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Seeley and Wordsworth (2021, https://doi.org/10.1038/s41586‐021‐03919‐z) showed that in small‐domain cloud‐resolving simulations the temporal pattern of precipitation transforms in extremely hot climates (≥320 K) from quasi‐steady to organized episodic deluges, with outbursts of heavy rain alternating with several dry days. They proposed a mechanism for this transition involving increased water vapor greenhouse effect and solar radiation absorption leading to net lower‐tropospheric radiative heating. This heating inhibits lower‐tropospheric convection and decouples the boundary layer from the upper troposphere during the dry phase, allowing lower‐tropospheric moist static energy to build until it discharges, resulting in a deluge. We perform cloud‐resolving simulations in polar night and show that the same transition occurs, implying that some revision of their mechanism is necessary. We perform further tests to show that episodic deluges can occur even if the lower‐tropospheric radiative heating rate is negative, as long as the magnitude of the upper‐tropospheric radiative cooling is about twice as large. We find that in the episodic deluge regime the period can be predicted from the time for radiation and reevaporation to cool the lower atmosphere. Plain Language Summary: Precipitation plays an important role in Earth's climate and habitability, and also influences important weathering processes such as the carbonate‐silicate cycle. In the distant future, Earth may experience a very hot and wet "hothouse" climate, just like it may have in the Archean. Modeling results show that in a hothouse climate, precipitation transforms into an "episodic deluge" pattern, with outbursts of heavy rain alternating with several dry days. In this study, we find that positive lower‐tropospheric heating is not the necessary cause for episodic deluges. Instead, vertical radiative cooling contrast is critical in triggering the episodic deluges in small‐domain hothouse climates. We also try to understand the underlying mechanism of episodic deluges through CIN and CAPE analyses. Key Points: Episodic deluges can occur during polar nightLower‐tropospheric radiative heating is not necessary for the occurrence of episodic delugesA strong vertical gradient of radiative cooling is a key factor in triggering episodic deluges [ABSTRACT FROM AUTHOR]

The purpose of this article is to discuss practical solutions to the threat to free inquiry at universities coming from the illiberal left. Based on my experiences at the University of Chicago, I propose that all universities should adopt and enforce rules requiring that: (1) the university, and any unit of it, cannot take collective positions on social and political issues; (2) faculty hiring and promotion be done solely on the basis of research and teaching merit, with nothing else taken into consideration; and (3) free expression be guaranteed on campus, even if someone claims to be offended, hurt or harmed by it. Faculty need to work together with students, alumni, journalists and politicians to get this done. [ABSTRACT FROM AUTHOR]

Hot Jupiters are tidally locked gaseous exoplanets with atmospheric circulations dominated by a super-rotating equatorial jet. Their global circulation is often studied with simulations in 3D general circulation models (GCMs). Energy builds up at the smallest scales in these models and must be dissipated. Many models use 'hyperdiffusion' for this, which applies a tendency to the prognostic variables based on a high-order Laplacian operator. This removes the unrealistic and unstable build-up of energy at small scales, and ideally does not affect the large-scale circulation. In this study, we show that hyperdiffusion can in fact affect the large-scale circulation of simulations of hot Jupiters. These planets have large velocity gradients, so hyperdiffusion can produce a momentum tendency that may affect the largest scales. We analyse four simulations with different hyperdiffusion parameters in the GCM THOR. These show that hyperdiffusion can affect the atmospheric zonal momentum budget as strongly as the physical forcing. The hyperdiffusion slows down and spreads out the jet, reducing its speed by more than |$50{{\ \rm per\ cent}}$| at some levels. We analyse simulations from the GCMs MITgcm and Exo-FMS and compare the effects of their different dissipation methods. The drag on the jet due to hyperdiffusion can be reduced by using a weaker hyperdiffusion coefficient, a higher resolution, or higher order diffusion. We aim to provide a basis for a study to investigate the 'real' momentum budget and jet speed of hot Jupiters. This study shows the need to examine long-held modelling assumptions when studying novel exoplanets. [ABSTRACT FROM AUTHOR]

Many rare weather events, including hurricanes, droughts, and floods, dramatically impact human life. To accurately forecast these events and characterize their climatology requires specialized mathematical techniques to fully leverage the limited data that are available. Here we describe transition path theory (TPT), a framework originally developed for molecular simulation, and argue that it is a useful paradigm for developing mechanistic understanding of rare climate events. TPT provides a method to calculate statistical properties of the paths into the event. As an initial demonstration of the utility of TPT, we analyze a low-order model of sudden stratospheric warming (SSW), a dramatic disturbance to the polar vortex that can induce extreme cold spells at the surface in the midlatitudes. SSW events pose a major challenge for seasonal weather prediction because of their rapid, complex onset and development. Climate models struggle to capture the long-term statistics of SSW, owing to their diversity and intermittent nature. We use a stochastically forced Holton-Mass-type model with two stable states, corresponding to radiative equilibrium and a vacillating SSW-like regime. In this stochastic bistable setting, from certain probabilistic forecasts TPT facilitates estimation of dominant transition pathways and return times of transitions. These "dynamical statistics" are obtained by solving partial differential equations in the model's phase space. With future application to more complex models, TPT and its constituent quantities promise to improve the predictability of extreme weather events through both generation and principled evaluation of forecasts. [ABSTRACT FROM AUTHOR]

