Spatially resolving exoplanet features from single-point observations is essential for evaluating the potential habitability of exoplanets. The ultimate goal of this protocol is to determine whether these planetary worlds harbor geological features and/or climate systems. We present a method of extracting information from multi-wavelength single-point light curves and retrieving surface maps. It uses singular value decomposition (SVD) to separate sources that contribute to light curve variations and infer the existence of partially cloudy climate systems. Through analysis of the time series obtained from SVD, physical attributions of principal components (PCs) could be inferred without assumptions of any spectral properties. Combining with viewing geometry, it is feasible to reconstruct surface maps if one of the PCs are found to contain surface information. Degeneracy originated from convolution of the pixel geometry and spectrum information determines the quality of reconstructed surface maps, which requires the introduction of regularization. For the purpose of demonstrating the protocol, multi-wavelength light curves of Earth, which serves as a proxy exoplanet, are analyzed. Comparison between the results and the ground truth is presented to show the performance and limitation of the protocol. This work provides a benchmark for future generalization of exoplanet applications
We investigate the potential for the James Webb Space Telescope (JWST) to detect and characterize the atmospheres of the sub-Neptunian exoplanets in the TOI-270 system. Sub-Neptunes are considered more likely to be water worlds than gas dwarfs. We model their atmospheres using three atmospheric compositions two examples of hydrogen-dominated atmospheres and a water-dominated atmosphere. We then simulate the infrared transmission spectra of these atmospheres for JWST instrument modes optimized for transit observation of exoplanet atmospheres: NIRISS, NIRSpec, and MIRI. We then predict the observability of each exoplanets atmosphere. TOI-270c and d are excellent targets for detecting atmospheres with JWST transmission spectroscopy, requiring only 1 transit observation with NIRISS, NIRSpec, and MIRI; higher signal-to-noise ratio can be obtained for a clear H-rich atmosphere. Fewer than three transits with NIRISS and NIRSpec may be enough to reveal molecular features. Water-dominated atmospheres require more transits. Water spectral features in water-dominated atmospheres may be detectable with NIRISS in two or three transits. We find that the detection of spectral features in a cloudy, H-rich atmosphere does not require integrations as long as those required for the water-dominated atmosphere, which is consistent with the differences in atmospheric mean molecular weight. TOI-270c and d could be prime targets for JWST transit observations of sub-Neptune atmospheres. These results provide useful predictions for observers who may propose to use JWST to detect and characterize the TOI-270 planet atmospheres.
We propose that the building blocks of RNA (nucleobases and ribose) bound to self-assembled prebiotic membranes. We have previously demonstrated that the bases bind to membranes composed of a prebiotic fatty acid, but evidence for the binding of sugars has remained a technical challenge. Here, we used pulsed-field gradient NMR spectroscopy to demonstrate that ribose and other sugars bind to membranes of decanoic acid. Moreover, the binding of some bases is strongly enhanced when they are linked to ribose to form a nucleoside or – with the addition of phosphate – a nucleotide. This enhanced binding could have played a role in the molecular evolution leading to the production of RNA.
The search for spectroscopic biosignatures with the next generation of space telescopes could provide observational constraints on the abundance of exoplanets with signs of life. An extension of this spectroscopic characterization of exoplanets is the search for observational evidence of technology, known as technosignatures. Current mission concepts that would observe biosignatures from ultraviolet to near-infrared wavelengths could place upper limits on the fraction of planets in the Galaxy that host life, although such missions tend to have relatively limited capabilities of constraining the prevalence of technosignatures at mid-infrared wavelengths. Yet searching for technosignatures alongside biosignatures would provide important knowledge about the future of our civilization. If planets with technosignatures are abundant, then we can increase our confidence that the hardest step in planetary evolutionthe Great Filteris probably in our past. But if we find that life is commonplace while technosignatures are absent, then this would increase the likelihood that the Great Filter awaits to challenge us in the future.
