Andy successfully defended his masters thesis on June 11, 2009

TITLE:
Neural Networks and Atmospheric Scattering Calculations

ABSTRACT:
For the majority of the particles in the atmosphere, calculations of scattering energy loss are increasingly accurate in proportion to the computing time afforded them. Accurate radiative transfer calculations, even with the most efficient numerical methods, are computationally expensive. This becomes a serious problem for multi-decadal climate simulations for which an accurate representation of the radiative impact of atmospheric constituents is crucial. This thesis presents one method for reducing the computational expense radiative transfer calculations of aerosol scattering properties, which are used in chemical models. The goal of this research is to develop a fast scattering code using a neural network that is trained on input and output data derived from an accurate T-Matrix scattering algorithm. The input space to the neural net consists of scattering parameters that describe the atmospheric scattering conditions such as wavelength of incoming light, effective particle radius, and index of refraction. The output space consists of the coefficients of a Legendre polynomial expansion of the phase function. The neural net finds the nonlinear mapping between the input and output spaces for a training set and can subsequently be used to generate the phase function for arbitrary wavelength, particle radius and index of refraction. In this research, a neural network applicable to both Lorenz and Mie scattering is developed and tested for both accuracy and speed. The accuracy of the neural net is found to be excellent, with errors well below 10%, and runtime testing shows that the neural net is approximately 5 times faster than a lookup table.

Chris successfully defended his thesis proposal on June 12, 2009.

TITLE:
A Remote Sensing Study of Boundary Layer Venting during Dynamic Events with the Atmospheric Emitted Radiance Interferometer (AERI)

ABSTRACT:
The study of atmospheric processes in the planetary boundary layer (PBL) is a very complex and interesting field. By definition, the PBL is the region of the atmosphere with turbulent motions resulting from the no-slip boundary condition with the surface, and its depth can range from 30 meters in conditions of large static stability to up to 3 kilometers in highly convective regimes. This project will quantify mixing of trace gases including CO, O₃, and H₂O into and out of the boundary layer. Our focus will be on days when either Horizontal Convective Rolls (HCR) or Low Level Jets (LLJ) occur in the boundary layer. New remote sensing techniques to retrieve information about the trace gases will be further developed using the Atmospheric Emitted Radiance Interferometer (AERI). Specifically, we will update the current CO retrieval algorithm which retrieves one mixing ratio value for the entire troposphere. The improvements will be to obtain values for CO in the boundary layer and in the free troposphere. CO’s 1-2 month lifetime makes it an excellent passive tracer of atmospheric motions; thus, monitoring it will quantify mixing from the boundary layer to the free troposphere. To validate the CO retrieval, we will utilize the 3+ years (2006-2009) of aircraft CO profiles obtained at the United States Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) program Southern Great Plains (SGP) site near Lamont Oklahoma. A comparison of work already done on the new retrieval compared to the old retrieval will be shown. Also, a presentation of case study days of LLJ and HCR will highlight the need to improve the retrieval.