Sensitivity to environmental properties in globally averaged synthetic spectra of EarthG. Tinetti (NAI-NRC/Caltech), V. S. Meadows (JPl/Caltech), D. Crisp (JPL), W. Fong (Caltech), T. Velusamy (JPL), E. Fishbein (JPL)

We are using computer models to explore the observational sensitivity to changes in atmospheric and surface properties, and the detectability of biosignatures, in the globally averagedspectrum of the Earth. Using AIRS (Atmospheric Infrared Sounder) data, as input on atmospheric and surface properties, we have generated spatially resolved high-resolution syntheticspectra using the SMART radiative transfer model (developed by D. Crisp), for a variety of conditions, from the UV to the far-IR (beyond the range of current Earth-based satellitedata). We have then averaged over the visible disk for a number of different viewing geometries to quantify the sensitivity to surface types and atmospheric features as a function ofviewing geometry, and spatial and spectral resolution. These results have been processed with an instrument simulator to improve our understanding of the detectable characteristicsof Earth-like planets as viewed by the first (and probably second) generation extrasolar terrestrial planet detection and characterization missions (Terrestrial Planet Finder/Darwin andLife finder). This model can also be used to analyze Earth-shine data for detectability of planetary characteristics in disk-averaged spectra.

Spectroscopy

Photometryremote sensing methodsThis information can be decoded using

Extrasolar planets will pose special challengesin our solar systemdeveloped for studying planettechniques have beenseveral remote sensing

− Limited signal to noise

− No spatial details

− No direct constraints on size

Once an extrasolar terrestrialplanet has been detected and resolved from its parent star...

...all the information about itsenvironment will arrive asphotons

s

If you are an extrasolar terrestrial planet, and you would like to be under-stood...

* English subtitles performed by VPL (Virtual planetary Laboratory)

"...ah thanks, that’s Life!"*"You look gorgeus, your ozone band is in great shape!!"

can be the right solution!!!Remote−sensing spectroscopy

I agree, this would bethe best way, but let us

for doing this...say we are too distant

he will have to struggle against billions This is Jack photonthe One!

This is Jack, a photon in the visible:planet, won’t be alone ...Photons coming from the terrestrial

of photons like him coming from the parent star, if he wants to be detected.His friend Tom, an IR photon has easiestlife: "only" millions of competitors...

Spectrum of the planet −> Information about chemical composition, themodynamics and kinetics of its atmosphere + surface composition

In its path to the detector thephoton may experiment some

The photon is unable to reachthe detector

Tom, IR photon Martha, H2O molecule

kind of interactions...

The principal goal of the NASA TPF mission concept is to detect and characterizeextrasolar terrestrial planets. TPF is expected to survey nearby stars and directly detectplanetary systems that include terrestrial-sized planets in their habitable zones. Youmay apply for being one of the observed planet and send your photons after year 2012 toTPF’s detector. Two different architectures are being considered for TPF:

0.5 µ < λ < 1.05 µ

photonsExtrasolar terrestrial planet

WANTED

? photons

Extrasolar terrestrial planet

6.µ < λ < 17 µ

WANTED

TPF coronograph

TPF interferometer

− window regions− atmospheric thermal structure − CO2 15 micron band− vertical distribution of temperatures and trace gases above emitting surface − (es. H2O, O3, CH4, N2O)− some combinations of these species can serve as astronomical biomarkers

ν ν’

The Virtual Planetary Laboratory is being developed to assess the relative merits of

these two architectures

− surface temperature− "color" of the reflecting surface (cloud top/ground)− atmospheric pressure at the reflecting surface− column abunance of trace gases− clouds/aerosols

Spectra of reflected Stellar Radiation Spectra of emitted Thermal Radiation

ν ν

TPF is supposed to provideonly disk−averaged spectra.

−local properties: detectable?

−spectral signature of life, detectable?

to resolve the diskResolution needed

The NAI Virtual Planetary Laboratory (VPL, Dr. Vic-toria Meadows, P. I.), seeks to understand what canbe learned about a planet’s surface and atmosphericproperties from disk-averaged spectra at a number ofspectral resolutions.To do this, we have

� derived an architecture for a planet simulationmodel that takes into account “tiling” or pix-elization (we decided to use HEALPIX pixelisa-tion, ref.[3] of the sphere and the way in whichthe tiles map back to surface types.

� We then have used the radiative transfer modelSMART [ref,] and observative data as input onatmospheric and surface, to generate syntheticspectra at the Healpix resolution for a range of il-lumination conditions (phase angles) and view-ing geometries.

� Finally, we have created a program, which takesuser specifications of spatial resolution and se-lects the appropriate radiative transfer spectragenerated by SMART (Spectral Mapping Atmo-spheric Radiative Transfer Model by D. Crisp,ref. [1,2]) for each pixel of the simulation (takinginto account local albedo, surface types, clouds,viewing angle and sun-position) to produce thefinal synthetic view, which can then be disk-averaged.