As Arctic sea ice extent decreases with increasing greenhouse gases, there is a growing interest in whether there could be a bifurcation associated with its loss, and whether there is significant hysteresis associated with that bifurcation. A challenge in answering this question is that the bifurcation behavior of certain Arctic energy balance models have been shown to be sensitive to how ice-albedo feedback is parameterized. We analyze an Arctic energy balance model in the limit as a smoothing parameter associated with ice-albedo feedback tends to zero, which introduces a discontinuity boundary to the dynamical systems model. Our analysis provides a case study where we use the system in this limit to guide the investigation of bifurcation behavior of the original albedo-smoothed system. In this case study, we demonstrate that certain qualitative bifurcation behaviors of the albedo-smoothed system can have counterparts in the limit with no albedo smoothing. We use this perspective to systematically explore the parameter space of the model. For example, we uncover parameter sets for which the largest transition, with increasing greenhouse gases, is from a perennially ice-covered Arctic to a seasonally ice-free state, an unusual bifurcation scenario that persists even when albedo-smoothing is reintroduced. This analysis provides an alternative perspective on how parameters of the model affect bifurcation behavior. We expect our approach, which exploits the width of repelling sliding intervals for understanding the hysteresis loops, would carry over to other positive feedback systems with a similar natural piecewise-smooth limit, and when the feedback strength is likewise modulated with seasons or other periodic forcing. [ABSTRACT FROM AUTHOR]

Recent general circulation model (GCM) simulations have challenged the idea that a snowball Earth would be nearly entirely cloudless. This is important because clouds would provide a strong warming to a high-albedo snowball Earth. GCM results suggest that clouds could lower the threshold CO2 needed to deglaciate a snowball by a factor of 10-100, enough to allow consistency with geochemical data. Here a cloud-resolving model is used to investigate cloud and convection behavior in a snowball Earth climate. The model produces convection that extends vertically to a similar temperature as modern tropical convection. This convection produces clouds that resemble stratocumulus clouds under an inversion on modern Earth, which slowly dissipate by sedimentation of cloud ice. There is enough cloud ice for the clouds to be optically thick in the longwave, and the resulting cloud radiative forcing is similar to that produced in GCMs run in snowball conditions. This result is robust to large changes in the cloud microphysics scheme because the cloud longwave forcing, which dominates the total forcing, is relatively insensitive to cloud amount and particle size. The cloud-resolving model results are therefore consistent with the idea that clouds would provide a large warming to a snowball Earth, helping to allow snowball deglaciation. [ABSTRACT FROM AUTHOR]

In the spirit of minimal modeling of complex systems, we develop an idealized two-column model to investigate the climate of tidally locked terrestrial planets with Earth-like atmospheres in the habitable zone of M-dwarf stars. The model is able to approximate the fundamental features of the climate obtained from three-dimensional (3D) atmospheric general circulation model (GCM) simulations. One important reason for the two-column model's success is that it reproduces the high cloud albedo of the GCM simulations, which reduces the planet's temperature and delays the onset of a runaway greenhouse state. The two-column model also clearly illustrates a secondary mechanism for determining the climate: the nightside acts as a “radiator fin” through which infrared energy can be lost to space easily. This radiator fin is maintained by a temperature inversion and dry air on the nightside, and plays a similar role to the subtropics on modern Earth. Since one-dimensional radiative-convective models cannot capture the effects of the cloud albedo and radiator fin, they are systematically biased toward a narrower habitable zone. We also show that cloud parameters are the most important in the two-column model for determining the day-night thermal emission contrast, which decreases and eventually reverses as the stellar flux increases. This reversal is important because it could be detected by future extrasolar planet characterization missions, which would suggest that the planet has Earth-like water clouds and is potentially habitable. [ABSTRACT FROM AUTHOR]

Penitents are broad snow spikes and ridges that range in height between centimeters and meters. Two key features of penitents remain unexplained: (1) they generally form at low latitudes and (2) their ridges and troughs have an east-west orientation. Here we show that surface-to-surface exchange of shortwave radiation and the local geometry of the sun's daily arc across the sky are the key processes that, in the absence of other effects, determine the geographic extent of where surface roughness features can grow or dissipate on snowfields and ice surfaces. As an application of our analysis, we examine the question of the geographic extent of snow penitents on horizontal surfaces. The results show that surface-to-surface radiative transfer can explain why penitents do not form on horizontal surfaces more than ∼55° off the equator. We further show on the basis of the sun's path across the sky that penitents that are corrugated, i.e. occur in long ridges or rows, must align their ridge axis within 30° of the east-west transect. [ABSTRACT FROM AUTHOR]

