arXiv subjects

Dorian S. Abbot

Publications and source records attributed to Dorian S. Abbot.

At least 37 records · Page 2Linked to original sources

arXiv2023

Simple physics and integrators accurately reproduce Mercury instability statistics

The long-term stability of the Solar System is an issue of significant scientific and philosophical interest. The mechanism leading to instability is Mercury's eccentricity being pumped up so high that Mercury either collides with Venus or is scattered into the Sun. Previously, only three five-billion-year $N$-body ensembles of the Solar System with thousands of simulations have been run to assess long-term stability. We generate two additional ensembles, each with 2750 members, and make them publicly available at \texttt{https://archive.org/details/@dorianabbot}. We find that accurate Mercury instability statistics can be obtained by (1) including only the Sun and the 8 planets, (2) using a simple Wisdom-Holman scheme without correctors, (3) using a basic representation of general relativity, and (4) using a time step of 3.16 days. By combining our Solar System ensembles with previous ensembles we form a 9,601-member ensemble of ensembles. In this ensemble of ensembles, the logarithm of the frequency of a Mercury instability event increases linearly with time between 1.3 and 5 Gyr, suggesting that a single mechanism is responsible for Mercury instabilities in this time range and that this mechanism becomes more active as time progresses. Our work provides a robust estimate of Mercury instability statistics over the next five billion years, outlines methodologies that may be useful for exoplanet system investigations, and provides two large ensembles of publicly available Solar System integrations that can serve as testbeds for theoretical ideas as well as training sets for artificial intelligence schemes.

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arXiv2023

Revealing the statistics of extreme events hidden in short weather forecast data

Extreme weather events have significant consequences, dominating the impact of climate on society. While high-resolution weather models can forecast many types of extreme events on synoptic timescales, long-term climatological risk assessment is an altogether different problem. A once-in-a-century event takes, on average, 100 years of simulation time to appear just once, far beyond the typical integration length of a weather forecast model. Therefore, this task is left to cheaper, but less accurate, low-resolution or statistical models. But there is untapped potential in weather model output: despite being short in duration, weather forecast ensembles are produced multiple times a week. Integrations are launched with independent perturbations, causing them to spread apart over time and broadly sample phase space. Collectively, these integrations add up to thousands of years of data. We establish methods to extract climatological information from these short weather simulations. Using ensemble hindcasts by the European Center for Medium-range Weather Forecasting (ECMWF) archived in the subseasonal-to-seasonal (S2S) database, we characterize sudden stratospheric warming (SSW) events with multi-centennial return times. Consistent results are found between alternative methods, including basic counting strategies and Markov state modeling. By carefully combining trajectories together, we obtain estimates of SSW frequencies and their seasonal distributions that are consistent with reanalysis-derived estimates for moderately rare events, but with much tighter uncertainty bounds, and which can be extended to events of unprecedented severity that have not yet been observed historically. These methods hold potential for assessing extreme events throughout the climate system, beyond this example of stratospheric extremes.

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arXiv2023

Inner Habitable Zone Boundary for Eccentric Exoplanets

The climate of a planet can be strongly affected by its eccentricity due to variations in the stellar flux. There are two limits for the dependence of the inner habitable zone boundary (IHZ) on eccentricity: (1) the mean-stellar flux approximation ($S_{\mbox{IHZ}} \propto \sqrt{1-e^2}$), in which the temperature is approximately constant throughout the orbit, and (2) the maximum-stellar flux approximation ($S_{\mbox{IHZ}} \propto (1-e)^2$), in which the temperature adjusts instantaneously to the stellar flux. Which limit is appropriate is determined by the dimensionless parameter $Π= \frac{C}{BP}$, where $C$ is the heat capacity of the planet, $P$ is the orbital period, and $B=\frac{\partial Ω}{\partial T_s}$, where $Ω$ is the outgoing longwave radiation and $T_s$ is the surface temperature. We use the Buckingham $Π$ theorem to derive an analytical function for the IHZ in terms of eccentricity and $Π$. We then build a time-dependent energy balance model to resolve the surface temperature evolution and constrain our analytical result. We find that $Π$ must be greater than about $\sim 1$ for the mean-stellar flux approximation to be nearly exact and less than about $\sim 0.01$ for the maximum-stellar flux approximation to be nearly exact. In addition to assuming a constant heat capacity, we also consider the effective heat capacity including latent heat (evaporation and precipitation). We find that for planets with an Earth-like ocean, the IHZ should follow the mean-stellar flux limit for all eccentricities. This work will aid in the prioritization of potentially habitable exoplanets with non-zero eccentricity for follow-up characterization.