� We have compared the results with observedspectra (fig. 6).

We present in this poster the results we have obtained for a Earth like planet.In this case we have used AIRS (Atmospheric Infrared Sounder) data as input on atmo-spheric and surface ref[6]. Enjoy!

[Ref. 1] V. S. Meadows, D. Crisp, Ground-based near-infrared observations of the Venus nightside: The thermalstructure and water abundance near the surface, (Journal of Geophysical Research, vol. 101, 4595-4622)[Ref. 2] Crisp D., Absorption of sunlight by water vapor in cloudy conditions: A partial explanation for the cloudabsorption anomaly. , Geophys. Res. Lett., 24, 571-574, 1997.[Ref. 3] Healpix (Hierarchical Equal Area and iso-Latitude Pixelisation) is a curvilinear partition of thesphere into exactly equal area quadrilaterals of varying shape. Healpix was originally designed for the ESAPlanck and NASA WMAP (Wilkinson Microwave Anisotropy Probe) missions by Krzysztof M. Gorski, EricHivon, Benjamin D. Wandelt, (1998). http://www.eso.org/science/healpix/index.html[Ref. 4] C.A. Beichman, N. J. Woolf, and C.A. Lindensmith, Eds. The Terrestrial Planet Finder, (JPL: Pasadena),JPL 99-3,1999.[Ref. 5] C.A. Beichman, and T. Velusamy, ”Sensitivity of TPF Interferometer for Planet Detection”, Optical

and IR Interferometry from Ground and Space. S.C.Unwin, and R.V. Stachnick, eds. ASP Conference Series,Vol.194 (San Francisco: ASP), 405, 1999.[Ref. 6] E. Fishbein, C.B. Farmer, S.L. Granger, D.T. Gregorich, M.R. Gunson, S.E. Hannon, M.D. Hofstadter,S.-Y. Lee, S.S Leroy; Formulation and Validation of Simulated Data for the Atmospheric Infrared Sounder (AIRS),IEEE TRANSACTIONS ON GEOSCIENCE & REMOTE SENSING, Vol. 41, N. 2, Feb 2003 1.

Surface types and clouds

Fig. 1 Spectra of different surface types. Almost no difference in the IR. In the visible on thecontrary we can see very clearly the red-edge (leafy plants reflect sunlight strongly in this band).

Strato−cumulus

Cirrus

Alto−stratus

Strato−cumulus

Alto−stratus

Cirrus

Fig. 2 Spectra of different cloud types. The contribution of clouds is dramatic. We have toinclude them in order to have a realistic model (see fig. 6). Even with clouds, the most important

features are still detectable in the IR. In the visible it is more difficult.

Disk-averaged synthetic spectraof Earth. IR and visible.

Disk-averaged solar and IR spectra of the Earth’s were generated from several vantagepoints (ie over the pole, over the equator, etc.) to assess the effects of clouds and surfacealbedos on the spectral information content.We have included in our simulation 6 different surface types: Ocean, Ice, Tundra, Forest,Grass, Ground. There are no clouds. We have used AIRS data as input for SMART (Spectral Mapping Atmospheric Radiative Transfer Model, by D. Crisp). We have used aresolution of 48 pixels for the atmosphere and 3,072 pixels for the surface.

G. Tinetti, V. Meadows, D. Crisp, W. Fong, E. Fishbein

_____ North Pole

_____ South Pole

_____ Equator, longitude 180

_____ Equator, longitude 0

G. Tinetti, V. Meadows, D. Crisp, W. Fong, E. Fishbein

_____ North Pole

_____ South Pole

_____ Equator, longitude 180

_____ Equator, longitude 0

Fig. 3 Sun position: latitude= 20.77�, longitude 1.65

�(corresponding to July 20th 2002, 0 p. m.

UT). Viewing position: black curve, North Pole; light blue curve, South Pole; green curve,Equator-longitude 0

�, red curve, equator-longitude 180

�.

G. Tinetti, V. Meadows, D. Crisp, W. Fong, E. Fishbein

_____ Sun position: lat 20.81, lon 91.64

_____ Sun position: lat 20.77, lon 1.65

_____ Sun position: lat 20.72, lon 271.64

_____ Sun position: lat 20.86, lon 181.64

G. Tinetti, V. Meadows, D. Crisp, W. Fong, E. Fishbein

_____ Sun position: lat 20.81, lon 91.64

_____ Sun position: lat 20.77, lon 1.65

_____ Sun position: lat 20.72, lon 271.64

_____ Sun position: lat 20.86, lon 181.64

Fig. 4 In these figures the observer is in the position longitude= 0�, latitude=0

�. The four cases

plotted correspond to different positions of the sun: longitude= 1.65�, latitude= 20.77

�(corresponding to July 20th 2002, 0 p.m. UT), lon= 271.65

�, lat= 20.72 (6 p.m. UT),

lon=181.64�, lat=20.86

�(0 a.m.), lon=91.64

�, lat=20.81

�(6 a.m.).