Large terrestrial planets are expected to have muted topography and deep oceans, implying that most super-Earths should be entirely covered in water, so-called waterworlds. This is important because waterworlds lack a silicate weathering thermostat so their climate is predicted to be less stable than that of planets with exposed continents. In other words, the continuously habitable zone for waterworlds is much narrower than for Earth-like planets. A planet's water is partitioned, however, between a surface reservoir, the ocean, and an interior reservoir, the mantle. Plate tectonics transports water between these reservoirs on geological timescales. Degassing of melt at mid-ocean ridges and serpentinization of oceanic crust depend negatively and positively on seafloor pressure, respectively, providing a stabilizing feedback on long-term ocean volume. Motivated by Earth's approximately steady-state deep water cycle, we develop a two-box model of the hydrosphere and derive steady-state solutions to the water partitioning on terrestrial planets. Critically, hydrostatic seafloor pressure is proportional to surface gravity, so super-Earths with a deep water cycle will tend to store more water in the mantle. We conclude that a tectonically active terrestrial planet of any mass can maintain exposed continents if its water mass fraction is less than ∼0.2%, dramatically increasing the odds that super-Earths are habitable. The greatest source of uncertainty in our study is Earth's current mantle water inventory: the greater its value, the more robust planets are to inundation. Lastly, we discuss how future missions can test our hypothesis by mapping the oceans and continents of massive terrestrial planets. [ABSTRACT FROM AUTHOR]

Previous studies have shown that increases in poleward ocean heat transport (OHT) do not strongly affect tropical SST. The goal of this paper is to explain this observation. To do so, the authors force two atmospheric global climate models (GCMs) in aquaplanet configuration with a variety of prescribed OHTs. It is found that increased OHT weakens the Hadley circulation, which decreases equatorial cloud cover and shortwave reflection, as well as reduces surface winds and evaporation, which both limit changes in tropical SST. The authors also modify one of the GCMs by alternatively setting the radiative effect of clouds to zero and disabling wind-driven evaporation changes to show that the cloud feedback is more important than the wind-evaporation feedback for maintaining constant equatorial SST as OHT changes. This work highlights the fact that OHT can reduce the meridional SST gradient without affecting tropical SST and could therefore serve as an additional degree of freedom for explaining past warm climates. [ABSTRACT FROM AUTHOR]

Sea ice schemes with a few vertical levels are typically used to simulate the thermodynamic evolution of sea ice in global climate models. Here it is shown that these schemes overestimate the magnitude of the diurnal surface temperature cycle by a factor of 2--3 when they are used to simulate tropical ice in a Snowball earth event. This could strongly influence our understanding of Snowball termination, which occurs in global climate models when the midday surface temperature in the tropics reaches the melting point. A hierarchy of models is used to show that accurate simulation of surface temperature variation on a given time scale requires that a sea ice model resolve the e-folding depth to which a periodic signal on that time scale penetrates. This is used to suggest modifications to the sea ice schemes used in global climate models that would allow more accurate simulation of Snowball deglaciation. [ABSTRACT FROM AUTHOR]

Most previous global climate model simulations could only produce the termination of Snowball Earth episodes at CO2 partial pressures of several tenths of a bar, which is roughly an order of magnitude higher than recent estimates of CO2 levels during and shortly after Snowball events. These simulations have neglected the impact of dust aerosols on radiative transfer, which is an assumption of potentially grave importance. In this paper it is argued, using the Dust Entrainment and Deposition (DEAD) box model driven by GCM results, that atmospheric dust aerosol concentrations may have been one to two orders of magnitude higher during a Snowball Earth event than today. It is furthermore asserted on the basis of calculations using NCAR’s Single Column Atmospheric Model (SCAM)—a radiative–convective model with sophisticated aerosol, cloud, and radiative parameterizations—that when the surface albedo is high, such increases in dust aerosol loading can produce several times more surface warming than an increase in the partial pressure of CO2 from 10−4 to 10−1 bar. Therefore the conclusion is reached that including dust aerosols in simulations may reconcile the CO2 levels required for Snowball termination in climate models with observations. [ABSTRACT FROM AUTHOR]

Winter sea ice dramatically cools the Arctic climate during the coldest months of the year and may have remote effects on global climate as well. Accurate forecasting of winter sea ice has significant social and economic benefits. Such forecasting requires the identification and understanding of all of the feedbacks that can affect sea ice. A convective cloud feedback has recently been proposed in the context of explaining equable climates, for example, the climate of the Eocene, which might be important for determining future winter sea ice. In this feedback, CO2-initiated warming leads to sea ice reduction, which allows increased heat and moisture fluxes from the ocean surface, which in turn destabilizes the atmosphere and leads to atmospheric convection. This atmospheric convection produces optically thick convective clouds and increases high-altitude moisture levels, both of which trap outgoing longwave radiation and therefore result in further warming and sea ice loss. Here it is shown that this convective cloud feedback is active at high CO2 during polar night in the coupled ocean–sea ice–land–atmosphere global climate models used for the 1% yr-1 CO2 increase to the quadrupling (1120 ppm) scenario of the Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report. At quadrupled CO2, model forecasts of maximum seasonal (March) sea ice volume are found to be correlated with polar winter cloud radiative forcing, which the convective cloud feedback increases. In contrast, sea ice volume is entirely uncorrelated with model global climate sensitivity. It is then shown that the convective cloud feedback plays an essential role in the elimination of March sea ice at quadrupled CO2 in NCAR’s Community Climate System Model (CCSM), one of the IPCC models that loses sea ice year-round at this CO2 concentration. A new method is developed to disable the convective cloud feedback in the Community Atmosphere Model (CAM), the atmospheric component of CCSM, and to show that March sea ice cannot be eliminated in CCSM at CO2 = 1120 ppm without the aide of the convective cloud feedback. [ABSTRACT FROM AUTHOR]

