Investigating linkages between atmospheric and terrain properties and spatial anisotropic multiscaling in orographic convective precipitation
Abstract
The solutions of idealized fully nonlinear cloud resolving numerical simulations of orographic convective precipitation display statistical multiscaling, similar to what is commonly found in observations in the atmosphere. This result is verified even in the absence of scaling in the initial conditions or terrain forcing, suggesting that this scaling behavior should be a general property of the nonlinear solutions of the Navier-Stokes like equations governing the atmospheric dynamics. By taking advantage of this scale invariance property, statistical downscaling methods can be constructed which can be used as sub-grid scale parameterizations and provide a way to bridge between coarser resolution numerical simulations and the high resolution needs of hydrological applications. However, the horizontal scaling exponent function (and respective multifractal parameters) varies with atmospheric and terrain properties, particularly small scale terrain spectra, atmospheric stability and mean wind speed. This result qualitatively agrees with the predictions of linear stability analysis that suggests the governing role of these parameters in embedded convective structures. Hence multiscaling statistical parameters should be computed for each particular geographical location and atmospheric conditions, bringing the necessity of development of relationships to predict them from coarse grid atmospheric data and terrain spectra. The spatial anisotropy (both vertical and horizontal) of the scaling exponent function for rain, cloud and velocity fields is also investigated. Based on the computed statistical multifractal exponents, multifractal simulations are performed to test the ability of these cascade models in reproducing the statistical properties of the atmospheric fields and the sensitivity of the statistical properties of the fields to variations in the multifractal parameters. Finally, simulations with scaling terrain forcing are created and the relationship between scaling of rain, cloud and wind fields and topography is explored.
- Publication:
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AGU Fall Meeting Abstracts
- Pub Date:
- December 2011
- Bibcode:
- 2011AGUFMNG51B1655N
- Keywords:
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- 1854 HYDROLOGY / Precipitation;
- 3314 ATMOSPHERIC PROCESSES / Convective processes;
- 4440 NONLINEAR GEOPHYSICS / Fractals and multifractals;
- 4475 NONLINEAR GEOPHYSICS / Scaling: spatial and temporal