Detection Of Biosignatures Research Articles

Detectability of Planetary Characteristics in Disk-Averaged Spectra II: Synthetic Spectra and Light-Curves of Earth

Spatially and spectrally resolved models were used to explore the observational sensitivity to changes in atmospheric and surface properties and the detectability of surface biosignatures in the globally averaged spectra and light-curves of the Earth. Compared with previous efforts to characterize the Earth using disk-averaged models, a more comprehensive and realistic treatment of the surface and atmosphere was taken into account here. Our results are presented as a function of viewing geometry and phases at both visible/near-infrared (0.5-1.7 microm) and mid-infrared (5-25 microm) wavelength ranges, applicable to the proposed NASA-Terrestrial Planet Finder visible coronagraph and mid-infrared interferometer and to the ESADarwin mission architectures. Clouds can change the thermal emission by as much as 50% compared with the cloud-free case and increase the visible albedo by up to 500% for completely overcast cases at the dichotomy phase. Depending on the observed phase and their distribution and type, clouds can also significantly alter the spectral shape. Moreover, clouds impact the detectability of surface biosignatures in the visible wavelength range. Modeling the disk-averaged sensitivity to the "red-edge," a distinctive spectral signature of vegetation, showed that Earth's land vegetation could be seen in disk-averaged spectra, even with cloud cover, when the signal was averaged over the daily time scale. We found that vegetation is more readily discriminated from clouds at dichotomy (50% illumination) rather than at full phase. The detectability of phytoplankton was also explored, but was found to be more difficult to detect in the disk-average than land vegetation.

Characterizing extrasolar terrestrial planets with reflected, emitted and transmitted spectra.

NASA and ESA are planning missions to directly detect and characterize terrestrial planets outside our solar system (nominally NASA-Terrestrial Planet Finder and ESA-DARWIN missions). These missions will provide our first opportunity to spectroscopically study the global characteristics of those planets, and search for signs of habitability and life. We have used spatially and spectrally-resolved models to explore the observational sensitivity to changes in atmospheric and surface properties, and the detectability of surface biosignatures, in the globally averaged spectra and light-curves of the Earth. Atmospheric signatures of Earth-size exoplanets might be detected, in a near future, by stellar occultation as well. Detectability depends on planet's size, atmospheric composition, cloud cover and stellar type. According to our simulations, Earth's land vegetation signature (red-edge) is potentially visible in the disk-averaged spectra, even with cloud cover, and when the signal is averaged over the daily time scale. Marine vegetation is far more difficult to detect. We explored also the detectability of an exo-vegetation responsible for producing a signature that is red-shifted with respect to the Earth vegetation's one.

Detectability of Red-Edge-shifted Vegetation on Terrestrial Planets Orbiting M Stars

We have explored the detectability of exovegetation on the surface of a terrestrial planet orbiting an M star. The exovegetation is responsible for producing a pigment-derived surface signature that is redshifted with respect to the Earth vegetation's red edge. The redshift was estimated using a model of leaf optical property spectra (Jacquemoud & Baret) combined with a 3 photon photosynthetic scheme calculated by Wolstencroft & Raven for a possible exovegetation growing on an M star planet. To study the detectability of this surface biosignature on an M star terrestrial planet, we have used the three-dimensional model developed by Tinetti et al. for the case of the Earth. This model can generate disk-averaged spectra and broadband integrated fluxes, which will be useful for future terrestrial planet exploration missions, such as the NASA Terrestrial Planet Finder Coronagraph. Input to this model were the atmospheric profiles and cloud distributions predicted by Joshi and coworkers for a synchronous planet orbiting an M dwarf and the distinctive surface reflectance of the exovegetation. While on Earth this pigment-derived surface feature would be almost completely masked by water absorption, even in a cloud-free atmosphere, we found that the strength of the edge feature on our simulated M star terrestrial planet can exceed that on Earth, given the right conditions. Obviously, the detectability of such biosignatures would be highly dependent on the extent of vegetation surface area, cloud cover, and viewing angle.

Plate tectonics and the detection of land-based biosignatures on Mars and extrasolar planets

On Earth, surface detritus has a quartz-rich mineralogy as a consequence of plate tectonics. Rocky planets without plate tectonics, like Mars, have surface detritus derived from volcanic rocks. There is a marked contrast in the transmission of photosynthetically active radiation (PAR) through the upper few millimetres of the two sediment types. Quartz-rich sediment allows PAR to penetrate below the level where ultraviolet (UV) radiation is cut out, so represents a potential refuge for phototrophs at an early stage of evolution before chemical defences against UV radiation are developed. Opaque volcanogenic sediment does not allow significant transmission of radiation beneath the surface. There are consequences for the expression of biosignatures from phototrophs. In the case of direct examination as proposed for Mars, techniques such as Raman spectroscopy will be applicable only to surfaces rather than penetratively into the subsurface. When spectroscopic techniques can be applied to extrasolar planets, the chance of a vegetation signature will be enhanced if the early evolution of phototrophs has been facilitated by a subsurface refuge.

Spectroscopic requirements for Raman instrumentation on a planetary lander: potential for the remote detection of biosignatures on Mars

The special characteristics of Raman spectroscopy (relative insensitivity to water, non-destructive detection, sensitivity to bio- and geosignatures, molecular structural composition information, etc.) together with the development of miniaturized Raman spectrometers make the consideration of this technique for future robotic landers on planetary surfaces, particularly Mars, a very interesting option. The development of light and rugged Raman spectrometers limits the possible scope of the instrumentation which has particular importance in the recognition of biomolecular and mineral signatures. In this work, we evaluate the spectral resolution and scan time parameters and the effect that they have on the Raman spectra of extremophilic biomolecules, together with the wavenumber ranges which are critical for the detection of life signals. This is of vital relevance for the design of miniaturized Raman spectrometer systems. From our results, we conclude that for extraterrestrial biological signatures unambiguous Raman spectral identification provided with a minimum of 16 cm−1 spectral resolution is required for the most significant biosignature wavenumber range in the 1700–700 cm−1 region.

Principal component analysis and neural networks for detection of amino acid biosignatures

We examine the applicability of Principal Component Analysis (PCA) and Artificial Neural Network (ANN) methods of data analysis to biosignature detection. These techniques show promise in classifying and simplifying the representation of patterns of amino acids resulting from biological and non-biological syntheses. PCA correctly identifies glycine and alanine as the amino acids contributing the most information to the task of discriminating biotic and abiotic samples. Trained ANNs correctly classify between 86.1 and 99.5% of a large set of amino acid samples as biotic or abiotic. These and similar techniques are important in the design of automated data analysis systems for robotic missions to distant planetary bodies. Both techniques are robust with respect to noisy and incomplete data. Analysis of the performance of PCA and ANNs also lends insight into the localization of useful information within a particular data set, a feature that may be exploited in the selection of experiments for efficient mission design.