Potential roles of satellite hyperspectral IR sensors in monitoring greenhouse effects

As we enter a new era of using satellite hyperspectral sensors for weather and other environmental applications, this paper discusses the applicability of using IR hyperspectral data for climate change monitoring; in particular, for quantifying the greenhouse effects. While broadband 1st order statistics quantify radiative forcings, the IR hyperspectral data provides a means of monitoring feedback processes. Radiative transfer modeling of the greenhouse effect is illustrated with examples: varying surface temperature, atmospheric temperature and water vapor. Three spectral greenhouse metrics are discussed: the difference between the surface emission and the outgoing longwave radiation (G), the surface-temperature normalized greenhouse effect (g) and vertical profile of cooling rate (C). Effects of changes in water vapor, clouds, carbon dioxide and methane are modeled and their potential observables identified.