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Likun Wang, Changyong Cao, and Pubu Ciren

Abstract

The High-Resolution Infrared Radiation Sounder (HIRS) has been carried on NOAA satellites for more than two decades, and the HIRS data have been widely used for geophysical retrievals, climate studies, and radiance assimilation for numerical weather prediction models. However, given the legacy of the filter-wheel radiometer originally designed in the 1970s, the HIRS measurement accuracy is neither well documented nor well understood, despite the importance of this information for data users, instrument manufacturers, and calibration scientists. The advent of hyperspectral sounders, such as the Atmospheric Infrared Sounder (AIRS), and intersatellite calibration techniques makes it possible to independently assess the accuracy of the HIRS radiances. This study independently assesses the data quality and calibration accuracy of HIRS by comparing the radiances between HIRS on NOAA-16 and AIRS on Aqua with simultaneous nadir overpass (SNO) observations for the year 2004. The results suggest that the HIRS radiometric bias relative to the AIRS-convolved HIRS radiance is on the order of ∼0.5 K, except channel 16, which has a bias of 0.8 K. For all eight spectrally overlapped channels, the observations by HIRS are warmer than the corresponding AIRS-convolved HIRS channel. Other than channel 16, the biases are temperature dependent. The root causes of the bias can be traced to a combination of the HIRS blackbody emissivity, nonlinearity, and spectral uncertainties. This study further demonstrates the utility of high-spectral-resolution radiance measurements for high-accuracy assessments of broadband radiometer calibration with the SNO observations.

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Changyong Cao, Kenneth Jarva, and Pubu Ciren

Abstract

Radiance data from the High-Resolution Infrared Radiation Sounder (HIRS) have been used routinely in both direct radiance assimilation for numerical weather prediction and climate change detection studies. The operational HIRS calibration algorithm is critical for producing accurate radiance to meet the user’s needs, and it has significant impacts on products at all levels. Since the HIRS does not calibrate every scan line, the calibration coefficients between calibration cycles have to be interpolated based on a number of assumptions. In the more than 25-yr history of operational HIRS calibration, several interpolation methods have been used and, unfortunately, depending on which method is used, these algorithms can produce HIRS level 1b radiance data with significant differences. By analyzing the relationship between the instrument self-emission and gain change during filter temperature fluctuations, in this paper a significant flaw in the previous operational calibration algorithm (version 3) is identified. This caused calibration errors greater than 0.5 K and periodically degraded the HIRS radiance data quality of NOAA-15, -16, and -17 between 1998 and 2005. A new HIRS calibration algorithm (version 4) is introduced to improve the calibration accuracy, along with better indicators for instrument noise in the level 1b data. The new algorithm has been validated in parallel tests before it became operational at NOAA/National Environmental Satellite Data and Information Service (NESDIS). Test results show that significant improvements in calibration accuracy can be achieved especially for NOAA-15/HIRS. Several areas of further calibration improvements are also identified. The new algorithm has been used for all operational satellites at NOAA/NESDIS since 28 April 2005.

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Changyong Cao, Hui Xu, Jerry Sullivan, Larry McMillin, Pubu Ciren, and Yu-Tai Hou

Abstract

Intersatellite radiance comparisons for the 19 infrared channels of the High-Resolution Infrared Radiation Sounders (HIRS) on board NOAA-15, -16, and -17 are performed with simultaneous nadir observations at the orbital intersections of the satellites in the polar regions, where each pair of the HIRS views the same earth target within a few seconds. Analysis of such datasets from 2000 to 2003 reveals unambiguous intersatellite radiance differences as well as calibration anomalies.

The results show that in general, the intersatellite relative biases are less than 0.5 K for most HIRS channels. The large biases in different channels differ in both magnitude and sign, and are likely to be caused by the differences and measurement uncertainties in the HIRS spectral response functions. The seasonal bias variation in the stratosphere channels is found to be highly correlated with the lapse rate factor approximated by the channel radiance differences. The method presented in this study works particularly well for channels sensing the stratosphere because of the relative spatial uniformity and stability of the stratosphere, for which the intercalibration accuracy and precision are mostly limited by the instrument noise. This method is simple and robust, and the results are highly repeatable and unambiguous. Intersatellite radiance calibration with this method is very useful for the on-orbit verification and monitoring of instrument performance, and is potentially useful for constructing long-term time series for climate studies.

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