Transmission Spectroscopy with the ACE-FTS Infrared Spectral Atlas of Earth: A Model Validation and Feasibility Study

Infrared solar occultation measurements are well established for remote sensing of Earth's atmosphere, and the corresponding primary transit spectroscopy has turned out to be valuable for characterization of extrasolar planets. Our objective is an assessment of the detectability of molecular signatures in Earth's transit spectra. To this end, we take a limb sequence of representative cloud-free transmission spectra recorded by the space-borne ACE-FTS Earth observation mission (Hughes et al., ACE infrared spectral atlases of the Earth's atmosphere, JQSRT 2014) and combine these spectra to the effective height of the atmosphere. These data are compared to spectra modeled with an atmospheric radiative transfer line-by-line infrared code to study the impact of individual molecules, spectral resolution, the choice of auxiliary data, and numerical approximations. Moreover, the study serves as a validation of our infrared radiative transfer code. The largest impact is due to water, carbon dioxide, ozone, methane, nitrous oxide, nitrogen, nitric acid, oxygen, and some chlorofluorocarbons (CFC11 and CFC12). The effect of further molecules considered in the modeling is either marginal or absent. The best matching model has a mean residuum of 0.4 km and a maximum difference of 2 km to the measured effective height. For a quantitative estimate of visibility and detectability we consider the maximum change of the residual spectrum, the relative change of the residual norm, the additional transit depth, and signal-to-noise ratios for a JWST setup. In conclusion, our study provides a list of molecules that are relevant for modeling transmission spectra of Earth-like exoplanets and discusses the feasibility of retrieval.Comment: 25 pages, 15 figures, 3 table

Spectral features of Earth-like planets and their detectability at different orbital distances around F, G, and K-type stars

We investigate the spectral appearance of Earth-like exoplanets in the HZ of different main sequence stars at different orbital distances. We furthermore discuss for which of these scenarios biomarker absorption bands may be detected during primary or secondary transit with near-future telescopes and instruments.We analyze the spectra taking into account different filter bandpasses of two photometric instruments planned to be mounted to the JWST. We analyze in which filters and for which scenarios molecular absorption bands are detectable when using the space-borne JWST or the ground-based telescope E-ELT. Absorption bands of CO2, H2O, CH4 and O3 are clearly visible in high-resolution spectra as well as in the filters of photometric instruments. However, only during primary eclipse bands of CO2, H2O and O3 are detectable for all scenarios when using photometric instruments and an E-ELT telescope setup. CH4 is only detectable at the outer HZ of the K star since here the atmospheric modeling results in very high abundances. Since the detectable CO2 and H2O bands overlap, separate bands need to be observed to prove their existence in the atmosphere. In order to detect H2O in a separate band, a S/N>7 needs to be achieved for E-ELT observations, e.g. by co-adding at least 10 transit observations. Using a spaceborne telescope like the JWST enables the detection of CO2 at 4.3mu, which is not possible for ground-based observations due to the Earth's atmospheric absorption. Hence combining observations of spaceborne and groundbased telescopes might allow to detect the presence of the biomarker molecule O3 and the related compounds H2O and CO2 in a planetary atmosphere. Other absorption bands using the JWST can only be detected for much higher S/Ns, which is not achievable by just co-adding transit observations since this would be far beyond the planned mission time of JWST.(abridged)Comment: 15 pages, 8 figure

Volcanic SO2 plume height retrieval from UV sensors using a full-physics inverse learning machine algorithm

Precise knowledge of the location and height of the volcanic sulphur dioxide (SO2) plume is essential for accurate determination of SO2 emitted by volcanic eruptions. Current SO2 plume height retrieval algorithms based on ultraviolet (UV) satellite measurements are very time-consuming and therefore not suitable for near-real-time applications. In this work we present a novel method called the full-physics inverse learning machine (FP-ILM) algorithm for extremely fast and accurate retrieval of the SO2 plume height. FP-ILM creates a mapping between the spectral radiance and the geophysical parameters of interest using supervised learning methods. The FP-ILM combines smart sampling methods, dimensionality reduction techniques, and various linear and non-linear regression analysis schemes based on principal component analysis and neural networks. The computationally expensive operations in FP-ILM are the radiative transfer model computations of a training dataset and the determination of the inversion operator - these operations are performed off-line. The application of the resulting inversion operator to real measurements is extremely fast since it is based on calculations of simple regression functions. Retrieval of the SO2 plume height is demonstrated for the volcanic eruptions of Mt. Kasatochi (in 2008) and Eyjafjallajökull (in 2010), measured by the GOME-2 (Global Ozone Monitoring Instrument - 2) UV instrument on-board MetOp-A