Environmental educators have long dealt with the charge that the practice of teaching about environmental issues is an attempt to introduce a liberal agenda into the classroom curriculum. However, traditionally Republican states and traditionally Democratic states are both among the nation's leaders and laggards in institutionalizing environmental education (EE) programs at the state level. Because of the political power of the charge of liberal bias in EE politics, it is important for researchers to try to determine the veracity of this charge in some meaningful way. The authors applied quantitative statistical methods to this issue and found that, in general, there were not significant differences among the degrees of state-level EE program activity between Democratic states and Republican states. In short, the political party affiliation of a given state is not a reliable predictor of that state's EE program activities. Thus, the evidence does not support the claim that EE is solely a liberal undertaking. [ABSTRACT FROM AUTHOR]

Previous work has shown that a convective cloud feedback can greatly increase high-latitude surface temperature upon the removal of sea ice and can keep sea ice from forming throughout polar night. This feedback activates at increased greenhouse gas concentrations. It may help to explain the warm “equable climates” of the late Cretaceous and early Paleogene eras (∼100 to ∼35 million years ago) and may be relevant for future climate under global warming. Here, the factors that determine the critical threshold CO2 concentration at which this feedback is active and the magnitude of the warming caused by the feedback are analyzed using both a highly idealized model and NCAR's single-column atmospheric model (SCAM) run under Arctic-like conditions. The critical CO2 is particularly important because it helps to establish the relevance of the feedback for past and future climates. Both models agree that increased heat flux into the high latitudes at low altitudes generally decreases the critical CO2. Increases in oceanic heat transport and in solar radiation absorbed during the summer should cause a sharp decrease in the critical CO2, but the effect of increases in atmospheric heat transport depends on its vertical distribution. It is furthermore found (i) that if the onset of convection produces more clouds and moisture, the critical CO2 should decrease, and the maximum temperature increase caused by the convective cloud feedback should increase and (ii) that reducing the depth of convection reduces the critical CO2 but has little effect on the maximum temperature increase caused by the convective cloud feedback. These results should help with interpretation of the strength and onset of the convective cloud feedback as found, for example, in Intergovernmental Panel on Climate Change (IPCC) coupled ocean–atmosphere models with different cloud and convection schemes. [ABSTRACT FROM AUTHOR]

A two-column atmospheric model on a land–sea interface is studied. The model has sophisticated convection, cloud, and radiation schemes, a mixed layer ocean, and a bucket model to simulate land hydrology. A self-sustained oscillation in soil moisture with a period on the order of months is found. This oscillation is strongest when the model is run with parameters chosen to correspond to the arid subtropics. The effect of changing model parameters on the oscillation is explored. The existence and qualitative behavior of the oscillation are relatively robust to changes in model parameters. [ABSTRACT FROM AUTHOR]

Potentially habitable exoplanets are targets of great interest for the James Webb Space Telescope and upcoming mission concepts such as the Habitable Worlds Observatory. Clouds strongly affect climate and habitability, but predicting their properties is difficult. In Global Climate Models (GCMs), especially those aiming at simulating Earth, cloud microphysics is often crudely approximated by assuming that all cloud particles have a single, constant size or a prescribed size distribution and that all clouds in a grid cell are identical. For exoplanets that range over a large phase space of planetary properties, this method could result in large errors. In this work, our goal is to determine how cloud microphysics on terrestrial exoplanets, whose condensable is mainly water vapor, depend on aerosol properties and planetary parameters such as surface pressure, surface gravity, and incident stellar radiation. We use the Community Aerosol and Radiation Model for Atmospheres as a 1D microphysical model to simulate the formation and evolution of clouds including the processes of nucleation, condensation, evaporation, coagulation, and vertical transfer. In these 1D idealized experiments, we find that the parameters that determine the macrophysical thermal structure of the atmospheres, including surface pressure and stellar flux, impact cloud radiative effect (CRE) most significantly. Parameters such as gravity and number density of aerosols working as cloud condensation nuclei affect the microphysical processes of cloud formation, including activation and vertical transfer. They also have a significant, though weaker effect on CRE. This work motivates the development of more accurate GCM cloud schemes and should aid in the interpretation of future observations. [ABSTRACT FROM AUTHOR]

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

Hurricanes are one of the most extreme storm systems that occur on Earth, characterized by strong rainfall and fast winds. The terrestrial exoplanets that will be characterized with future infrared space telescopes orbit M dwarf stars. As a result, the best observable terrestrial exoplanets have vastly different climates from Earth, with a large dayside-to-nightside irradiation contrast and relatively slow rotation. Hurricanes may affect future observations of terrestrial exoplanets because they enhance the vertical transport of water vapor and could influence ocean heat transport. In this work, we explore how the environment of terrestrial exoplanets orbiting M dwarf stars affects the favorability of hurricane genesis (formation). To do so, we apply metrics developed to understand hurricane genesis on Earth to three-dimensional climate models of ocean-covered exoplanets orbiting M dwarf stars. We find that hurricane genesis is most favorable on intermediate-rotating tidally locked terrestrial exoplanets with rotation periods of ∼8–10 days. As a result, hurricane genesis is most favorable for terrestrial exoplanets in the habitable zones of late-type M dwarf stars. The peak in the favorability of hurricane genesis at intermediate rotation occurs because sufficient spin is required for hurricane genesis, but the vertical wind shear on fast-rotating terrestrial exoplanets disrupts hurricane genesis. We find that hurricane genesis is less favorable on slowly rotating terrestrial exoplanets, which agrees with previous work. Future work using simulations that resolve hurricane genesis and evolution can test our expectations for how the environment affects the favorability of hurricane genesis on tidally locked terrestrial exoplanets. [ABSTRACT FROM AUTHOR]

