Statistics – Applications
Scientific paper
Dec 2009
adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2009agufm.p31e..08p&link_type=abstract
American Geophysical Union, Fall Meeting 2009, abstract #P31E-08
Statistics
Applications
[1952] Informatics / Modeling, [5400] Planetary Sciences: Solid Surface Planets, [5421] Planetary Sciences: Solid Surface Planets / Interactions With Particles And Fields, [6250] Planetary Sciences: Solar System Objects / Moon
Scientific paper
The Moon has a complex three-dimensional shape with significant large-scale and small-scale topographic relief. The Moon’s topography largely controls the distribution of incident solar radiation, as well as the scattered solar and infrared radiation fields. Topography also affects the Moon’s interaction with the space environment, its magnetic field, and the propagation of seismic waves. As more extensive and detailed lunar datasets become available, there is an increasing need to interpret and compare them with the results of physical models in a fully three-dimensional context. We have developed a three-dimensional framework for lunar modeling we call the Digital Moon. The goal of this work is to enable high fidelity physical modeling and visualization of the Moon in a parallel computing environment. The surface of the Moon is described by a continuous triangular mesh of arbitrary shape and spatial scale. For regions of limited geographic extent, it is convenient to employ meshes on a rectilinear grid. However for global-scale modeling, we employ a continuous geodesic gridding scheme (Teanby, 2008). Each element in the mesh surface is allowed to have a unique set of physical properties. Photon and particle interactions between mesh elements are modeled using efficient ray tracing algorithms. Heat, mass, photon and particle transfer within each mesh element are modeled in one dimension. Each compute node is assigned a portion of the mesh and collective interactions between elements are handled through network interfaces. We have used the model to calculate lunar surface and subsurface temperatures that can be compared directly with radiometric temperatures measured by the Diviner Lunar Radiometer Experiment on the Lunar Reconnaissance Orbiter. The model includes realistic surface photometric functions based on goniometric measurements of lunar soil samples (Foote and Paige, 2009), and one-dimensional thermal models based on lunar remote sensing and Apollo heat flow measurements (Vasavada et al., 1999; Siegler et al., this meeting). Using the latest available topographic data, the results of the model are in excellent qualitative agreement with the Diviner measurements and we are in the process of refining input parameters to obtain better quantitative agreements. Other near-term applications for the model include visualizing the LCROSS impact event for Earth-based observers, modeling the fluxes of thermal and epithermal neutrons observed by Lunar Prospector, and adapting the model to other airless bodies. Foote E. J., Paige D. A., Johnson J. R., Grundy W. M., Shepard M. T. (2009) “The Bidirectional Reflectance of Apollo 11 Soil Sample 10084”, LPSC Abstract #2500. Teanby N. A. (2006) "An icosahedron-based method for even binning of globally distributed remote sensing data", Computers & Geosciences 32 (9), 1442-1450. Siegler M., Paige D. A., Keihm S., Vasavada A. R., Ghent R., Bandfield J. L., Snook K (2009) “LRO Diviner Radiometer and the Apollo 15 Heat Flow Experiment”, this meeting. Vasavada, A. R., Paige, D. A., Wood, S. E. (1999) “Near-surface temperatures on Mercury and the Moon and the stability of polar ice deposits”, Icarus 141, 179-193.
Elphic Richard C.
Foote Emily J.
Meeker Seth R.
Paige David A.
Siegler Matthew A.
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