Suniti Sanghavi

Suniti Sanghavi is a remote sensing scientist at the Jet Propulsion Laboratory with a focus on radiative transfer modeling and inversion algorithm development.

Dr. Sanghavi recognized the need for fast and accurate radiative transfer modeling while carrying out the first Optimal Estimation based inversion of aerosol properties using SCIAMACHY data (Suniti Sanghavi et al., 2010; S. Sanghavi et al., 2012). She later expanded her approach to MISR (Diner et al., 2012), leading to state-of-the-art refinements in aerosol electromagnetic scattering simulations (Suniti Sanghavi, 2014; Suniti Sanghavi & Stephens, 2015) and forward modeling (Suniti Sanghavi et al., 2014; S. V. Sanghavi et al., 2013; Suniti Sanghavi & Natraj, 2013). The resulting framework was used to carry out sensitivity studies and information content analyses of the influence of aerosol and cloud properties on OCO/GOSAT measurements (S. Sanghavi et al., 2015; Suniti Sanghavi et al., 2020). The vSmartMOM modeling framework has also been applied to study the cloudy atmospheres of exoplanets and brown dwarfs (Suniti Sanghavi et al., 2021; Suniti Sanghavi & Shporer, 2018; Suniti Sanghavi & West, 2019). Following the GPU adaptation of vSmartMOM (Jeyaram et al., 2022), Dr. Sanghavi’s work led to the development of a GPU accelerated inelastic scattering model (Suniti Sanghavi, 2022; Suniti Sanghavi & Frankenberg, 2023) that allows the correction of hyperspectral retrievals for biases caused by Raman scattering. Similar corrections due to the hyperspectral effects of canopy radiative transfer are being developed jointly with Dr. Frankenberg.