Liquid water oceans are at the center of our search for life on exoplanets because water is a strict requirement for life as we know it. However, oceans are dynamic habitats—and some oceans may be better hosts for life than others. In Earth's ocean, circulation transports essential nutrients such as phosphate and is a first-order control on the distribution and productivity of life. Of particular importance is upward flow from the dark depths of the ocean in response to wind-driven divergence in surface layers. This "upwelling" returns essential nutrients that tend to accumulate at depth via sinking of organic particulates back to the sunlit regions where photosynthetic life thrives. Ocean dynamics are likely to impose constraints on the activity and atmospheric expression of photosynthetic life in exo-oceans as well, but we lack an understanding of how ocean dynamics may differ on other planets. We address this issue by exploring the sensitivity of ocean dynamics to a suite of planetary parameters using ROCKE-3D, a fully coupled ocean–atmosphere general circulation model. Our results suggest that planets that rotate slower and have higher surface pressure than Earth may be the most attractive targets for remote life detection because upwelling is enhanced under these conditions, resulting in greater nutrient supply to the surface biosphere. Seasonal deepening of the mixed layer on high-obliquity planets may also enhance nutrient replenishment from depth into the surface mixed layer. Efficient nutrient recycling favors greater biological activity, more biosignature production, and thus more detectable life. More generally, our results demonstrate the importance of considering oceanographic phenomena for exoplanet life detection and motivate future interdisciplinary contributions to the emerging field of exo-oceanography. [ABSTRACT FROM AUTHOR]

The sensitivity of the climate to CO2 forcing depends on spatially varying radiative feedbacks that act both locally and nonlocally. We assess whether a method employing multiple regression can be used to estimate local and nonlocal radiative feedbacks from internal variability. We test this method on millennial-length simulations performed with six coupled atmosphere–ocean general circulation models (AOGCMs). Given the spatial pattern of warming, the method does quite well at recreating the top-of-atmosphere flux response for most regions of Earth, except over the Southern Ocean where it consistently overestimates the change, leading to an overestimate of the sensitivity. For five of the six models, the method finds that local feedbacks are positive due to cloud processes, balanced by negative nonlocal shortwave cloud feedbacks associated with regions of tropical convection. For four of these models, the magnitudes of both are comparable to the Planck feedback, so that changes in the ratio between them could lead to large changes in climate sensitivity. The positive local feedback explains why observational studies that estimate spatial feedbacks using only local regressions predict an unstable climate. The method implies that sensitivity in these AOGCMs increases over time due to a reduction in the share of warming occurring in tropical convecting regions and the resulting weakening of associated shortwave cloud and longwave clear-sky feedbacks. Our results provide a step toward an observational estimate of time-varying climate sensitivity by demonstrating that many aspects of spatial feedbacks appear to be the same between internal variability and the forced response. [ABSTRACT FROM AUTHOR]

The Gaia hypothesis postulates that life regulates its environment to be favorable for its own survival. Most planets experience numerous perturbations throughout their lifetimes such as asteroid impacts, volcanism, and the evolution of their host star's luminosity. For the Gaia hypothesis to be viable, life must be able to keep the conditions of its host planet habitable, even in the face of these challenges. ExoGaia, a model created to investigate the Gaia hypothesis, has been previously used to demonstrate that a randomly mutating biosphere is in some cases capable of maintaining planetary habitability. However, those model scenarios assumed that all non-biological planetary parameters were static, neglecting the inevitable perturbations that real planets would experience. To see how life responds to climate perturbations to its host planet, we created three climate perturbations in ExoGaia: one rapid cooling of a planet and two heating events, one rapid and one gradual. The planets on which Gaian feedbacks emerge without climate perturbations are the same planets on which life is most likely to survive each of our perturbation scenarios. Biospheres experiencing gradual changes to the environment are able to survive changes of larger magnitude than those experiencing rapid perturbations, and the magnitude of change matters more than the sign. These findings suggest that if the Gaia hypothesis is correct, then typical perturbations that a planet would experience may be unlikely to disrupt Gaian systems. [ABSTRACT FROM AUTHOR]

Next-generation space telescopes will allow us to characterize terrestrial exoplanets. To do so effectively it will be crucial to make use of all available data. We investigate which atmospheric properties can, and cannot, be inferred from the broadband thermal phase curve of a dry and tidally locked terrestrial planet. First, we use dimensional analysis to show that phase curves are controlled by six nondimensional parameters. Second, we use an idealized general circulation model to explore the relative sensitivity of phase curves to these parameters. We find that the feature of phase curves most sensitive to atmospheric parameters is the peak-to-trough amplitude. Moreover, except for hot and rapidly rotating planets, the phase amplitude is primarily sensitive to only two nondimensional parameters: (1) the ratio of dynamical to radiative timescales and (2) the longwave optical depth at the surface. As an application of this technique, we show how phase curve measurements can be combined with transit or emission spectroscopy to yield a new constraint for the surface pressure and atmospheric mass of terrestrial planets. We estimate that a single broadband phase curve, measured over half an orbit with the James Webb Space Telescope, could meaningfully constrain the atmospheric mass of a nearby super-Earth. Such constraints will be important for studying the atmospheric evolution of terrestrial exoplanets as well as characterizing the surface conditions on potentially habitable planets. [ABSTRACT FROM AUTHOR]

