Dr. David Crisp (Jet Propulsion Laboratory/California Institute of Technology Dr. Victoria Meadows (California Institute of Technology) Understanding the Remote-Sensing Signatures of Life in Disk-averaged Planetary Spectra: 1

Rationale Understanding the origin and evolution of terrestrial planets, and their plausible diversity, will help inform the search and characterization of extrasolar terrestrial planets. –The emphasis is not only on understanding the likely planetary environments, but Understanding their appearance to astronomical instrumentation Understanding whether they are able to support life –As we search for habitable worlds, superEarths Are likely to be the first extrasolar terrestrial planets that are characterized represent a class of terrestrial planet that may also support life –And this could all happen in our lifetimes!!

TPF-I MIR:  m overall trace gas composition greenhouse/metabolic byproducts atmospheric and surface T TPF and Darwin Interferometers TPF- Coronagraph Launch 2016-? Launch 2020-? TPF-C Visible:  m quantification of gases surface composition SIM – Launch 2011-? – Terrestrial Planet Masses and Orbits Characterizing Extrasolar Terrestrial Planets

NASA’s Life Finder Will search for chemical signatures of life at R~1000 The President’s Vision For Space Exploration

Modeling Studies Supporting Extrasolar Planet Missions Signal Extraction Spectral SimulationInformation Retrieval How well can we best detect Terrestrial planets? What kinds of information can we collect? What can we learn from this data?

Remote Detection of Planetary Characteristics We will not be able to “resolve” the extrasolar planet Everything we learn about the planet will be obtained from disk-averaged data. The signs of life must be a global phenomenon

Detecting Distant Signs of Life Life can provide global-scale modification of: –A planet’s atmosphere –A planet’s surface –A planet’s appearance over time Astronomical Biosignatures Photometric, spectral or temporal features indicative of life. Must be global-scale to enable detection in a disk-averaged spectrum. Must always be identified in the context of the planetary environment –e.g. Earth methane vs Titan methane –0.72um, H 2 O/CH 4 /CO 2 How will this information manifest itself in the planetary spectrum? H2OH2O H2OH2O

? Planetary Environmental Characteristics Is it a terrestrial planet? (Mass, brightness, color) Is it in the Habitable Zone? (global energy balance?) –Stellar Type - luminosity, spectrum –Orbit radius, eccentricity, obliquity, rotation rate In general, moderate rotation rate, low obliquity and a near circular orbit stabilizes climate. –Bolometric albedo – fraction of stellar flux absorbed Does it have an atmosphere? –Photometric variability (clouds, possibly surface) –Greenhouse gases: CO 2,H 2 O vapor present? –UV shield (e.g. O3)? –Surface pressure –Clouds/aerosols What are its surface properties? –Presence of liquid water on the surface Surface pressure > 10 mbar, T> 273 K –Land surface cover Interior: What is the geothermal energy budget?

Energy Balance of a Planet Planetary Energy balance is given by: σT e 4 = S(1-A)/4 The effective radiating temperature T e denotes the average temperature that the planet’s effective emitting surface The emitting surface is not necessarily the physical surface of the planet unless it has no atmosphere. T surface No Greenhouse Greenhouse Warming Venus 470 C -43C 513C Earth 15C -17C 32C Mars -50C -55C 5C After Table 9.1, Bennet, Shostak, Jakosky, 2003 A planet’s greenhouse effect is at least as important in determining that planet’s surface temperature as is its distance from the star! r  r 2 S(1-A) 4r2T44r2T4

Atmospheric Greenhouse Effects The atmosphere is sufficiently transparent at solar wavelengths to allow some sunlight to penetrate to the surface –Ozone and water vapor are primary absorbers The atmosphere is (partially) opaque at thermal wavelengths, reducing escape of heat to space –Water vapor, CO 2 and Ozone are the primary absorbers T4T4 a T4T4 a T4T4 s F o (1-a) T4T4 a  T 4 - s

