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The AMSU-A was designed to measure the vertical temperature profile from the Earth’s surface to the upper stratosphere with its 15 channels ranging from 23.8 to 89 GHz (Table 1). The AMSU-A is a total power, line-scanning radiometer with an instantaneous field of view (FOV) of 3.3° at the half-power points. Its antenna provides a cross-track scan, covering 48.33° on each side of the nadir direction with a total of 30 Earth FOVs per scan line. These scan patterns and geometric resolution translate to a 45-km-diameter cell at nadir and a 2343-km swath width on the ground from the 833-km nominal orbital altitude.

We used the Aqua and MetOp-A AMSU-A daily gridded brightness temperature data archived at the NOAA/National Centers for Environmental Information (NCEI) in the Climate Data Record Program ( to generate temperature anomaly time series. The dataset was originally produced by the NOAA/Center for Satellite Applications and Research (STAR) group as an AMSU-A fundamental climate data record (38). In this dataset, intersatellite biases were minimized for the AMSU-A observations onboard multiple polar-orbiting satellites, including NOAA-15 to NOAA-18, Aqua, and MetOp-A. For Aqua, only a constant offset was added to its original swath radiances for each individual channel to minimize its differences from AMSU-A observations from other satellites (10). In this sense, this version of the Aqua data preserved the characteristics in the original operational calibration in terms of calibration drift, that is, no additional calibration drift was introduced to the Aqua data by the intercalibration effort. For MetOp-A AMSU-A, constant offsets and optimal nonlinear calibration coefficients were applied to minimize its differences from other satellites. Different calibration nonlinearity affects the seasonal cycles observed by the AMSU-A channels (10). It may also affect the observed climate trends that are expected to be more reliable with optimal calibration nonlinearity. Uncertainties associated with this effect are discussed in the analysis section.

In addition to swath radiances at each scan angles, the NOAA/STAR AMSU-A fundamental climate data record contains limb-corrected brightness temperatures for Aqua, MetOp-A, and other satellites. A limb correction adjusts radiances at off-nadir view angles to those at the nadir direction. This adjustment allows the use of the off-nadir footprints in the same way as the nadir observations to increase observational samples and reduce noise and sampling-related biases in developing climate data record. The statistical algorithm developed by Goldberg et al. (39) was used for the AMSU-A limb adjustment, adjusting a target channel using adjacent channels. The NOAA/STAR AMSU-A daily gridded data were generated by accumulating and binning limb-adjusted AMSU-A brightness temperatures into grid cells with a resolution of 1° latitude by 1° longitude and then averaging them in daily intervals (38). Among the 30 FOVs in a scan line, only footprints from the scan positions 8 to 23 were used in the daily gridded products, because limb adjustments for these scan positions resulted in off-nadir biases of only 0.1 K (38, 40).

The Aqua and MetOp-A AMSU-A daily data contain files with ascending and descending orbits separately. We further averaged these daily data to derive ascending and descending monthly data with the same spatial resolution. We then calculated a multiyear average for each channel, which is referred to as the annual mean “climatology” throughout this study, for ascending and descending orbits separately and for their averages, by averaging data for the same month at each grid cell through the period from January 2012 to December 2016 (figs. S2 and S3). The period for this climatology is exactly the same as for the ATMS. This is important, as selection of different periods for climatology calculation will introduce signals not suitable for an apple-to-apple comparison of the anomaly time series. Temperature anomalies for ascending and descending orbits and for their averages were calculated for each grid cells based on their climatology. Global mean anomalies were an area-weighted average of the anomalies over the globe for ascending and descending orbits and their averages, respectively.

The archiving in NOAA/NCEI contains AMSU-A data from channels 4 to 14. Aqua AMSU-A channels 4 and 5 failed since September 2007 and April 2012, respectively. The failure in channel 5 affected the quality of limb adjustment for its adjacent channel 6. Therefore, we only compared Aqua/AMSU-A channels 7 through 14 to the ATMS data. Similarly, MetOp-A AMSU-A channels 7 and 8 failed since December 2009 and April 2016, respectively. The failure of these two channels caused quality issues for limb adjustments for their adjacent channels 6 and 9. As a result, we only compared MetOp-A/AMSU-A channels 4, 5, and 10 through 14 to the ATMS data.

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