Fluid recharge and discharge between the deep ocean and the porous upper layer of off-axis oceanic crust tends to concentrate in small volumes of rock, such as seamounts and fractures, that are unimpeded by low-permeability sediments. Basement structure, sediment burial, heat flow, and other regional characteristics of off-axis hydrothermal systems appear to produce considerable diversity of circulation behaviors. Circulation of seawater and seawater-derived fluids controls the extent of fluid-rock interaction, resulting in significant geochemical impacts. However, the primary regional characteristics that control how seawater is distributed within upper oceanic crust are still poorly understood. In this paper we present the details of the two-dimensional (2-D) BASALT (Basement Activity Simulated At Low Temperatures) numerical model of heat and fluid transport in an off-axis hydrothermal system. This model is designed to simulate a wide range of conditions in order to explore the dominant controls on circulation. We validate the BASALT model's ability to reproduce observations by configuring it to represent a thoroughly studied transect of the Juan de Fuca Ridge eastern flank. The results demonstrate that including series of narrow, ridge-parallel fractures as subgrid features produces a realistic circulation scenario at the validation site. In future projects, a full reactive transport version of the validated BASALT model will be used to explore geochemical fluxes in a variety of off-axis hydrothermal environments. [ABSTRACT FROM AUTHOR]

Atmospheric regime transitions are highly impactful as drivers of extreme weather events, but pose two formidable modeling challenges: predicting the next event (weather forecasting) and characterizing the statistics of events of a given severity (the risk climatology). Each event has a different duration and spatial structure, making it hard to define an objective "average event." We argue here that transition path theory (TPT), a stochastic process framework, is an appropriate tool for the task. We demonstrate TPT's capacities on a wave–mean flow model of sudden stratospheric warmings (SSWs) developed by Holton and Mass, which is idealized enough for transparent TPT analysis but complex enough to demonstrate computational scalability. Whereas a recent article (Finkel et al. 2021) studied near-term SSW predictability, the present article uses TPT to link predictability to long-term SSW frequency. This requires not only forecasting forward in time from an initial condition, but also backward in time to assess the probability of the initial conditions themselves. TPT enables one to condition the dynamics on the regime transition occurring, and thus visualize its physical drivers with a vector field called the reactive current. The reactive current shows that before an SSW, dissipation and stochastic forcing drive a slow decay of vortex strength at lower altitudes. The response of upper-level winds is late and sudden, occurring only after the transition is almost complete from a probabilistic point of view. This case study demonstrates that TPT quantities, visualized in a space of physically meaningful variables, can help one understand the dynamics of regime transitions. [ABSTRACT FROM AUTHOR]

It is likely that unambiguous habitable zone terrestrial planets of unknown water content will soon be discovered. Water content helps determine surface land fraction, which influences planetary weathering behavior. This is important because the silicate-weathering feedback determines the width of the habitable zone in space and time. Here a low-order model of weathering and climate, useful for gaining qualitative understanding, is developed to examine climate evolution for planets of various land-ocean fractions. It is pointed out that, if seafloor weathering does not depend directly on surface temperature, there can be no weathering-climate feedback on a waterworld. This would dramatically narrow the habitable zone of a waterworld. Results from our model indicate that weathering behavior does not depend strongly on land fraction for partially ocean-covered planets. This is powerful because it suggests that previous habitable zone theory is robust to changes in land fraction, as long as there is some land. Finally, a mechanism is proposed for a waterworld to prevent complete water loss during a moist greenhouse through rapid weathering of exposed continents. This process is named a “waterworld self-arrest,” and it implies that waterworlds can go through a moist greenhouse stage and end up as planets like Earth with partial ocean coverage. This work stresses the importance of surface and geologic effects, in addition to the usual incident stellar flux, for habitability. [ABSTRACT FROM AUTHOR]

