In this paper, we will present a Single Field-of-view (FOV) Sounder Atmospheric Product (SiFSAP) and a Climate Fingerprinting Sounder Product (ClimFiSP). Both products are derived from hyperspectral Infrared remote sensors such as Atmospheric Infrared Sounder (AIRS) and Cross-track Infrared Sounder (CrIS). Compared to the current operational AIRS and CrIS level-2 algorithms, the SiFSAP algorithm has 3 advantages, which are listed in the technical review abstract. We have developed a ClimFiSP product, which is derived from spatiotemporally averaged level-1 hyperspectral radiances directly. Again, the ClimFiSP algorithm overcomes many issues associated with traditional level-1 to level-2 and then to level-3 approach. It can be used to derive climate change signals from multiple satellite sensors using consistent radiative kernels and a robust spectral fingerprinting method. We have applied this method to both AIRS and CrIS data and generated decade-long climate data records for atmospheric temperature, water vapor, cloud, trace gases, and surface skin temperature. Both SiFSAP and ClimFiSP are being transitioned to NASA data centers for routine generations of both level-2 and level-3 products.
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