Thousands of exoplanets have now been discovered with a huge range of masses, sizes and orbits: from rocky Earth-like planets to large gas giants grazing the surface of their host star. However, the essential nature of these exoplanets remains largely mysterious: there is no known, discernible pattern linking the presence, size, or orbital parameters of a planet to the nature of its parent star. We have little idea whether the chemistry of a planet is linked to its formation environment, or whether the type of host star drives the physics and chemistry of the planet's birth, and evolution. ARIEL was conceived to observe a large number (~1000) of transiting planets for statistical understanding, including gas giants, Neptunes, super-Earths and Earth-size planets around a range of host star types using transit spectroscopy in the 1.25-7.8 μm spectral range and multiple narrow-band photometry in the optical. ARIEL will focus on warm and hot planets to take advantage of their well-mixed atmospheres which should show minimal condensation and sequestration of high-Z materials compared to their colder Solar System siblings. Said warm and hot atmospheres are expected to be more representative of the planetary bulk composition. Observations of these warm/hot exoplanets, and in particular of their elemental composition (especially C, O, N, S, Si), will allow the understanding of the early stages of planetary and atmospheric formation during the nebular phase and the following few million years. ARIEL will thus provide a representative picture of the chemical nature of the exoplanets and relate this directly to the type and chemical environment of the host star. ARIEL is designed as a dedicated survey mission for combined-light spectroscopy, capable of observing a large and welldefined planet sample within its 4-year mission lifetime. Transit, eclipse and phasecurve spectroscopy methods, whereby the signal from the star and planet are differentiated using knowledge of the planetary ephemerides, allow us to measure atmospheric signals from the planet at levels of 10-100 part per million (ppm) relative to the star and, given the bright nature of targets, also allows more sophisticated techniques, such as eclipse mapping, to give a deeper insight into the nature of the atmosphere. These types of observations require a stable payload and satellite platform with broad, instantaneous wavelength coverage to detect many molecular species, probe the thermal structure, identify clouds and monitor the stellar activity. The wavelength range proposed covers all the expected major atmospheric gases from e.g. H 2 O, CO 2 , CH 4 NH 3 , HCN, H 2 S through to the more exotic metallic compounds, such as TiO, VO, and condensed species. Simulations of ARIEL performance in conducting exoplanet surveys have been performedusing conservative estimates of mission performance and a

Astronomically calibrated cyclostratigraphy relies on correct matching of observed sedimentary cycles to predicted astronomical drivers such as eccentricity, obliquity, and climate precession. However, the periods of these astronomical cycles, in the past, are not perfectly known because: (i) they drift through time; (ii) they overlap; and (iii) they are affected by the poorly constrained recession history of the Moon. This paper estimates the resulting uncertainties in ancient Milankovitch cycle periods and shows that they lead to: (i) problems with using Milankovitch cycles for accurate measurement of durations (potential errors are around 25% by the start of the Phanerozoic); (ii) problems with correctly identifying the Milankovitch cycles responsible for observed period ratios (e.g., the ratio for long-eccentricity/short-eccentricity overlaps, within error, with the ratio for short-eccentricity/precession); and (iii) problems with verifying that observed cycles are Milankovitch driven at all (the probability of a random period ratio matching a predicted Milankovitch ratio, within error, is 20-70% in the Phanerozoic). Milankovitch-derived ages and durations should therefore be treated with caution unless supported by additional information such as radiometric constraints.

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Analyses of bulk petrographic data indicate that during the Late Paleozoic wildfires were more prevalent than at present. We propose that the development of fire systems through this interval was controlled predominantly by the elevated atmospheric oxygen concentration (p(O2)) that mass balance models predict prevailed. At higher levels of p(O2), increased fire activity would have rendered vegetation with high-moisture contents more susceptible to ignition and would have facilitated continued combustion. We argue that coal petrographic data indicate that p(O2) rather than global temperatures or climate, resulted in the increased levels of wildfire activity observed during the Late Paleozoic and can, therefore, be used to predict it. These findings are based upon analyses of charcoal volumes in multiple coals distributed across the globe and deposited during this time period, and that were then compared with similarly diverse modern peats and Cenozoic lignites and coals. Herein, we examine the environmental and ecological factors that would have impacted fire activity and we conclude that of these factors p(O2) played the largest role in promoting fires in Late Paleozoic peat-forming environments and, by inference, ecosystems generally, when compared with their prevalence in the modern world.

This paper describes a new 3‐D forward numerical model (CARBONATE 3D) that simulates the stratigraphic and sedimentological development of carbonate platforms and mixed carbonate–siliciclastic shelves by simulating the following sedimentary processes: (1) Carbonate shallow, open‐marine production, dependent on water depth, restriction and sediment input; (2) Carbonate shallow, restricted‐marine production, dependent on water restriction; (3) Pelagic sediment production and deposition; (4) Coarse and fine siliciclastic input; (5) Erosion, transport and redeposition of sediment, dependent on currents, slope, depth and restriction as well as sediment grain‐size and composition; (6) Dissolution of subaerially exposed carbonate. In this paper the model is used to investigate the controlling mechanisms on the sequence stratigraphy of isolated carbonate platforms and atolls and to predict distinctive architectural signatures from different drowning mechanisms. Investigation of the mechanisms controlling atoll strata shows that although relative sea‐level is the major control, antecedent topography, environmental setting and early diagenesis have profound influence on what stratigraphic geometries and facies develop. Hence care must be taken if sea‐level curves are interpreted from real stratigraphies. Atoll drowning by fast sea‐level rise, by lowered production and by repeated exposure and fast subsequent sea‐level rises are investigated and different stratigraphic signatures for the respective mechanisms predicted. A fast relative sea‐level rise results in a bucket‐shaped morphology developed prior to drowning and a sharp transition from the platform margin facies to a pelagic cover. Drowning caused by lowered platform margin production is predicted to result in the development of a dome‐shaped, shallow‐water shoal over the whole platform top prior to drowning. Fourth order amplitudes of several tens of metres, typical of ‘icehouse’ settings, cause atoll drowning at subsidence rates where atolls subject to fourth order amplitude of only a few metres, typical of ‘greenhouse’ settings, can keep up with the rising sea‐level. In the resultant strata, vertical facies belts are less well developed but horizontally extensive facies bands are more prominent. High fourth order amplitudes (up to 80 m) without sufficient third order scale subsidence will not lead to drowning, however, as the platform can recover in each fourth order lowstand. These results suggest that atolls might be easier to drown in ‘icehouse’ rather than in ‘greenhouse’ conditions but only in situations with suitably high rates of longer‐term relative sea‐level rise or sufficient lag times.