The high computational cost of Global Climate Models (GCMs) is a problem that limits their use in many areas. Recently an inverse climate modeling (InvCM) method, which fixes the global mean sea surface temperature (SST) and evolves the CO2 mixing ratio to equilibrate climate, has been implemented in a cloud‐resolving model. In this article, we apply InvCM to ExoCAM GCM aquaplanet simulations, allowing the SST pattern to evolve while maintaining a fixed global‐mean SST. We find that InvCM produces the same climate as normal slab‐ocean simulations but converges an order of magnitude faster. We then use InvCM to calculate the equilibrium CO2 for SSTs ranging from 290 to 340 K at 1 K intervals and reproduce the large increase in climate sensitivity at an SST of about 315 K at much higher temperature resolution. The speedup provided by InvCM could be used to equilibrate GCMs at higher spatial resolution or to perform broader parameter space exploration in order to gain new insight into the climate system. Additionally, InvCM could be used to find unstable and hidden climate states, and to find climate states close to bifurcations such as the runaway greenhouse transition. Plain Language Summary: A large portion of the computational cost in climate simulation is spent in the initial equilibration phase before the model produces relevant output. This is because in normal Global Climate Model (GCM) simulations, you prescribe the atmospheric CO2 and allow the surface temperature to evolve until it reaches a roughly constant global‐mean value. In this article, we instead prescribe a global‐mean surface temperature and evolve the CO2 until the GCM is in energy balance. This leads to about a factor of ten decrease in equilibration time, which represents a considerable savings of computational resources. This allows us to investigate the change in climate sensitivity as the global‐mean temperature increases at high‐temperature resolution. Although the results we describe are for an idealized model set‐up, we believe that the method can be applied more generally. Additionally, the method could be used to investigate the climate response to given SST patterns and to find climate states that are unstable and/or hidden from normal GCM simulations. Key Points: We converge a GCM by varying the CO2 while keeping the global‐mean surface temperature fixed (the inverse climate modeling method)Inverse climate modeling converges about 10 times faster than normal slab‐ocean simulationsThe SST gradient response timescale is the bottleneck on the convergence rate of inverse climate modeling [ABSTRACT FROM AUTHOR]

Rare events arising in nonlinear atmospheric dynamics remain hard to predict and attribute. We address the problem of forecasting rare events in a prototypical example, sudden stratospheric warmings (SSWs). Approximately once every other winter, the boreal stratospheric polar vortex rapidly breaks down, shifting midlatitude surface weather patterns for months. We focus on two key quantities of interest: the probability of an SSW occurring, and the expected lead time if it does occur, as functions of initial condition. These optimal forecasts concretely measure the event's progress. Direct numerical simulation can estimate them in principle but is prohibitively expensive in practice: each rare event requires a long integration to observe, and the cost of each integration grows with model complexity. We describe an alternative approach using integrations that are short compared to the time scale of the warming event. We compute the probability and lead time efficiently by solving equations involving the transition operator, which encodes all information about the dynamics. We relate these optimal forecasts to a small number of interpretable physical variables, suggesting optimal measurements for forecasting. We illustrate the methodology on a prototype SSW model developed by Holton and Mass and modified by stochastic forcing. While highly idealized, this model captures the essential nonlinear dynamics of SSWs and exhibits the key forecasting challenge: the dramatic separation in time scales between a single event and the return time between successive events. Our methodology is designed to fully exploit high-dimensional data from models and observations, and has the potential to identify detailed predictors of many complex rare events in meteorology. [ABSTRACT FROM AUTHOR]

Extreme mesoscale weather, including tropical cyclones, squall lines, and floods, can be enormously damaging and yet challenging to simulate; hence, there is a pressing need for more efficient simulation strategies. Here, we present a new rare event sampling algorithm called quantile diffusion Monte Carlo (quantile DMC). Quantile DMC is a simple-to-use algorithm that can sample extreme tail behavior for a wide class of processes. We demonstrate the advantages of quantile DMC compared to other sampling methods and discuss practical aspects of implementing quantile DMC. To test the feasibility of quantile DMC for extreme mesoscale weather, we sample extremely intense realizations of two historical tropical cyclones, 2010 Hurricane Earl and 2015 Hurricane Joaquin. Our results demonstrate quantile DMC's potential to provide low-variance extreme weather statistics while highlighting the work that is necessary for quantile DMC to attain greater efficiency in future applications. [ABSTRACT FROM AUTHOR]

Direct computer simulation of intense tropical cyclones (TCs) in weather models is limited by computational expense. Intense TCs are rare and have small‐scale structures, making it difficult to produce large ensembles of storms at high resolution. Further, models often fail to capture the process of rapid intensification, which is a distinguishing feature of many intense TCs. Understanding rapid intensification is especially important in the context of global warming, which may increase the frequency of intense TCs. To better leverage computational resources for the study of rapid intensification, we introduce an action minimization algorithm applied to the Weather Research and Forecasting and WRFPLUS models. Action minimization nudges the model into forming more intense TCs than it otherwise would; it does so via the maximum likelihood path in a stochastic formulation of the model, thereby allowing targeted study of intensification mechanisms. We apply action minimization to simulations of Hurricanes Danny (2015) and Fred (2009) at 6‐km resolution to demonstrate that the algorithm consistently intensifies TCs via physically plausible pathways. We show an approximately tenfold computational savings using action minimization to study the tail of the TC intensification distribution. Further, for Hurricanes Danny and Fred, action minimization produces perturbations that preferentially reduce low‐level shear as compared to upper‐level shear, at least above a threshold of approximately 4 m/s. We also demonstrate that asymmetric, time‐dependent patterns of heating can cause significant TC intensification beyond symmetric, azimuthally averaged heating and find a regime of nonlinear response to asymmetric heating that has not been extensively studied in previous work. Key Points: Action minimization reduces the computational cost of intense cyclone simulation as compared to an ensemble studyAction minimization perturbs climate/weather models into producing realistic and more intense tropical cyclonesTime‐dependent, asymmetric heating can contribute significantly to tropical cyclone intensification [ABSTRACT FROM AUTHOR]