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arXiv2022

Data-driven transition path analysis yields a statistical understanding of sudden stratospheric warming events in an idealized model

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 (1976), 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 \emph{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 \emph{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.

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arXiv2022

The Effect of Ocean Salinity on Climate and Its Implications for Earth's Habitability

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 vs. 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 g/kg 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 pCO$_2$ threshold at which Snowball glaciation occurs in our Archean scenarios. In combination with higher levels of greenhouse gases such as CO$_2$ and CH$_4$, 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.

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arXiv2022

Critical percolation threshold restricts late-summer Arctic sea ice melt pond coverage

During the summer, vast regions of Arctic sea ice are covered by meltwater ponds that significantly lower the ice reflectivity and accelerate melting. Ponds develop over the melt season through an initial rapid growth stage followed by drainage through macroscopic holes. Recent analysis of melt pond photographs indicates that late-summer ponds exist near the critical percolation threshold, a special pond coverage fraction below which the ponds are largely disconnected and above which they are highly connected. Here, we show that the percolation threshold, a statistical property of ice topography, constrains pond evolution due to pond drainage through macroscopic holes. We show that it sets the approximate upper limit and scales pond coverage throughout its evolution after the beginning of drainage. Furthermore, we show that the rescaled pond coverage during drainage is a universal function of a single non-dimensional parameter, $η$, roughly interpreted as the number of drainage holes per characteristic area of the surface. This universal curve allows us to formulate an equation for pond coverage time-evolution during and after pond drainage that captures the dependence on environmental parameters and is supported by observations on undeformed first-year ice. This equation reveals that pond coverage is highly sensitive to environmental parameters, suggesting that modeling uncertainties could be reduced by more directly parameterizing the ponds' natural parameter, $η$. Our work uncovers previously unrecognized constraints on melt pond physics and places ponds within a broader context of phase transitions and critical phenomena. Therefore, it holds promise for improving ice-albedo parameterizations in large-scale models.

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arXiv2022

Snow topography on undeformed Arctic sea ice captured by an idealized "snow dune" model

Our ability to predict the future of Arctic sea ice is limited by ice's sensitivity to detailed surface conditions such as the distribution of snow and melt ponds. Snow on top of the ice decreases ice's thermal conductivity, increases its reflectivity (albedo), and provides a source of meltwater for melt ponds during summer that decrease the ice's albedo. In this paper, we develop a simple model of pre-melt snow topography that accurately describes snow cover of flat, undeformed Arctic sea ice on several study sites for which data was available. The model considers a surface that is a sum of randomly sized and placed "snow dunes" represented as Gaussian mounds. This model generalizes the "void model" of Popović et al. (2018) and, as such, accurately describes the statistics of melt pond geometry. We test this model against detailed LiDAR measurements of the pre-melt snow topography. We show that the model snow-depth distribution is statistically indistinguishable from the measurements on flat ice, while small disagreement exists if the ice is deformed. We then use this model to determine analytic expressions for the conductive heat flux through the ice and for melt pond coverage evolution during an early stage of pond formation. We also formulate a criterion for ice to remain pond-free throughout the summer. Results from our model could be directly included in large-scale models, thereby improving our understanding of energy balance on sea ice and allowing for more reliable predictions of Arctic sea ice in a future climate.

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arXiv2021

Rare Event Sampling Improves Mercury Instability Statistics

Due to the chaotic nature of planetary dynamics, there is a non-zero probability that Mercury's orbit will become unstable in the future. Previous efforts have estimated the probability of this happening between 3 and 5 billion years in the future using a large number of direct numerical simulations with an N-body code, but were not able to obtain accurate estimates before 3 billion years in the future because Mercury instability events are too rare. In this paper we use a new rare event sampling technique, Quantile Diffusion Monte Carlo (QDMC), to estimate that the probability of a Mercury instability event in the next 2 billion years is approximately $10^{-4}$ in the REBOUND N-body code. We show that QDMC provides unbiased probability estimates at a computational cost of up to 100 times less than direct numerical simulation. QDMC is easy to implement and could be applied to many problems in planetary dynamics in which it is necessary to estimate the probability of a rare event.

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arXiv2021

Learning forecasts of rare stratospheric transitions from short simulations

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 \emph{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 \emph{short} compared to the timescale 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 (1976) 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 timescales 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.

