Thermal modeling

The most frequent method to determine the size (and volume) of an asteroid is fitting the thermal data observations (typically from IRAS, WISE, and AKARI satellites) by simple thermal models that assume a spherical shape model:
  • Standard Thermal Model (STM) of Lebovsky et al (1986) – no rotation and asteroid in opposition. Includes a normalization factor – beaming parameter η that is calibrated by the size of asteroids (1) Ceres and (2) Pallas derived from stellar occultation measurements. This value (η=0.756) is not valid for smaller asteroids! Used to analyze AKARI data, however, η values were re-calibrated to be more realistic for certain populations (MBAs, NEAs).
  • Fast Rotating Model
  • Near-Earth Asteroid Thermal Model of Harris (1998) – beaming parameter is fitted, still spherical non-rotating (the lightcurve is averaged) object. The thermal flux is computed only for the illuminated and visible part of the surface. Used with WISE data.

The reported size uncertainties for individual asteroids are usually very small (few percent), however, they are not realistic. Indeed, the uncertainties are dominated by the model systematic errors - the spherical shape assumption is too crude and also the role of the geometry is neglected (e.g., the spin axis orientation). In the statistical sense, the sizes determined by thermal models are reliable, but could be easily off for individual objects by 10-30%. This implies a volume uncertainty of 30-90%!

Beaming parameter interpretation

Related to thermal inertia, surface roughness, size, pole, ...

Albedos and sizes from thermal modeling

The physical characterization of asteroids has seen an enormous boost in recent years thanks to the data of the NASA Wide-field Infrared Survey Explorer (WISE) mission (Wright et al. 2010; Mainzer et al. 2011a). In particular, sizes and albedos have been determined by the NEATM for about 130,000 asteroids and for different populations thereof, including main belt asteroids – Masiero et al. (2011, 2012), Hildas – Grav et al. (2012a), near-Earth objects – Mainzer et al. (2011b, 2014), and Trojans – Grav et al. (2011, 2012b). This resulted in a database of impressive quality in terms of number of observed bodies and sensitivity as compared to previous surveys:

  • Infrared Astronomical Satellite (IRAS) – sky survey in four filters (12, 25, 60 and 100 μm), 57cm mirror, launched 1983 and operational for 10 months, ~2200 albedos and sizes by STM (Tedesco et al., 2002).
  • Infrared astronomy satellite AKARI – launched in early 2006 by JAXA, 68.5cm mirror, ~5000 albedos and sizes from STM (Usui et al., 2011).
  • Wide-field Infrared Survey Explorer (WISE) – launched December 2009, operational since January 14, 2010. Sky survey in four filters: 3.4, 4.6, 12 and 22 μm, 40cm telescope. The cooling medium depleted after ten months (cryogenic mission), then only filters 3.4 and 4.6 μm with lower sensitivity (post-cryogenic mission). ~130,000 albedos and sizes derived by NEATM.

Figure. ​Venn diagram of the number of asteroids detected with IRAS, AKARI, and WISE. Adopted from Usui et al. (2014).

Thermophysical modeling

Simple thermal models assume spherical, non-rotating asteroids. When shape models, spin vectors, and other physical parameters are known, it is possible to apply more sophisticated methods to infer thermophysical properties such as thermal inertia and/or surface roughness. So far, such thermophysical parameters were derived for less than about 50 asteroids due to the lack of both physical properties (i.e., shape models, spin axis orientations) as well as available thermal infrared observations. However, the number of shape models has grown dramatically in the past decade and the newly obtained thermal infrared data from WISE now open the opportunity to greatly increase the number of thermal inertia determinations.

Thermal inertia, defined by Γ= √ρκC, where ρ is the density of the surface regolith, κ its thermal conductivity, and C its heat capacity, measures the resistance of a material to temperature change, and thus controls the temperature distribution of the surface of an atmosphere-less body. As it affects the symmetry of the temperature distribution on asteroids, the thermal inertia controls the strength of the Yarkovsky effect, which is the rate of change in the semi-major axis of the orbit of an asteroid (da/dt) due to the recoil force of the thermal photons (Bottke et al., 2006, for instance). Thermal inertia is also a sensitive indicator of the nature of the surface regolith as its value is affected by the cohesion of the material in the soil (i.e., between one and several tens of millimeters of the surface layer see, e.g., Mellon et al., 2000; Jakosky, 1986). Knowledge of the grain size of asteroid regolith is of paramount importance for future landing and/or sample-return missions (such as OSIRIS-REx and Hayabusa-2, two different sample return missions to carbonaceous asteroids, Lauretta et al., 2012; Okada et al., 2014). Thermal inertia is strongly affected by the porosity of the material (Zimbelman, 1986). For a given surface composition, the higher the porosity, the lower the values of both j and C. See Vernazza et al. (2012) for a discussion of the effect of porosity on asteroids surfaces.