Geochemical data from cap carbonates deposited above Cryogenian glacial deposits have been widely used to infer the conditions that prevailed in the aftermath of snowball Earth. However, the time scale over which these carbonates were deposited and the degree to which they record the chemistry of a globally well-mixed ocean have remained poorly constrained. During deglaciation, a large volume of meltwater entered the ocean, creating two distinct layers: the fresh, hot, and light upper layer, and the salty, cold, and dense lower layer. Here we estimate the ocean mixing time scale based on energetic constraints. We find that the mixing time scale is 104-105 yr, with a best estimate of ~5 × 104 yr, or up to 100 times longer than that of the modern ocean. Mixing of the surface temperature anomaly implies a delayed sea-level rise of 40-50 m associated with pure thermal expansion. This result reconciles geological, geochemical, and paleomagnetic data from basal Ediacaran cap carbonates with physical oceanographic theory. In particular, our model suggests that (1) the cap dolostones formed predominantly in a freshwater environment; (2) the waters in which the dolostones formed were not well mixed with saline deep water, allowing for large geochemical differences between the cap dolostones and the deep ocean; and (3) the cap carbonate sequences formed in a two-phase transgression that lasted >104 yr, which is consistent with both local sea-level records and the preservation of magnetic excursions and reversals. [ABSTRACT FROM AUTHOR]

The effect of clouds on climate remains the largest uncertainty in climate change predictions, due to the inability of global climate models (GCMs) to resolve essential small-scale cloud and convection processes. We compare preindustrial and quadrupled CO2 simulations between a conventional GCM in which convection is parameterized and a "superparameterized" model in which convection is explicitly simulated with a cloud-permitting model in each grid cell. We find that the global responses of the two models to increased CO2 are broadly similar: both simulate ice-free Arctic summers, wintertime Arctic convection, and enhanced Madden-Julian oscillation (MJO) activity. Superparameterization produces significant differences at both CO2 levels, including greater Arctic cloud cover, further reduced sea ice area at high CO2, and a stronger increase with CO2 of the MJO. [ABSTRACT FROM AUTHOR]

In order to understand the climate on terrestrial planets orbiting nearby Sun-like stars, one would like to know their thermal inertia. We use a global climate model to simulate the thermal phase variations of Earth analogs and test whether these data could distinguish between planets with different heat storage and heat transport characteristics. In particular, we consider a temperate climate with polar ice caps (like the modern Earth) and a snowball state where the oceans are globally covered in ice. We first quantitatively study the periodic radiative forcing from, and climatic response to, rotation, obliquity, and eccentricity. Orbital eccentricity and seasonal changes in albedo cause variations in the global-mean absorbed flux. The responses of the two climates to these global seasons indicate that the temperate planet has 3× the bulk heat capacity of the snowball planet due to the presence of liquid water oceans. The obliquity seasons in the temperate simulation are weaker than one would expect based on thermal inertia alone; this is due to cross-equatorial oceanic and atmospheric energy transport. Thermal inertia and cross-equatorial heat transport have qualitatively different effects on obliquity seasons, insofar as heat transport tends to reduce seasonal amplitude without inducing a phase lag. For an Earth-like planet, however, this effect is masked by the mixing of signals from low thermal inertia regions (sea ice and land) with that from high thermal inertia regions (oceans), which also produces a damped response with small phase lag. We then simulate thermal light curves as they would appear to a high-contrast imaging mission (TPF-I/Darwin). In order of importance to the present simulations, which use modern-Earth orbital parameters, the three drivers of thermal phase variations are (1) obliquity seasons, (2) diurnal cycle, and (3) global seasons. Obliquity seasons are the dominant source of phase variations for most viewing angles. A pole-on observer would measure peak-to-trough amplitudes of 13% and 47% for the temperate and snowball climates, respectively. Diurnal heating is important for equatorial observers (∼5% phase variations), because the obliquity effects cancel to first order from that vantage. Finally, we compare the prospects of optical versus thermal direct imaging missions for constraining the climate on exoplanets and conclude that while zero- and one-dimensional models are best served by thermal measurements, second-order models accounting for seasons and planetary thermal inertia would require both optical and thermal observations. [ABSTRACT FROM AUTHOR]

Climate change, amplified in the far north, has led to rapid sea ice decline in recent years. In the summer, melt ponds form on the surface of Arctic sea ice, significantly lowering the ice reflectivity (albedo) and thereby accelerating ice melt. Pond geometry controls the details of this crucial feedback; however, a reliable model of pond geometry does not currently exist. Here we show that a simple model of voids surrounding randomly sized and placed overlapping circles reproduces the essential features of pond patterns. The only two model parameters, characteristic circle radius and coverage fraction, are chosen by comparing, between the model and the aerial photographs of the ponds, two correlation functions which determine the typical pond size and their connectedness. Using these parameters, the void model robustly reproduces the ponds' area-perimeter and area-abundance relationships over more than 6 orders of magnitude. By analyzing the correlation functions of ponds on several dates, we also find that the pond scale and the connectedness are surprisingly constant across different years and ice types. Moreover, we find that ponds resemble percolation clusters near the percolation threshold. These results demonstrate that the geometry and abundance of Arctic melt ponds can be simply described, which can be exploited in future models of Arctic melt ponds that would improve predictions of the response of sea ice to Arctic warming. [ABSTRACT FROM AUTHOR]