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arXiv2021

Probing the capability of future direct imaging missions to spectrally constrain the frequency of Earth-like planets

A critical question in astrobiology is whether exoEarth candidates (EECs) are Earth-like, in that they originate life that progressively oxygenates their atmospheres similarly to Earth. We propose answering this question statistically by searching for O2 and O3 on EECs with missions such as HabEx or LUVOIR. We explore the ability of these missions to constrain the fraction, fE, of EECs that are Earth-like in the event of a null detection of O2 or O3 on all observed EECs. We use the Planetary Spectrum Generator to simulate observations of EECs with O2 and O3 levels based on Earth's history. We consider four instrument designs: LUVOIR-A (15m), LUVOIR-B (8m), HabEx with a starshade (4m, "HabEx/SS"), HabEx without a starshade (4m, "HabEx/no-SS"); as well as three estimates of the occurrence rate of EECs (eta_earth): 24%, 5%, and 0.5%. In the case of a null-detection, we find that for eta_earth = 24%, LUVOIR-A, LUVOIR-B, and HabEx/SS would constrain fE to <= 0.094, <= 0.18, and <= 0.56, respectively. This also indicates that if fE is greater than these upper limits, we are likely to detect O3 on at least 1 EEC. Conversely, we find that HabEx/no-SS cannot constrain fE, due to the lack of an coronagraph ultraviolet channel. For eta_earth = 5%, only LUVOIR-A and LUVOIR-B would be able to constrain fE, to <= 0.45 and <= 0.85, respectively. For eta_earth = 0.5%, none of the missions would allow us to constrain fE, due to the low number of detectable EECs. We conclude that the ability to constrain fE is more robust to uncertainties in eta_earth for missions with larger aperture mirrors. However all missions are susceptible to an inconclusive null detection if eta_earth is sufficiently low.

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arXiv2020

Non-detection of O$_2$/O$_3$ informs frequency of Earth-like planets with LUVOIR but not HabEx

A critical question in the search for extraterrestrial life is whether exoEarths are Earth-like, in that they host life that progressively oxygenates their atmospheres roughly following Earth's oxygenation history. This question could be answered statistically by searching for O$_2$ and O$_3$ on exoEarths detected by HabEx or LUVOIR. The point of this paper is to compare the ability of HabEx and LUVOIR to prevent a false negative answer to this question, in which we do not detect O$_2$ or O$_3$ on any planet even if all exoEarths are Earth-like. Our approach is to assign O$_2$ and O$_3$ values drawn from Earth's history to a distribution of detectable exoEarths and determine whether O$_2$ and O$_3$ would be detectable using the Planetary Spectrum Generator. We find that if exoEarths tend to be Earth-like, we expect to detect O$_3$ with a LUVOIR-sized instrument. We also find that LUVOIR is unlikely to have a false negative scenario in the context of searching for Earth-like life on its targeted exoEarths. Because of that, if LUVOIR does not detect O$_2$ or O$_3$ on any exoEarths, we will be able to constrain the maximum number of exoEarths that could be Earth-like. In contrast, we find that even if all exoEarths are Earth-like, HabEx has up to a 22% chance of not detecting O$_2$ or O$_3$ on any of them. This is because HabEx will detect less planets and cannot reliably detect O$_2$ and O$_3$ at all potential Proterozoic levels. This is a strong argument for building a larger telescope such as LUVOIR if we want to determine whether exoEarths tend to be Earth-like.

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arXiv2020

Hurricane genesis is favorable on terrestrial exoplanets orbiting late-type M dwarf stars

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 than 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 $\sim 8-10~\mathrm{days}$. 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.

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arXiv2020

The Effect of Substellar Continent Size on Ocean Dynamics of Proxima Centauri b

The potential habitability of tidally locked planets orbiting M-dwarf stars has been widely investigated in recent work, typically with a non-dynamic ocean and without continents. On Earth, ocean dynamics are a primary means of heat and nutrient distribution. Continents are a critical source of nutrients, strongly influence ocean dynamics, and participate in climate regulation. In this work, we investigate how the size of a substellar land mass affects the oceans ability to transport heat and upwell nutrients on the tidally locked planet Proxima Centauri b using the ROCKE-3D coupled ocean-atmosphere General Circulation Model (GCM). We find that dayside ice-free ocean and nutrient delivery to the mixed layer via upwelling are maintained across all continent sizes. We also find that Proxima Centauri bs climate is more sensitive to differences among atmospheric GCMs than to the inclusion of ocean dynamics in ROCKE-3D. Finally, we find that Proxima Centauri b transitions from a lobster state where ocean heat transport distributes heat away from the substellar point to an eyeball state where heat transport is restricted and surface temperature decreases symmetrically from the substellar point when the continent size exceeds about 20 percent of the surface area. Our work suggests that both a dynamic ocean and continents are unlikely to decrease the habitability prospects of nearby tidally locked targets like Proxima Centauri b that could be investigated with future observations by the James Webb Space Telescope (JWST).