The Earth as an extrasolar transiting planet - II: HARPS and UVES detection of water vapor, biogenic O2_2, and O3_3

The atmospheric composition of transiting exoplanets can be characterized during transit by spectroscopy. For the transit of an Earth twin, models predict that biogenic $O_2$ and $O_3$ should be detectable, as well as water vapour, a molecule linked to habitability as we know it on Earth. The aim is to measure the Earth radius versus wavelength $\lambda$ - or the atmosphere thickness $h(\lambda)$ - at the highest spectral resolution available to fully characterize the signature of Earth seen as a transiting exoplanet. We present observations of the Moon eclipse of 21-12-2010. Seen from the Moon, the Earth eclipses the Sun and opens access to the Earth atmosphere transmission spectrum. We used HARPS and UVES spectrographs to take penumbra and umbra high-resolution spectra from 3100 to 10400 Ang. A change of the quantity of water vapour above the telescope compromised the quality of the UVES data. We corrected for this effect in the data processing. We analyzed the data by 3 different methods. The 1st method is based on the analysis of pairs of penumbra spectra. The 2nd makes use of a single penumbra spectrum, and the 3rd of all penumbra and umbra spectra. Profiles $h(\lambda)$ are obtained with the three methods for both instruments. The 1st method gives the best result, in agreement with a model. The second method seems to be more sensitive to the Doppler shift of solar spectral lines with respect to the telluric lines. The 3rd method makes use of umbra spectra which bias the result, but it can be corrected for this a posteriori from results with the first method. The 3 methods clearly show the spectral signature of the Rayleigh scattering in the Earth atmosphere and the bands of H$_2$O, O$_2$, and O$_3$. Sodium is detected. Assuming no atmospheric perturbations, we show that the E-ELT is theoretically able to detect the $O_2$ A-band in 8~h of integration for an Earth twin at 10pc.Comment: Final version accepted for publication in A&A - 21 pages, 27 figures. Abstract above slightly shortened wrt the original. The ArXiv version has low resolution figures, but a version with full resolution figures is available here: http://www.obs-hp.fr/~larnold/publi_to_download/eclipse2010_AA_v5_final.pd

Volcanic SO2 Effective Layer Height Retrieval for OMI Using a Machine Learning Approach

Information about the height and loading of sulfur dioxide (SO2) plumes from volcanic eruptions is crucial for aviation safety and for assessing the effect of sulfate aerosols on climate. While SO2 layer height has been successfully retrieved from backscattered Earthshine ultraviolet (UV) radiances measured by the Ozone Monitoring Instrument (OMI), previously demonstrated techniques are computationally intensive and not suitable for near-real-time applications. In this study, we introduce a new OMI algorithm for fast retrievals of effective volcanic SO2 layer height. We apply the Full-Physics Inverse Learning Machine (FP_ILM) algorithm to OMI radiances in the spectral range of 310–330 nm. This approach consists of a training phase that utilizes extensive radiative transfer calculations to generate a large dataset of synthetic radiance spectra for geophysical parameters representing the OMI measurement conditions. The principal components of the spectra from this dataset in addition to a few geophysical parameters are used to train a neural network to solve the inverse problem and predict the SO2 layer height. This is followed by applying the trained inverse model to real OMI measurements to retrieve the effective SO2 plume heights. The algorithm has been tested on several major eruptions during the OMI data record. The results for the 2008 Kasatochi, 2014 Kelud, 2015 Calbuco, and 2019 Raikoke eruption cases are presented here and compared with volcanic plume heights estimated with other satellite sensors. For the most part, OMI-retrieved effective SO2 heights agree well with the lidar measurements of aerosol layer height from Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) and thermal infrared retrievals of SO2 heights from the infrared atmospheric sounding interferometer (IASI). The errors in OMI-retrieved SO2 heights are estimated to be 1–1.5 km for plumes with relatively large SO2 signals (>40 DU). The algorithm is very fast and retrieves plume height in less than 10 min for an entire OMI orbit

