Satellites provide an ideal platform to study the Earth-atmosphere system on practically all spatial and temporal scales. Thus, one may expect that their rapidly growing datasets could provide crucial insights not only for short-term weather processes/predictions but into ongoing and future climate change processes as well. For example, outgoing longwave radiation (OLR), probably the most important parameter to assess global climate change, since the Earth-atmosphere system has to adjust to the new energy balance, is well suited for satellite monitoring. In addition to its primary dependence of the atmospheric temperature profile and cloud distribution, the OLR is dependent on natural and man-induced changes of various radiatively important atmospheric constituents like water vapor, carbon-dioxide, and other trace gases. The AIRS instrument is the best space-based tool so far to simultaneously monitor all of the above-mentioned parameters, and has provided high quality data for more than 5 years. AIRS analysis results produced at the GODDARD/DAAC, based on Versions 4 & 5 of the AIRS retrieval algorithm, are currently available for public use.

Here we present AIRS-retrievals-based (based on 5 full years, since Sept. 2002) global, regional and 1x1 degree grid-scale “trend”-analyses of important atmospheric parameters (e. g., temperature and moisture fields, in addition to OLR and cloud fields) and investigate their interrelationships. Note that here “trend” simply means the linear fit to the anomaly (relative the mean seasonal cycle) time series of various parameters at the above-mentioned spatial scales, and we present these to illustrate the usefulness of continuing AIRS-based climate observations.

We also present preliminary validation efforts in terms of intercomparisons of interannual variabilities with other available satellite data analysis results. For example, we show that the OLR interannual spatial variabilities from the available state-of-the-art CERES measurements and from the AIRS computations are in remarkably good agreement. Version 6 of the AIRS retrieval scheme (currently under development) promises to further improve bias agreements for the absolute values by implementing a more accurate radiative transfer model for the OLR computations.