Carbonate-Silicate Cycle Planetary processes can regulate the atmospheric greenhouse gas concentrations –Atmospheric CO 2 dissolves in the ocean –Rainfall erodes silicate rocks and carries it to the oceans –The silicate minerals react with the dissolved CO 2 to form carbonate minerals which fall to the ocean floor –The sea floor carbonates are eventually subducted –The subducted rocks melt to form CO 2 rich magma, which is released to the atmosphere in volcanic eruptions. CO 2

The CO 2 Cycle as a Thermostat Carbonate mineral formation rate is sensitive to ocean temperature and silicate weathering is sensitive to surface temperature. This allows the CO 2 cycle to regulate our climate by setting up a negative feedback process It takes 400,000 yrs after an increase in atmospheric CO 2 for the carbonate- silicate cycle to return surface temperatures to their original value. (-) Surface temperature Rainfall Silicate weathering rate Atmospheric CO 2 Greenhouse effect

Characterizing Planets by Remote-Sensing O3O Tropopause Stratopause Water Vapor Ozone Absorption Net Emission In the visible, sunlight is reflected and scattered back to the observer or it is absorbed by materials on the planet’s surface and in its atmosphere. The planet emits this energy back to space as infrared radiation. As this radiation escapes to space, the atmosphere absorbs some of it producing Spectral features Greenhouse effects

Simulating Planetary Spectra: Radiative Transfer Models Simulating the radiation field Resolve the spectral dependence of gases, cloud, aerosols, surface albedos and radiation sources. Multiple Scattering Model Gas Absorption –Line-By-Line model for IR vibration-rotation bands Includes absorption by H 2 O, CO 2, O 3, N 2 O, CH 4, and O 2 –UV Absorption Optical Properties of Clouds and Aerosols Wavelength dependent albedos of the surface Stellar Thermal Atmospheric Composition H 2 O H2OH2O H2OH2O H2OH2O O2O2 O3O3

2. Atmospheric structure and composition Data or Climate/ Chemical Model. Modeling Spectra of Alien Terrestrial Planets 1. Input Database: Stellar spectra Gas absorption Clouds/aerosol optical properties 3. Radiative Transfer Model: R. Hasler 3. Surface Properties Types/areal coverage Optical properties

The Effect of Surface Type in the Visible Crisp, Meadows

H 2 O N 2 O CH 4 CO 2 O3O3 The Earth From Space in the Infrared

Effects of Clouds on Thermal Spectra Low Middle High Ozone O3O3

Characterizing Environments of Extrasolar Terrestrial Planets Once an extrasolar terrestrial planet has been detected (as an unresolved point source) –The first step will be to search for candidate biosignatures in its spectrum –If any are found, a more quantitative description of the planetary environment will be needed to determine whether they can be produced abiotically, or require a biological origin Wavelength (  m) O3?O3? GOT LIFE? CO 2 ?

Special Challenges Posed by Extrasolar Terrestrial Planets While reliable remote sensing retrieval methods exist for studying terrestrial planets in our solar system, extrasolar terrestrial planets pose unique challenges: –Spatial variations: Most existing remote sensing retrieval methods can be applied only to soundings acquired over a spatially homogeneous scene The first generation observations of terrestrial planets will provide only disk integrated results that mix viewing geometries, surface types, clear and cloudy scenes, etc. –Additional (ad-hoc) constraints will be needed to define the spatial variability within each sounding –Modest spectral resolution and signal / noise resolving power < 100 Signal-to-noise ratios <<100

Implications for TPF and Darwin VIS Coronagraphs Most trace gas information is at UV and near-IR wavelengths –Currently ignored in TPF designs Time dependent photometric or spectroscopic data may be essential to detect/discriminate biosignatures IR Nulling interferometers Atmospheric temperatures must be measured to quantify trace gas amounts from thermal radiances –A well mixed gas with a well known spectrum is essential for this –The CO 2 15 micron band is the best candidate for terrestrial planets in our solar system (Venus/Earth/Mars) Moderate spectral resolution and high signal-to-noise are essential for characterizing environments The problem is still underconstrained