Robust atmospheric and radiative transfer modeling will be required to properly interpret reflected-light and thermal emission spectra of terrestrial exoplanets. This will help break observational degeneracies between the numerous atmospheric, planetary, and stellar factors that drive planetary climate. Here, we simulate the climates of earthlike worlds around the Sun with increasingly slow rotation periods, from earthlike to fully Sun-synchronous, using the ROCKE-3D general circulation model. We then provide these results as input to the Spectral Planet Model, which employs the Spectral Mapping Atmospheric Radiative Transfer model to simulate the spectra of a planet as it would be observed from a future space-based telescope. We find that the primary observable effects of slowing planetary rotation rate are the altered cloud distributions, altitudes, and opacities that subsequently drive many changes to the spectra by altering the absorption band depths of biologically relevant gas species (e.g., ${{rm{H}}}_{2}{rm{O}}$, ${{rm{O}}}_{2}$, and ${{rm{O}}}_{3}$). We also identify a potentially diagnostic feature of synchronously rotating worlds in mid-infrared ${{rm{H}}}_{2}{rm{O}}$ absorption/emission lines.
Multiple hypotheses/models have been put forward regarding Earth’s cooling history. Searching for life beyond Earth has brought these models into a new light as they connect to an energy source that life can tap. Discriminating between different cooling models and adapting them to aid in the assessment of planetary habitability has been hampered by a lack of uncertainty quantification. Here, we provide an uncertainty quantification that accounts for a range of interconnected model uncertainties. This involved calculating over a million individual model evolutions to determine uncertainty metrics. Accounting for uncertainties means that model results must be evaluated in a probabilistic sense, even though the underlying models are deterministic. The uncertainty analysis was used to quantify the degree to which different models can satisfy observational constraints on the Earth’s cooling. For the Earth’s cooling history, uncertainty leads to ambiguitymultiple models, based on different hypotheses, can match observations. This has implications for using such models to forecast conditions for exoplanets that share Earth characteristics but are older than the Earth, i.e., ambiguity has implications for modeling the long-term life potential of terrestrial planets. Even for the most earthlike planet we know of, the Earth itself, model uncertainty and ambiguity leads to large forecast spreads. Given that Earth has the best data constraints, we should expect larger spreads for models of terrestrial planets, in general. The uncertainty analysis provided here can be expanded by coupling planetary cooling models to climate models and propagating uncertainty between them to assess habitability from a probabilistic view.
Multiple hypotheses/models have been put forward regarding Earth’s cooling history. Searching for life beyond Earth has brought these models into a new light as they connect to an energy source that life can tap. Discriminating between different cooling models and adapting them to aid in the assessment of planetary habitability has been hampered by a lack of uncertainty quantification. Here, we provide an uncertainty quantification that accounts for a range of interconnected model uncertainties. This involved calculating over a million individual model evolutions to determine uncertainty metrics. Accounting for uncertainties means that model results must be evaluated in a probabilistic sense, even though the underlying models are deterministic. The uncertainty analysis was used to quantify the degree to which different models can satisfy observational constraints on the Earth’s cooling. For the Earth’s cooling history, uncertainty leads to ambiguitymultiple models, based on different hypotheses, can match observations. This has implications for using such models to forecast conditions for exoplanets that share Earth characteristics but are older than the Earth, i.e., ambiguity has implications for modeling the long-term life potential of terrestrial planets. Even for the most earthlike planet we know of, the Earth itself, model uncertainty and ambiguity leads to large forecast spreads. Given that Earth has the best data constraints, we should expect larger spreads for models of terrestrial planets, in general. The uncertainty analysis provided here can be expanded by coupling planetary cooling models to climate models and propagating uncertainty between them to assess habitability from a probabilistic view.
To evaluate the influence of selection on gene content variation in hydrothermal vent microbial populations, we examined 22 metagenome-assembled genomes (MAGs) (70 to 97% complete) from the ubiquitous vent Epsilonbacteraeota genus Sulfurovum that were recovered from two deep-sea hydrothermal vent regions, Axial Seamount in the northeastern Pacific Ocean (13 MAGs) and the Mid-Cayman Rise in the Caribbean Sea (9 MAGs). Genes involved in housekeeping functions were highly conserved across Sulfurovum lineages. However, genes involved in environment-specific functions, and in particular phosphate regulation, were found mostly in Sulfurovum genomes from the Mid-Cayman Rise in the low-phosphate Atlantic Ocean environment, suggesting that nutrient limitation is an important selective pressure for these bacteria.
Chemical disequilibrium in exoplanetary atmospheres (detectable with remote spectroscopy) can indicate life. The modern Earth’s atmosphere–ocean system has a much larger chemical disequilibrium than other solar system planets with atmospheres because of oxygenic photosynthesis. However, no analysis exists comparing disequilibrium on lifeless, prebiotic planets to disequilibrium on worlds with primitive chemotrophic biospheres that live off chemicals and not light. Here, we use a photochemical–microbial ecosystem model to calculate the atmosphere–ocean disequilibria of Earth with no life and with a chemotrophic biosphere.
