test these predictions and yield insight into the properties of the ice shell and underlying ocean.

<strong class="journal-contentHeaderColor">Abstract.</strong> Abrupt and irreversible winter Arctic sea-ice loss may occur under anthropogenic warming due to the collapse of a sea-ice equilibrium at a threshold value of CO₂, commonly referred to as a tipping point. Previous work has been unable to conclusively identify whether a tipping point in Arctic sea ice exists because fully-coupled climate models are too computationally expensive to run to equilibrium for many CO₂ values. Here, we explore the deviation of sea ice from its equilibrium state under realistic rates of CO₂ increase to demonstrate how a few time-dependent CO₂ experiments can be used to predict the existence and timing of sea-ice tipping points without running the model to steady-state. This study highlights the inefficacy of using a single experiment with slow-changing CO₂ to discover changes in the sea-ice steady-state, and provides an alternate method that can be developed for the identification of tipping points in realistic climate models.

Abstract Stratocumulus clouds cover about a fifth of Earth’s surface, and due to their albedo and low-latitude location, they have a strong effect on Earth’s radiation budget. Previous studies using large-eddy simulations have shown that multiple equilibria (both stratocumulus-covered and cloud-free/scattered cumulus states) exist as a function of fixed SST, with relevance to equatorward advected air masses. Multiple equilibria have also been found as a function of atmospheric CO 2 , with a subtropical SST nearly 10 K higher in the cloud-free state and with suggested relevance to warm climate dynamics. In this study, we use a mixed-layer model with an added surface energy balance and the ability to simulate both the stratocumulus (coupled) and cloud-free/scattered cumulus (decoupled) states using a “stacked” mixed-layer approach to study both types of multiple equilibria and the corresponding hysteresis. The model’s simplicity and computational efficiency allow us to qualitatively explore the mechanisms critical to the stratocumulus cloud instability and hysteresis as well as isolate key processes that allow for multiple equilibria via mechanism-denial experiments not possible with a full-complexity model. For the hysteresis in fixed SST, we find that decoupling can occur due to either enhanced entrainment warming or a reduction in cloud-top longwave cooling. The critical SST at which decoupling occurs is highly sensitive to precipitation and entrainment parameterizations. In the CO 2 hysteresis, decoupling occurs in the simple model used even without the inclusion of SST–cloud cover feedbacks, and the width of the hysteresis displays the same sensitivities as the fixed SST case. Overall, the simple model analysis and results motivate further studies using higher complexity models.