Search

We present reflectance spectra from 0.4 to 2.4 ?m of Asteroid (101955) 1999 RQ36, the target of the OSIRIS-REx spacecraft mission. The visible spectral data were obtained at the McDonald Observatory 2.1-m telescope with the ES2 spectrograph. The infrared spectral data were obtained at the NASA Infrared Telescope Facility using the SpeX instrument. The average visible spectrum is combined with the average near-infrared wavelength spectrum to form a composite spectrum. We use three methods to constrain the compositional information in the composite spectrum of Asteroid (101955) 1999 RQ36 (hereafter RQ36). First, we perform a least-squares search for meteorite spectral analogs using 15,000 spectra from the RELAB database. Three most likely meteorite analogs are proposed based on the least-squares search. Next, six spectral parameters are measured for RQ36 and their values are compared with the ranges in parameter values of the carbonaceous chondrite meteorite classes. A most likely meteorite analog group is proposed based on the depth of overlap in parameter values. The results of the least-squares search and the parametric comparisons point to CIs and/or CMs as the most likely meteorite analogs for RQ36, and COs and CHs as the least likely. RQ36 has a spectrally blue continuum slope that is also observed in carbonaceous chondrites containing magnetite. We speculate that RQ36 is composed of a CM1 -like material. Finally, we compare RQ36 to other B-type asteroids measured by Clark et al. (Clark, B.E. et al. [2010]. J. Geophys. Res. 115, E06005). The results of this comparison are inconclusive. RQ36 is comparable to Themis spectral properties in terms of its albedo, visible spectrum, and near-infrared spectrum from 1.1 to 1.45 micrometers. However, RQ36 is more similar to Pallas in terms of its near-infrared spectrum from 1.6 to 2.3 micrometers. Thus it is possible that B-type asteroids form a spectral continuum and that RQ36 is a transitional object, spectrally intermediate between the two end-members. This is particularly interesting because Asteroid 24 Themis was recently discovered to have H2O ice on the surface (Rivkin, A., Emery, J. [2010]. Nature 464, 1322 1323; Campins, H. et al. [2010a]. Nature 464, 1320 1321).

We have reanalyzed three sets of Viking Lander 1 and 2 (VL1 and VL2) images of the Martian atmosphere to better evaluate the radiative properties of the atmospheric dust particles. The properties of interest are the first two moments of the size distribution, the single-scattering albedo, the dust single-scattering phase function, and the imaginary index of refraction. These properties provide a good definition of the influence that the atmospheric dust has on heating of the atmosphere. Our analysis represents a significant improvement over past analyses (Pollack et al. 1977,1979) by deriving more accurate brightnesses closer to the sun, by carrying out more precise analyses of the data to acquire the quantities of interest, and by using a better representation of scattering by nonspherical particles. The improvements allow us to better define the diffraction peak and hence the size distribution of the particles. For a lognormal particle size distribution, the first two moments of the size distribution, weighted by the geometric cross section, are found. The geometric cross-section weighted mean radius (r(sub eff)) is found to be 1.85 +/- 0.3 microns at VL2 during northern summer when dust loading was low and 1.52 +/- 0.3 microns at VL1 during the first dust storm. In both cases the best cross-section weighted mean variance (nu(eff)) of the size distribution is equal to 0.5 +/- 0.2 microns. The changes in size distribution, and thus radiative properties, do not represent a substantial change in solar energy deposition in the atmosphere over the Pollack et al. (1977,1979) estimates.

The role of fractional area coverage by cloud types in the energy balance of the earth is investigated through joint use of International Satellite Cloud Climatology Project (ISCCP) C1 cloud data and Earth Radiation Budget Experiment (ERBE) broadband energy flux data for the one-year period March 1985 through February 1986. Multiple linear regression is used to relate the radiation budget data to the cloud data. Comparing cloud forcing estimates obtained from the ISCCP-ERBE regression with those derived from the ERBE scene identification shows generally good agreement except over snow, in tropical convective regions, and in regions that are either nearly cloudless or always overcast. It is suggested that a substantial fraction of the disagreement in longwave cloud forcing in tropical convective regions is associated with the fact that the ERBE scene identification does not take into account variations in upper-tropospheric water vapor. On a global average basis, low clouds make the largest contribution to the net energy balance of the Earth, because they cover such a large area and because their albedo effect dominates their effect on emitted thermal radiation. High, optically thick clouds can also very effectively reduce the energy balance, however, because their very high albedos overcome their low emission temperatures.

International Satellite Cloud Climatology Project (ISCCP) C1 cloud information is compared with planetary albedo, outgoing longwave radiation (OLR), and net radiation measured at the top of the atmosphere by the Earth Radiation Budget Experiment (ERBE). Principal component analysis indicates that the day-to-day variations of the abundances of the 35 cloud types of the C1 data are correlated with each other, so that for many purposes the data set can be well represented by about five cloud types. Using stepwise multiple regression, the ISCCP C1 data can be used to predict the day-to-day variations of the energy balance measured by ERBE for 2.5-deg regions. Total fractional area coverage of cloudiness is a relatively poor predictor of radiation budget quantities. If the total fractional area coverage by clouds is divided into contributions from several distinct cloud types, the fractional coverages by these several cloud types will together form a much better prediction of radiation budget quantities than the single variable of total fractional-area cloud coverage. The regression equations can be used to estimate the net effect of clouds on the radiation balance and the contributions from particular types of clouds to albedo, OLR, and net radiation.