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arXiv2020

Oceanographic Considerations for Exoplanet Life Detection

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 GCM. 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.

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arXiv2020

Robustness of Gaian Feedbacks to Climate Perturbations

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.

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arXiv2019

Simulations of Water Vapor and Clouds on Rapidly Rotating and Tidally Locked Planets: a 3D Model Intercomparison

Robustly modeling the inner edge of the habitable zone is essential for determining the most promising potentially habitable exoplanets for atmospheric characterization. Global climate models (GCMs) have become the standard tool for calculating this boundary, but divergent results have emerged among the various GCMs. In this study, we perform an inter-comparison of standard GCMs used in the field on a rapidly rotating planet receiving a G-star spectral energy distribution and on a tidally locked planet receiving an M-star spectral energy distribution. Experiments both with and without clouds are examined. We find relatively small difference (within 8 K) in global-mean surface temperature simulation among the models in the G-star case with clouds. In contrast, the global-mean surface temperature simulation in the M-star case is highly divergent (20-30 K). Moreover, even differences in the simulated surface temperature when clouds are turned off are significant. These differences are caused by differences in cloud simulation and/or radiative transfer, as well as complex interactions between atmospheric dynamics and these two processes. For example we find that an increase in atmospheric absorption of shortwave radiation can lead to higher relative humidity at high altitudes globally and, therefore, a significant decrease in planetary radiation emitted to space. This study emphasizes the importance of basing conclusions about planetary climate on simulations from a variety of GCMs and motivates the eventual comparison of GCM results with terrestrial exoplanet observations to improve their performance.

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arXiv2019

Clouds will likely prevent the detection of water vapor in JWST transmission spectra of terrestrial exoplanets

We are on the verge of characterizing the atmospheres of terrestrial exoplanets in the habitable zones of M dwarf stars. Due to their large planet-to-star radius ratios and higher frequency of transits, terrestrial exoplanets orbiting M dwarf stars are favorable for transmission spectroscopy. In this work, we quantify the effect that water clouds have on the amplitude of water vapor transmission spectral features of terrestrial exoplanets orbiting M dwarf stars. To do so, we make synthetic transmission spectra from general circulation model (GCM) experiments of tidally locked planets. We improve upon previous work by considering how varying a broad range of planetary parameters affects transmission spectra. We find that clouds lead to a 10-100 times increase in the number of transits required to detect water features with the James Webb Space Telescope (JWST) with varying rotation period, incident stellar flux, surface pressure, planetary radius, and surface gravity. We also find that there is a strong increase in the dayside cloud coverage in our GCM simulations with rotation periods $\gtrsim 12 \ \mathrm{days}$ for planets with Earth's radius. This increase in cloud coverage leads to even stronger muting of spectral features for slowly rotating exoplanets orbiting M dwarf stars. We predict that it will be extremely challenging to detect water transmission features in the atmospheres of terrestrial exoplanets in the habitable zone of M dwarf stars with JWST. However, species that are well-mixed above the cloud deck (e.g., CO$_2$ and CH$_4$) may still be detectable on these planets with JWST.

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arXiv2019

No Snowball on Habitable Tidally Locked Planets with a Dynamic Ocean

Terrestrial planets orbiting within the habitable zones of M-stars are likely to become tidally locked in a 1:1 spin:orbit configuration and are prime targets for future characterization efforts. An issue of importance for the potential habitability of terrestrial planets is whether they could experience snowball events (periods of global glaciation). Previous work using an intermediate complexity atmospheric Global Climate Model (GCM) with no ocean heat transport suggested that tidally locked planets would smoothly transition to a snowball, in contrast with Earth, which has bifurcations and hysteresis in climate state associated with global glaciation. In this paper, we use a coupled ocean-atmosphere GCM (ROCKE-3D) to model tidally locked planets with no continents. We chose this configuration in order to consider a case that we expect to have high ocean heat transport. We show that including ocean heat transport does not reintroduce the snowball bifurcation. An implication of this result is that a tidally locked planet in the habitable zone is unlikely to be found in a snowball state for a geologically significant period of time.

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