Warming the early Earth - CO2 reconsidered

Despite a fainter Sun, the surface of the early Earth was mostly ice-free. Proposed solutions to this so-called "faint young Sun problem" have usually involved higher amounts of greenhouse gases than present in the modern-day atmosphere. However, geological evidence seemed to indicate that the atmospheric CO2 concentrations during the Archaean and Proterozoic were far too low to keep the surface from freezing. With a radiative-convective model including new, updated thermal absorption coefficients, we found that the amount of CO2 necessary to obtain 273 K at the surface is reduced up to an order of magnitude compared to previous studies. For the late Archaean and early Proterozoic period of the Earth, we calculate that CO2 partial pressures of only about 2.9 mb are required to keep its surface from freezing which is compatible with the amount inferred from sediment studies. This conclusion was not significantly changed when we varied model parameters such as relative humidity or surface albedo, obtaining CO2 partial pressures for the late Archaean between 1.5 and 5.5 mb. Thus, the contradiction between sediment data and model results disappears for the late Archaean and early Proterozoic.Comment: 53 pages, 4 tables, 11 figures, published in Planetary and Space Scienc

Nonlinear operators on graphs via stacks

International audienceWe consider a framework for nonlinear operators on functions evaluated on graphs via stacks of level sets. We investigate a family of transformations on functions evaluated on graph which includes adaptive flat and non-flat erosions and dilations in the sense of mathematical morphology. Additionally, the connection to mean motion curvature on graphs is noted. Proposed operators are illustrated in the cases of functions on graphs, textured meshes and graphs of images

Evaluating the assimilation of S5P/TROPOMI near real-time SO2 columns and layer height data into the CAMS integrated forecasting system (CY47R1), based on a case study of the 2019 Raikoke eruption

The Copernicus Atmosphere Monitoring Service(CAMS), operated by the European Centre for Medium-Range Weather Forecasts on behalf of the European Com-mission, provides daily analyses and 5 d forecasts of atmospheric composition, including forecasts of volcanic sulfur dioxide (SO2) in near real time. CAMS currently assimilates total column SO2products from the GOME-2 instruments on MetOp-B and MetOp-C and the TROPOMI instrument on Sentinel-5P, which give information about the location and strength of volcanic plumes. However, the operational TROPOMI and GOME-2 data do not provide any information about the height of the volcanic plumes, and therefore some prior assumptions need to be made in the CAMS data assimilation system about where to place the resulting SO2increments in the vertical. In the current operational CAMS configuration, the SO2increments are placed in the mid-troposphere, around 550 hPa or 5 km. While this gives good results for the majority of volcanic emissions, it will clearly be wrong for eruptions that inject SO2at very different altitudes, in particular exceptional events where part of the SO2plume reaches the stratosphere.A new algorithm, developed by the German Aerospace Centre (DLR) for GOME-2 and TROPOMI, optimized in the frame of the ESA-funded Sentinel-5P Innovation–SO2Layer Height Project, and known as the Full-Physics Inverse Learning Machine (FP_ILM) algorithm, retrieves SO2 layer height from TROPOMI in near real time (NRT) in addition to the SO2column. CAMS is testing the assimilation of these products, making use of the NRT layer height information to place the SO2increments at a retrieved altitude. Assimilation tests with the TROPOMI SO2layer height data for the Raikoke eruption in June 2019 show that the resulting CAMSSO2plume heights agree better with IASI plume height data than operational CAMS runs without the TROPOMI SO2layer height information and show that making use of the additional layer height information leads to improved SO2 forecasts. Including the layer height information leads to higher modelled total column SO2values in better agreement with the satellite observations. However, the plume area and SO2burden are generally also overestimated in the CAMS analysis when layer height data are used. The main reason for this overestimation is the coarse horizontal resolution used in the minimizations. By assimilating the SO2layer height data, the CAMS system can predict the overall location of the Raikoke SO2plume up to 5 d in advance for about 20 dafter the initial eruption, which is better than with the operational CAMS configuration (without prior knowledge of the plume height) where the forecast skill is much more reduced for longer forecast lead times