Abstract
Abstract. In anticipation of the upcoming GOES-R launch we simulate visible and near-infrared reflectances of the Advanced Baseline Imager (ABI) for cases of high aerosol loading containing regional haze and smoke over the eastern United States. The simulations are performed using the Weather Research and Forecasting (WRF), Sparse Matrix Operator Kernel Emissions (SMOKE), and Community Multiscale Air Quality (CMAQ) models. Geostationary, satellite-derived, biomass-burning emissions are also included as an input to CMAQ. Using the CMAQ aerosol concentrations and Mie calculations, radiance is computed from the discrete ordinate atmospheric radiative transfer model. We present detailed methods for deriving aerosol extinction from WRF and CMAQ outputs. Our results show that the model simulations create a realistic set of reflectances in various aerosol scenarios. The simulated reflectances provide distinct spectral features of aerosols which are then compared to data from the Moderate Resolution Imaging Spectroradiometer (MODIS). We also present a simple technique to synthesize green band reflectance (which will not be available on the ABI), using the model-simulated blue and red band reflectance. This study is an example of the use of air quality modeling in improving products and techniques for Earth-observing missions.
Highlights
The Geostationary Operational Environmental Satellites-R Series (GOES-R) is the generation of geostationary satellites that will offer a continuation of current products and services and enable new and improved applications (Schmit et al, 2005)
We use the Discrete Ordinate Radiative Transfer model (Ricchiazzi et al, 1998), coupled to the existing CMAQ modeling system. This consists of three primary modeling components (Yang et al, 2011): the Weather Research and Forecasting model (WRF, version 3.2; Grell et al, 1995), Sparse Matrix Operator Kernel Emissions (SMOKE) model (SMOKE, version 2.5; Houyoux et al, 2000), and Community Multiscale Air Quality (CMAQ, version 4.6)
From the perspective of spectral signature of various features, we present a simple technique to synthesize green band reflectance, which will not be available on Advanced Baseline Imager (ABI)
Summary
The Geostationary Operational Environmental Satellites-R Series (GOES-R) is the generation of geostationary satellites that will offer a continuation of current products and services and enable new and improved applications (Schmit et al, 2005). The ABI will provide data in 16 spectral bands in the visible (0.47 and 0.64 μm), near-infrared (0.87, 1.38, 1.61, and 2.25 μm) and infrared (3.9, 6.19, 6.95, 7.34, 8.5, 9.61, 10.35, 11.2, 12.3, and 13.3 μm) portions of the electromagnetic spectrum These improvements will help data assimilation and numerical weather prediction (NWP) applications, especially by providing crucial observations for regional and mesoscale data assimilations and predictions (Schmit et al, 2005). We use the Discrete Ordinate Radiative Transfer model (Ricchiazzi et al, 1998), coupled to the existing CMAQ modeling system This consists of three primary modeling components (Yang et al, 2011): the Weather Research and Forecasting model (WRF, version 3.2; Grell et al, 1995), Sparse Matrix Operator Kernel Emissions (SMOKE) model (SMOKE, version 2.5; Houyoux et al, 2000), and Community Multiscale Air Quality (CMAQ, version 4.6). We show the synthetic RGB imagery that is produced based on the red, green (synthesized), and blue band reflectance
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