The dune field at White Sands, New Mexico, shows a well-defined pattern of dunes and interdune areas, as well as spatial variations in this pattern. The purpose of this research is to determine which measured pattern parameters are most consistent across the dune field and to determine the cause of depositional spatial variability. This was accomplished using an airborne LiDAR generated digital-elevation model (DEM) collected in June 2007 and covering 39 km² of the dune field. Properties of the dune field are defined by measurements from three dune populations: 1) 110 randomly selected dunes, 2) 247 dunes along transects oriented in the net transport direction, and 3) 171 dunes from three zones within the field where differences in pattern are visible. Measurements of eight common dune parameters show that the lowest coefficients of variation occur with dune orientation and crestline sinuosity, which largely define the field pattern. Cross-plotting of parameters shows generally poor correlations, which is thought to reflect variation around field-scale means that are comparable to other dune fields globally. Removing the dunes from the LiDAR DEM reveals a depositional substrate with breaks in slope interpreted as three paleoshorelines associated with Pleistocene Lake Otero. The paleoshorelines are antecedent boundary conditions that exert the primary control on spatial variability within the dune pattern. / text

This dissertation combines studies of aeolian bedforms and aeolian dune-field patterns to create a comprehensive set of tools that can be used in tandem (or separately) to extract information about climate change and landscape evolution, and to identify the controls on formation for specific modern dune fields or ancient aeolian sequences. The spatial distribution of surface processes, erosion/deposition rates, and lee face sorting on aeolian dunes are each a function of the incident angle. This correlation between stratification style and incidence angle can be used to develop a “toolbox” of methods based on measurements of key suites of parameters found in ancient aeolian deposits. Information obtained from the rock record can be used as input data for different kinds of numerical models. Regional-scale paleowind conditions can be used to validate paleoclimate and global circulation models. Understanding the natural variability in the Earth’s climate throughout its history can help predict future climate change. Reconstructed wind regimes and bedform morphologies can be used in numerical models of aeolian dune-field pattern evolution to simulate patterns analogous to those reconstructed from ancient aeolian systems. Much of the diversity of aeolian dune-field patterns seen in the real world is a function of the sediment supply and transport capacity, which in turn determine the sediment availability of the system. Knowledge of the sediment supply, availability, and transport capacity of aeolian systems can be used to predict the amount of sand in the system and where it might have migrated. This information can be extremely useful for development and production of oil and gas accumulations, where a discovery has been made but the spatial extent of the aeolian reservoir is unknown. / text