A Unified Radiative Transfer Model: Microwave to Infrared Tom Greenwald CIMSS

Motivation Why use one RT model across the thermal spectrum for multiple scattering calculations? Physics is the same Consistency in calculations Reduces complexity in applications such as multi-sensor retrievals of atmospheric/cloud properties and direct radiance data assimilation This presentation will examine monochromatic adjoint sensitivities and contrast them in clear sky and cloudy conditions

Description of Modeling System Multiple scattering RT model: Successive Order of Interaction (SOI) method (Heidinger et al. 2005; O’Dell et al. 2005) Fast and accurate (< 1 K over most conditions) Can accommodate any number of cloud layers Adaptive: variable number of streams (angular resolution). Other fast models do not have this flexibility since angular resolution is fixed Incorporated into CRTM and tested LBL gas absorption models: Infrared: LBLRTM v8.4 Microwave: Liebe MPM v. 1989

Description of Modeling System contd. Cloud single-scattering properties: Infrared: Tables of properties for mixture of habits (Baum et al. 2005) and individual habits (bullet rosettes, columns, plates, aggregates) based on rigorous techniques (Yang); water spheres based on Anomalous Diffraction Theory Microwave: Tables of properties for bullet rosettes, plates, columns and ice spheres based on DDA calculations (Evans) Adjoint models built for all forward models except LBLRTM

Experimental Setup Tropical mean temperature/humidity profiles Cloud properties

Experimental Setup contd. Surface properties Microwave emissivity: Fresnel equation; permittivity model from Stogryn et al. (1995) Infrared emissivity: Fixed 0.98 Geometry Zenith angle = 0o

Forward Results

Adjoint Sensitivity Analysis Jacobian Adjoint forcing • Definition of adjoint: • Forward vs. adjoint sensitivity: Adjoint is much faster and gives more accurate derivatives • Non-dimensional relative sensitivity (Zou et al. 1993):

Non-dimensional Tb Sensitivity to Atmospheric Temperature (Thermal Source only) Clear sky Cloudy

Non-dimensional Tb Sensitivity to Water Vapor Mixing Ratio Clear sky Cloudy

Absolute Tb Sensitivity to Water Vapor Mixing Ratio (K/g/kg) Clear sky Cloudy

Non-dimensional Tb Sensitivity to LWP and IWP

Summary Additional near-term work: An example of the capabilities of a unified RT modeling system was given and illustrated the complementary nature of information on the atmosphere and clouds in the microwave and IR Additional near-term work: Compare various techniques for handling gas absorption and scattering across spectral bands (e.g., k-distribution method and Optimal Spectral Sampling) Explore and further develop approximate physical methods (e.g., Anomalous Diffraction Theory) for fast computation of scattering properties