A key factor in determining the potential habitability of synchronously rotating planets is the strength of the atmospheric boundary layer inversion between the dark side surface and the free atmosphere. Here we analyze data obtained from polar night measurements at the South Pole and Alert Canada, which are the closest analogs on Earth to conditions on the dark sides of synchronously rotating exoplanets without and with a maritime influence, respectively. On Earth, such inversions rarely exceed 30 K in strength, because of the effect of turbulent mixing induced by phenomena such as so-called “mesoscale slope winds,” which have horizontal scales of 10100 s of km, suggesting a similar constraint to near-surface dark side inversions. We discuss the sensitivity of inversion strength to factors such as orography and the global-scale circulation, and compare them to a simulation of the planet Proxima Centauri b. Our results demonstrate the importance of comparisons with Earth data in exoplanet research, and highlight the need for further studies of the exoplanet atmospheric collapse problem using mesoscale and eddy-resolving models.
We model the long-term X-ray and ultraviolet (XUV) luminosity of TRAPPIST-1 to constrain the evolving high-energy radiation environment experienced by its planetary system. Using a Markov Chain Monte Carlo (MCMC) method, we derive probabilistic constraints for TRAPPIST-1’s stellar and XUV evolution that account for observational uncertainties, degeneracies between model parameters, and empirical data of low-mass stars. We constrain TRAPPIST-1’s mass to m sstarf = 0.089 ± 0.001 M ? and find that its early XUV luminosity likely saturated at ${mathrm{log}}_{10}({L}_{mathrm{XUV}}/{L}_{mathrm{bol}})=-{3.03}_{-0.12}^{+0.23}$. From the posterior distribution, we infer that there is a ~40% chance that TRAPPIST-1 is still in the saturated phase today, suggesting that TRAPPIST-1 has maintained high activity and L XUV/L bol ? 10?3 for several gigayears. TRAPPIST-1’s planetary system therefore likely experienced a persistent and extreme XUV flux environment, potentially driving significant atmospheric erosion and volatile loss. The inner planets likely received XUV fluxes ~103104 times that of the modern Earth during TRAPPIST-1’s ~1 Gyr long pre-main-sequence phase. Deriving these constraints via MCMC is computationally nontrivial, so scaling our methods to constrain the XUV evolution of a larger number of M dwarfs that harbor terrestrial exoplanets would incur significant computational expenses. We demonstrate that approxposterior, an open source Python machine learning package for approximate Bayesian inference using Gaussian processes, accurately and efficiently replicates our analysis using 980 times less computational time and 1330 times fewer simulations than MCMC sampling using emcee. We find that approxposterior derives constraints with mean errors on the best-fit values and 1? uncertainties of 0.61% and 5.5%, respectively, relative to emcee.
The dynamical structure of the Solar System can be explained by a period of orbital instability experienced by the giant planets. While a late instability was originally proposed to explain the Late Heavy Bombardment, recent work favors an early instability. Here we model the early dynamical evolution of the outer Solar System to self-consistently constrain the most likely timing of the instability.
The balance between carbon outgassing and carbon burial controls Earth’s climate on geological timescales. Carbon removal in carbonates consumes both atmospheric carbon and ocean carbonate alkalinity sourced from silicate weathering on the land or seafloor. Reverse weathering (RW) refers to clay-forming reactions that consume alkalinity but not carbon. If the cations (of alkalinity) end up in clay minerals rather than in the carbonates, carbon remains as atmospheric , warming the climate. Higher silicate weathering fluxes and warmer temperatures are then required to balance the carbon cycle. It has been proposed that high dissolved silica concentrations resulting from the absence of ecologically significant biogenic silica precipitation in the Precambrian drove larger RW fluxes than today, affecting the climate. Here, we present the first fully coupled carbon-silica cycle model for post-Hadean Earth history that models climate evolution self-consistently (available as open source code). RW fluxes and biogenic silica deposition fluxes are represented using a sediment diagenesis model that can reproduce modern conditions. We show that a broad range of climate evolutions are possible but most plausible scenarios produce Proterozoic warming (+5 K relative to without RW), which could help explain the sustained warmth of the Proterozoic despite lower insolation. RW in the Archean is potentially more muted due to a lower land fraction and sedimentation rate. Key model uncertainties are the modern reverse weathering flux, the rate coefficient for RW reactions, and the solubility of authigenic clays. Consequently, within the large uncertainties, other self-consistent scenarios where Proterozoic RW was unimportant cannot be excluded. Progress requires better constraints on parameters governing RW reaction rates including explicit consideration of cation-limitations to Precambrian RW, and perhaps new inferences from Si or Li isotopes systems.