G. Tinetti, V. Meadows, D. Crisp, W. Fong, E. Fishbein

_____ Sun position: lat 20.86, lon 181.64

_____ Sun position: lat 20.81, lon 91.64

_____ Sun position: lat 20.77, lon 1.65

_____ Sun position: lat 20.72, lon 271.64

G. Tinetti, V. Meadows, D. Crisp, W. Fong, E. Fishbein

_____ Sun position: lat 20.86, lon 181.64

_____ Sun position: lat 20.81, lon 91.64

_____ Sun position: lat 20.77, lon 1.65

_____ Sun position: lat 20.72, lon 271.64

Fig. 5 We have plotted four dichotomies corresponding to different sun position longitude=1.65

�, latitude= 20.77

�(corresponding to July 20th 2002, 0 p.m. UT), lon= 271.65

�, lat= 20.72

(6 p.m. UT), lon=181.64�, lat=20.86

�(0 a.m.), lon=91.64

�, lat=20.81

�(6 a.m.).

Validation with observed spectra

_________ Disk−averaged synthetic spectrum, no cloud

_________ Disk−averaged measured spectrum

_________ Disk−averaged synthetic spectrum: 60% of clouds

_ _ _ _ _ _ Disk−averaged synthetic spectrum, 100% Strato−cumulus

_ . _ . _ . _ . Disk−averaged synthetic spectrum, 100% Alto−Stratus

. . . . . . . . . Disk−averaged synthetic spectrum, 100% Cirrus

Fig. 6 Disk-averaged spectrum of Earth observed by Mars Thermal Emission Spectrometer (TES)(red) compared with the synthetic one produced in almost the same conditions with 60% of clouds(blue) and without clouds (black). Plots in green show the contribution of different cloud-types.On the right we show the view of the Earth at 17:30 UT on November 24, 1996, from the MGS.

[Ref. 7] Initial data from the Mars Global Surveyor thermal emission spectrometer experiment: Observations of theEarth, P. R. Christensen, J. C. Pearl, Journal of Geophysical research Vol. 102, May 25, 1997

Light curves

Time dependent variations in the disk-averaged spectra, or ”light curve” can provideadditional information about spatial variations.

Fig. 7 Light-curves following the diurnal rotation of the planet for the intervals 8-13 � m for theIR and 0.7-0.8 � m for the visible (red-edge effect).

The quantity plotted is�������� d �� � �� � d � , where �� ��� is the disk-averaged radiation, ��� and ��� are the

extremes of the chosen interval. The phases considered are totally illuminated, totally dark anddichotomies.

Simulation of a TPF detectionof a Earth-like planet

Our synthetic disk-averaged spectra were run through a TPF observation systemsimulator for different spectral resolutions. The TPF book design has been as-sumed for these calculations and the planet was placed around a G star that is10pc distant. TPF will provide only disk-averaged spectra with possible spectralresolutions of � 75 (visible) and � 25 (MIR), depending on final architecture [Ref.4,5].

Fig. 8 Simulation of TPF-Interferometer detection of a Earth-like planet orbiting arounda G star. The top spectrum in each set is at high-resolution, and the middle and lower

panels show R � 100 (at 10 days integration) and R � 20 (at 2 days integration)respectively. 1- � error bars are shown in red. We recall that the wavelength range

currently proposed and desirable should be 6.-17 microns for the interferometer, withspectral resolution of 25-50.

Fig. 9 Simulation of TPF-Coronograph detection of a Earth-like planet orbiting arounda G star. These plots have been produced by processing the synthetic spectra with an

observational system simulator of the TPF coronograph, at spectral resolutions R= 70with corresponding integration time of 6h. The error bars in the spectra represent rmsnoise (1 sigma) in the TPF measurement in each spectral channel for the integration.

Conclusions� Our approach is feasible. The comparison with the experiment confirms:

the model works (see fig. 7)!� We can distinguish among different surface types looking at the Earth’s

spectra in the visible (0.7-0.8 � m band, red-edge), there are almost no dif-ferences in the IR (fig. 1).

� The contribution of clouds is dramatic. We have to include them in order tohave a realistic model. Even with clouds, the most important features arestill detectable in the IR. In the visible it is more difficult.

� The temperature inversion in the Earth’s atmosphere, which produces theemission peak at the center of the CO � 15 � m band, can be used as a sec-ondary (confirmation) indicator of the presence of a high-altitude absorbersuch as ozone.

� Although it is possible to discriminate between Mars and Earth at R � 20, athigher resolution we are much better able to characterize the temperaturesof the surface and atmosphere via features such as the CO � 15 � m band.

� The lack of high spectral resolution smears out the spectral features. How-ever some of the strongest features are detectable with TPF.

This work has been supported by NASA Astrobiology Institute and NationalAcademies.