A Self-Consistent Radiative Transfer Model for Simulating Active and Passive Observations of Precipitation

Monday, 14 December 2015: 09:00
3022 (Moscone West)
Ian S Adams, US Naval Research Laboratory, Washington, DC, United States
Current generation sensors suites such as those included on the Global Precipitation Measurement (GPM) mission, Aquarius, and Soil Moisture Active / Passive (SMAP) exploit a combination to provide a greater understanding of geophysical phenomena. While “operationalized” retrieval algorithms require fast forward models, the ability to perform higher fidelity simulations is necessary for understanding the physics of remote sensing problems to test assumptions and to develop parameterizations for the fast models. To ensure proper synergy between active and passive modeling, forward models must be consistent between the two sensor types. This work presents a self-consistent active and passive radiative transfer model for simulating radar and radiometer responses to precipitation.

To accomplish this, we extend the Atmospheric Radiative Transfer Simulator (ARTS) version 2.3 to solve the radiative transfer equation for radar under multiple scattering conditions using Monte Carlo integration. Early versions of ARTS (1.1 and later) included a passive Monte Carlo solver, and ARTS is capable of handling atmospheres of up to three dimensions with ellipsoidal planetary geometries. The modular nature of ARTS facilitates extensibility, and the well-developed ray-tracing tools are suited for implementation of Monte Carlo algorithms. Finally, since ARTS handles the full Stokes vector, co- and cross-polarized reflectivity products are possible for scenarios that include nonspherical particles, with or without preferential alignment.

The accuracy of the forward model will be demonstrated, and the effects of multiple scattering will be detailed. The three-dimensional nature of the radiative transfer model will be useful for understanding the effects of nonuniform beamfill and multiple scattering for spatially heterogeneous precipitation events. This targets of this forward model are GPM (the Dual-wavelength Precipitation Radar (DPR) and GPM Microwave Imager (GMI)) and airborne sensors used in GPM-supporting ground validation missions.