The search for water-rich Earth-sized exoplanets around low-mass stars is rapidly gaining attention because they represent the best opportunity to characterize habitable planets in the near future. Understanding the atmospheres of these planets and determining the optimal strategy for characterizing them through transmission spectroscopy with our upcoming instrumentation is essential in order to constrain their environments. For this study, we present simulated transmission spectra of tidally locked Earth-sized ocean-covered planets around late-M to mid-K stellar spectral types, utilizing the results of general circulation models previously published by Kopparapu et al. as inputs for our radiative transfer calculations performed using NASA’s Planetary Spectrum Generator (psg.gsfc.nasa.gov). We identify trends in the depth of H2O spectral features as a function of planet surface temperature and rotation rate. These trends allow us to calculate the exposure times necessary to detect water vapor in the atmospheres of aquaplanets through transmission spectroscopy with the upcoming James Webb Space Telescope as well as several future flagship space telescope concepts under consideration (the Large UV Optical Infrared Surveyor and the Origins Space Telescope) for a target list constructed from the Transiting Exoplanet Survey Satellite (TESS) Input Catalog (TIC). Our calculations reveal that transmission spectra for water-rich Earth-sized planets around low-mass stars will be dominated by clouds, with spectral features <20 ppm, and only a small subset of TIC stars would allow for the characterization of an ocean planet in the habitable zone. We thus present a careful prioritization of targets that are most amenable to follow-up characterizations with next-generation instrumentation, in order to assist the community in efficiently utilizing precious telescope time.
One of the main science motivations for the ESA PLAnetary Transit and Oscillations (PLATO) mission is to measure exoplanet transit radii with 3 per cent precision. In addition to flares and starspots, stellar oscillations and granulation will enforce fundamental noise floors for transiting exoplanet radius measurements. We simulate light curves of Earth-sized exoplanets transiting continuum intensity images of the Sun taken by the Helioseismic and Magnetic Imager (HMI) instrument aboard the Solar Dynamics Observatory (SDO) to investigate the uncertainties introduced on the exoplanet radius measurements by stellar granulation and oscillations. After modelling the solar variability with a Gaussian process, we find that the amplitude of solar oscillations and granulation is of order 100 ppm similar to the depth of an Earth transit and introduces a fractional uncertainty on the depth of transit of 0.73 per cent assuming four transits are observed over the mission duration. However, when we translate the depth measurement into a radius measurement of the planet, we find a much larger radius uncertainty of 3.6 per cent. This is due to a degeneracy between the transit radius ratio, the limb darkening, and the impact parameter caused by the inability to constrain the transit impact parameter in the presence of stellar variability. We find that surface brightness inhomogeneity due to photospheric granulation contributes a lower limit of only 2 ppm to the photometry in-transit. The radius uncertainty due to granulation and oscillations, combined with the degeneracy with the transit impact parameter, accounts for a significant fraction of the error budget of the PLATO mission, before detector or observational noise is introduced to the light curve. If it is possible to constrain the impact parameter or to obtain follow-up observations at longer wavelengths where limb darkening is less significant, this may enable higher precision radius measurements.
We attempted to use vesicle sizes in lavas erupted near sea-level from the ~2.9 Ga Pongola Supergroup from Mahlangatsha and Mooihoek, eSwatini (formerly Swaziland) and the White Mfolozi River gorge of KwaZulu-Natal, South Africa to provide further Archean paleobarometric data. However, reliable results were unobtainable due to small and scarce amygdales, irregular vesicle morphologies and metamorphic mineralogical homogenization preventing the use of X-ray Computed Tomography for accurate vesicle size determination. Researchers attempting paleobarometric analysis using lava vesicle sizes should henceforth avoid these areas of the Pongola Supergroup and instead look at other subaerially emplaced lava flows. With this being only the second time this method has been used on Precambrian rocks, we provide a list of guidelines informed by this study to aid future attempts at vesicular paleobarometry.
