Open-Source Software Development

The complex refractive index m=n+ik, as the only intrinsic optical property of an aerosol particle, is a required parameter for climate modeling and satellite retrieval algorithms, and cannot be measured directly. Typically, Mie theory inversions are often constrained to the particle size and real m, but the specific inverse problem of recovering complex m from experimental measurements is always a challenge. The Python Mie Scattering package, or PyMieScatt, has been developed to be a complete tool for both forward and inverse Mie theory calculations. In addition to over twenty functions for Mie theory calculations, it contains an implementation of a highly visual method for solving the inverse Mie problem for the complex refractive index, given known or assumed size parameter and optical measurements. It is open-source, fully documented, and available to the community, allowing research groups to bypass the step of developing their own Mie theory software. Since its release, PyMieScatt has been used by researchers from leading universities such as MIT, Univ. of Helsinki, Univ. of Tokyo, Weizmann Institute of Science, Tsinghua University, and several Indian Universities.

Constraining and accurately parameterizing the microphysical processes and resulting morphology of non-spherical aerosol has been an ongoing challenge for both experimentalists and modelers. Early in his career, Dr. Chakrabarty developed FracMAP – a state-of-art interactive 3-dimensional package for modeling and characterizing fractal, inhomogeneous aerosols (Patent issued). FracMAP is currently being actively used by aerosol researchers all over the world, and is freely downloadable from the library of Queen’s University at Belfast, Ireland. Using this package, Dr. Chakrabarty developed numerous recipes and correction factors for accurately characterizing the morphological properties of aggregates; these novel formulations have found great use by researchers in both academia and industry. For instance, he recently provided the correction factors for extracting the mass fractal dimension of aggregates from mass-mobility exponents routinely measured using a CPMA or APM.