In order to derive the thermal inertia and other physical parameters of asteroids, such as the diameter and the albedo, a thermophysical model (hereafter TPM, Lagerros, 1996, 1997, 1998) is typically used to analyze thermal infrared data. A TPM calculates thermal infrared fluxes given a set of physical parameters (size D, thermal inertia Γ, Bond albedo A, surface roughness θ) whose values are adjusted to provide the best fit between the model and the observed fluxes, by minimizing a figure of merit (chi-square). Classically, a TPM is used with an a priori knowledge of the shape and the rotational state of the asteroid, which are taken as fixed quantities. Typically, shapes are based on radar imaging (e.g., asteroids 2010 EV5, or (101955) Bennu, Alí-Lagoa et al., 2014; Emery et al., 2014) or on convex inversion of photometric ligthcurves (e.g., asteroids (25143) Itokawa, or (1620) Geographos, Müller et al., 2014; Rozitis and Green, 2014).
References

Alí-Lagoa, V. et al., 2014. Thermophysical properties of near-Earth Asteroid (341843) 2008 EV 5 from WISE data. Astron. Astrophys., 561, A45.

Bottke, J.W.F. et al., 2006. The Yarkovsky and Yorp effects: Implications for asteroid dynamics. Ann. Rev. Earth Planet. Sci., 34, 157-191.

Emery, J.P. et al., 2014. Thermal infrared observations and thermophysical characterization of OSIRIS-REx target Asteroid (101955) Bennu. Icarus, 234, 17-35.

Grav, T. et al., 2011. WISE/NEOWISE observations of the jovian Trojans: Preliminary results. Astrophys. J., 742, 40.

Grav, T. et al., 2012a. WISE/NEOWISE observations of the Hilda Population: Preliminary results. Astrophys. J., 744, 197.

Grav, T. et al., 2012b. WISE/NEOWISE observations of the jovian Trojan Population: Taxonomy. Astrophys. J., 759, 49.

Harris, A.W., 1998. A thermal model for near-Earth asteroids. Icarus, 131, 291-301.

Jakosky, B.M., 1986. On the thermal properties of martian fines. Icarus, 66, 117-124.

Lagerros, J.S.V., 1996. Thermal physics of asteroids. I. Effects of shape, heat conduction and beaming. Astron. Astrophys., 310, 1011-1020.

Lagerros, J.S.V., 1997. Thermal physics of asteroids. III. Irregular shapes and albedo variegations. Astron. Astrophys., 325, 1226-1236.

Lagerros, J.S.V., 1998. Thermal physics of asteroids. IV. Thermal infrared beaming. Astron. Astrophys., 332, 1123-1132.

Lauretta, D.S. et al., 2012. The OSIRIS-REx Mission - Sample acquisition strategy and evidence for the nature of regolith on Asteroid (101955) 1999 RQ36. LPI Contrib., 1667, 6291.

Lebofsky L. A., Sykes M. V., Tedesco E. F., et al. (1986). A refined ’standard’ thermal model for asteroids based on observations of 1 Ceres and 2 Pallas. Icarus, 68, 239-251.

Mainzer, A. et al., 2011a. Thermal model calibration for minor planets observed with wide-field infrared survey explorer/NEOWISE. Astrophys. J., 736, 100.

Mainzer, A. et al., 2011b. NEOWISE observations of near-Earth objects: Preliminary results. Astrophys. J., 743, 156.

Mainzer, A. et al., 2014. The population of tiny near-Earth objects observed by NEOWISE. Astrophys. J., 784, 110.

Masiero, J.R. et al., 2011. Main belt asteroids with WISE/NEOWISE. I. Preliminary albedos and diameters. Astrophys. J., 741, 68.

Masiero, J.R. et al., 2012. Preliminary analysis of WISE/NEOWISE 3-band cryogenic and post-cryogenic observations of main belt asteroids. Astrophys. J., 759, L8.

Mellon, M.T. et al., 2000. High-resolution thermal inertia mapping from the Mars Global Surveyor Thermal Emission Spectrometer. Icarus, 148, 437-455.

Müller, T.G., Hasegawa, S., Usui, F., 2014. (25143) Itokawa: The power of radiometric techniques for the interpretation of remote thermal observations in the light of the Hayabusa rendezvous results. Publ. Astron. Soc. Japan, 66, 52.

Okada, T. et al., 2014. Thermal-infrared imaging of C-Class Asteroid 162173(1999JU3) by Hayabusa2. In: Lunar and Planetary Institution Technical Report, vol. 45. Lunar and Planetary Science Conference, 1201.

Rozitis, B., Green, S.F., 2014. Physical characterisation of near-Earth Asteroid (1620) Geographos. Reconciling radar and thermal-infrared observations. Astron. Astrophys., 568, A43.

Tedesco, E.F. et al., 2002. The supplemental IRAS Minor Planet Survey. Astron. J., 123, 1056-1085.

Vernazza, P. et al., 2012. High surface porosity as the origin of emissivity features in asteroid spectra. Icarus, 221, 1162-1172.

Wright, E.L. et al., 2010. The Wide-field Infrared Survey Explorer (WISE): Mission description and initial on-orbit performance. Astron. J., 140, 1868-1881.

Usui, F. et al., 2011. Asteroid catalog using Akari: AKARI/IRC Mid-Infrared Asteroid Survey. Publ. Astron. Soc. Japan, 63, 1117-1138.

Usui, F. et al., 2014. A comparative study of infrared asteroid surveys: IRAS, AKARI, and WISE. Publ. Astron. Soc. Japan, 66, 56.

Zimbelman, J.R., 1986. The role of porosity in thermal inertia variations on basaltic lavas. Icarus, 68, 366-369.



-- JosefHanus - 21 May 2015

This topic: Main > ThermalModeling
Topic revision: 28 Aug 2015, JosefHanus
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