Hyperspectral observations have become one of the most popular and powerful methods for atmospheric remote sensing, and are widely used for temperature, gas, aerosol, and cloud retrievals. However, accurate forward radiative transfer simulations are computationally expensive since typical line-by-line approaches involve a large number of monochromatic radiative transfer calculations. This study explores the feasibility of machine learning techniques (using neural network (NN) as an example) for fast hyperspectral radiative transfer simulations, by performing calculations at a small fraction of hyperspectral wavelengths and extending them across the entire spectral range. Results from the NN model are compared with those from a principal component analysis (PCA) model, which uses a similar principle of dimensionality reduction. We consider hyperspectral radiances from both actual satellite observations and accurate line-by-line simulations. The NN model can alleviate the computational burden by two to three orders of magnitude, and generate radiances with small relative errors (generally less than 0.5% compared to exact calculations); the performance of the NN model is better than that of the PCA model. The model can be further improved by optimizing the training procedure and parameters, the representative wavelengths, and the machine learning technique itself.
We present gray gas general circulation model (GCM) simulations of the tidally locked mini-Neptune GJ 1214b. On timescales of 100010,000 Earth days, our results are comparable to previous studies of the same planet, in the sense that they all exhibit two off-equatorial eastward jets. Over much longer integration times (50,000250,000 Earth days) we find a significantly different circulation and observational features. The zonal-mean flow transitions from two off-equatorial jets to a single wide equatorial jet that has higher velocity and extends deeper. The hot spot location also shifts eastward over the integration time. Our results imply a convergence time far longer than the typical integration time used in previous studies. We demonstrate that this long convergence time is related to the long radiative timescale of the deep atmosphere and can be understood through a series of simple arguments. Our results indicate that particular attention must be paid to model convergence time in exoplanet GCM simulations, and that other results on the circulation of tidally locked exoplanets with thick atmospheres may need to be revisited.
The atmosphere of the Archean eon—one-third of Earth’s history—is important for understanding the evolution of our planet and Earth-like exoplanets. New geological proxies combined with models constrain atmospheric composition. They imply surface O2 levels <10−6 times present, N2 levels that were similar to today or possibly a few times lower, and CO2 and CH4 levels ranging ~10 to 2500 and 102 to 104 times modern amounts, respectively. The greenhouse gas concentrations were sufficient to offset a fainter Sun. Climate moderation by the carbon cycle suggests average surface temperatures between 0° and 40°C, consistent with occasional glaciations. Isotopic mass fractionation of atmospheric xenon through the Archean until atmospheric oxygenation is best explained by drag of xenon ions by hydrogen escaping rapidly into space. These data imply that substantial loss of hydrogen oxidized the Earth. Despite these advances, detailed understanding of the coevolving solid Earth, biosphere, and atmosphere remains elusive, however.
Upcoming telescopes such as the James Webb Space Telescope (JWST), the European Extremely Large Telescope (E-ELT), the Thirty Meter Telescope (TMT) or the Giant Magellan Telescope (GMT) may soon be able to characterize, through transmission, emission or reflection spectroscopy, the atmospheres of rocky exoplanets orbiting nearby M dwarfs. One of the most promising candidates is the late M-dwarf system TRAPPIST-1, which has seven known transiting planets for which transit timing variation (TTV) measurements suggest that they are terrestrial in nature, with a possible enrichment in volatiles. Among these seven planets, TRAPPIST-1e seems to be the most promising candidate to have habitable surface conditions, receiving ?66?% of the Earth’s incident radiation and thus needing only modest greenhouse gas inventories to raise surface temperatures to allow surface liquid water to exist. TRAPPIST-1e is, therefore, one of the prime targets for the JWST atmospheric characterization. In this context, the modeling of its potential atmosphere is an essential step prior to observation. Global climate models (GCMs) offer the most detailed way to simulate planetary atmospheres. However, intrinsic differences exist between GCMs which can lead to different climate prediction and thus observability of gas and/or cloud features in transmission and thermal emission spectra. Such differences should preferably be known prior to observations. In this paper we present a protocol to intercompare planetary GCMs. Four testing cases are considered for TRAPPIST-1e, but the methodology is applicable to other rocky exoplanets in the habitable zone. The four test cases included two land planets composed of modern-Earth and pure-CO2 atmospheres and two aqua planets with the same atmospheric compositions. Currently, there are four participating models (LMDG, ROCKE-3D, ExoCAM, UM); however, this protocol is intended to let other teams participate as well.
