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[1] Quantifying the radiometric difference and creating a calibration link between Atmospheric Infrared Sounder (AIRS) on Aqua and Infrared Atmospheric Sounding Interferometer (IASI) on MetOp are crucial for creating fundamental climate data records and intercalibrating other narrowband or broadband satellite instruments. This study employs two different methods to assess the AIRS and IASI radiance consistency within the four Geostationary Operational Environmental Satellite (GOES) imager infrared channels (with central wavelengths at 6.7, 10.7, 12.0, and 13.3 mm) through a period of 2 years and 9 months. The first method employs the differences of AIRS and IASI relative to the GOES observations sampled in the tropics to indirectly track the AIRS and IASI radiance differences. The second approach directly compares AIRS and IASI in the polar regions through the simultaneous nadir overpass observations. Both methods reveal that AIRS and IASI radiances are in good agreement with each other both in the tropics and in the polar regions within GOES imager channels used in this study, while AIRS is found to be slightly warmer than IASI by less than 0.1 K.

A cold bias of ∼ −2 K was found for Channel 6 (13.3 μm) of the Imager instrument on the 13th of Geostationary Operational Environmental Satellite (GOES-13) during its postlaunch tests. Similar bias was found previously for GOES-12 and for other instruments (the High Resolution Infrared Radiation Sounder, the Moderate Resolution Imaging Spectroradiometer, and the Spinning Enhanced Visible and Infrared Imager) in the similar spectral region. It was often suspected that the spectral response function (SRF) of these instruments may be in error; in some cases, it had been demonstrated that an altered SRF can eliminate most of the differences between the measured and the expected values. Using products recently developed for the Global Space-based Inter-Calibration System, this paper concluded that an SRF error is the root cause for the GOES Imager Channel 6 bias. Based on this theory, an algorithm was developed to correct for the bias. Application of this correction to GOES-13 Imager Channel 6 resulted in an SRF shift of −2.1 cm −1 . The remaining biases have mean of nearly zero and much reduced standard deviation and are independent of the thermal structure of the interlaying atmosphere. This correction has also been successfully applied of other channels and of other GOES, which was described in a companion paper.

Abstract:The Advanced Himawari Imager (AHI) on-board Himawari-8, which was launched on 7 October 2014, is the first geostationary instrument housed with a solar diffuser to provide accurate onboard calibrated data for the visible and near-infrared (VNIR) bands. In this study, the Ray-matching and collocated Deep Convective Cloud (DCC) methods, both of which are based on incidently collocated homogeneous pairs between AHI and Suomi NPP (S-NPP) Visible Infrared Imaging Radiometer Suite (VIIRS), are used to evaluate the calibration difference between these two instruments. While the Ray-matching method is used to examine the reflectance difference over the all-sky collocations with similar viewing and illumination geometries, the near lambertian collocated DCC pxiels are used to examine the difference for the median or high reflectance scenes. Strong linear relationships between AHI and VIIRS can be found at all the paired AHI and VIIRS bands. Results of both methods indicate that AHI radiometric calibration accuracy agrees well with VIIRS data within 5% for B1-4 and B6 at mid and high reflectance scenes, while AHI B5 is generally brighter than VIIRS by~6%-8%. No apparent East-West viewing angle dependent calibration difference can be found at all the VNIR bands. Compared to the Ray-matching method, the collocated DCC method provides less uncertainty of inter-calibration results at near-infrared (NIR) bands. As AHI has similar optics and calibration designs to the GOES-R Advanced Baseline Imager (ABI), which is currently scheduled to launch in fall 2016, the on-orbit AHI data provides a unique opportunity to develop, test and examine the cal/val tools developed for ABI.

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