We derive analytic, closed-form solutions for the light curve of a planet transiting a star with a limb-darkening profile that is a polynomial function of the stellar elevation, up to an arbitrary integer order. We provide improved analytic expressions for the uniform, linear, and quadratic limb-darkened cases, as well as novel expressions for higher-order integer powers of limb darkening. The formulae are crafted to be numerically stable over the expected range of usage. We additionally present analytic formulae for the partial derivatives of instantaneous flux with respect to the radius ratio, impact parameter, and limb-darkening coefficients. These expressions are rapid to evaluate and compare quite favorably in speed and accuracy to existing transit light-curve codes. We also use these expressions to numerically compute the first partial derivatives of exposure-time-averaged transit light curves with respect to all model parameters. An additional application is modeling eclipsing binary or eclipsing multiple star systems in cases where the stars may be treated as spherically symmetric. We provide code which implements these formulae in C++, Python, IDL, and Julia, with tests and examples of usage (https://github.com/rodluger/Limbdark.jl).
Models of planet formation are built on underlying physical processes. In order to make sense of the origin of the planets we must first understand the origin of their building blocks. This review comes in two parts. The first part presents a detailed description of six key mechanisms of planet formation: 1) The structure and evolution of protoplanetary disks 2) The formation of planetesimals 3) Accretion of protoplanets 4) Orbital migration of growing planets 5) Gas accretion and giant planet migration 6) Resonance trapping during planet migration. While this is not a comprehensive list, it includes processes for which our understanding has changed in recent years or for which key uncertainties remain.
The second part of this review shows how global models are built out of planet formation processes. We present global models to explain different populations of known planetary systems, including close-in small/low-mass planets (i.e., super-Earths), giant exoplanets, and the Solar System’s planets. We discuss the different sources of water on rocky exoplanets, and use cosmochemical measurements to constrain the origin of Earth’s water. We point out the successes and failings of different models and how they may be falsified.
Finally, we lay out a path for the future trajectory of planet formation studies.
The upcoming launch of the James Webb Space Telescope (JWST) combined with the unique features of the TRAPPIST-1 planetary system should enable the young field of exoplanetology to enter into the realm of temperate Earth-sized worlds. Indeed, the proximity of the system (12pc) and the small size (0.12 Rsun) and luminosity (0.05 Lsun) of its host star should make the comparative atmospheric characterization of its seven transiting planets within reach of an ambitious JWST program. Given the limited lifetime of JWST, the ecliptic location of the star that limits its visibility to 100d per year, the large number of observational time required by this study, and the numerous observational and theoretical challenges awaiting it, its full success will critically depend on a large level of coordination between the involved teams and on the support of a large community. In this context, we present here a community initiative aiming to develop a well-defined sequential structure for the study of the system with JWST and to coordinate on every aspect of its preparation and implementation, both on the observational (e.g. study of the instrumental limitations, data analysis techniques, complementary space-based and ground-based observations) and theoretical levels (e.g. model developments and comparison, retrieval techniques, inferences). Depending on the outcome of the first phase of JWST observations of the planets, this initiative could become the seed of a major JWST Legacy Program devoted to the study of TRAPPIST-1.
A planet’s climate can be strongly affected by its orbital eccentricity and obliquity. Here we use a 1-dimensional energy balance model modified to include a simple runaway greenhouse (RGH) parameterization to explore the effects of these two parameters on the climate of Earth-like aqua planets – completely ocean-covered planets – orbiting F-, G-, K-, and M-dwarf stars. We find that the range of instellations for which planets exhibit habitable surface conditions throughout an orbit decreases with increasing eccentricity. However, the appearance of temporarily habitable conditions during an orbit creates an eccentric habitable zone (EHZ) that is sensitive to orbital eccentricity and obliquity, planetary latitude, and host star spectral type. We find that the fraction of a planet’s orbit over which it exhibits habitable surface conditions is larger on eccentric planets orbiting M-dwarf stars, due to the lower broadband planetary albedos of these planets. Planets with larger obliquities have smaller EHZs, but exhibit warmer climates if they do not enter a snowball state during their orbits. We also find no transient runaway greenhouse state on planets at all eccentricities. Rather, planets spend their entire orbits either in a RGH or not. For G-dwarf planets receiving 100% of the modern solar constant and with eccentricities above 0.55, an entire Earth ocean inventory can be lost in 3.6 Gyr. M-dwarf planets, due to their larger incident XUV flux, can become desiccated in only 690 Myr with eccentricities above 0.38. This work has important implications for eccentric planets that may exhibit surface habitability despite technically departing from the traditional habitable zone as they orbit their host stars.