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The Ozone Mapping and Profiler Suite (OMPS) Nadir Profilers (NPs) are advanced backscatter ultraviolet (BUV) hyperspectral instruments that measure ozone profiles in the Earth atmosphere. The first NP sensor onboard the Suomi National Polar-orbiting Partnership (Suomi-NPP) satellite began its science observations on January 26, 2012, after its aperture door opened. The second OMPS NP, flying on the NOAA-20 satellite, opened its aperture door on January 8, 2018, starting science its data collection. The two NP sensors acquire Earth spectral images along their satellite flight path with a 16.7° wide swath, enabling weekly coverage of vertical ozone distribution in the Earth atmosphere. A successful thorough sensor calibration enables the NP sensors’ data records (SDRs) to meet measurement accuracy requirements. The largest error term in the albedo calibration came from the spectral wavelength calibration. This article provides SDRs accuracy analysis for both NP sensors and discusses important aspects of the SDRs performance in relation to the sensors’ characterization and calibration. [ABSTRACT FROM AUTHOR]

The Suomi National Polar-Orbiting Partnership ( S-NPP) satellite was successfully launched on 28 October 2011. It carries five new-generation instruments, including the Visible Infrared Imaging Radiometer Suite (VIIRS). The VIIRS is a whiskbroom radiometer that scans the surface of the earth using a rotating telescope assembly, a double-sided half-angle mirror, and 16 individual detectors. Substantial efforts are being made to accurately calibrate all detectors in orbit. As of this writing, VIIRS striping is reduced to levels below those seen in corresponding Terra and Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) bands and meets the program specifications and requirements. However, the level 2 SST products derived from level 1 sensor data records (SDRs) thermal emissive bands still show residual striping. These artifacts reduce the accuracy of SST measurements and adversely affect cloud masking and the output of downstream applications, such as thermal front detection. To improve the quality of SST imagery derived from the VIIRS sensor, an adaptive algorithm was developed for operational use within the National Environmental Satellite, Data, and Information Service (NESDIS)'s SST system. The methodology uses a unidirectional quadratic variational model to extract stripe noise from the observed image prior to nonlocal filtering. Evaluation of the algorithm performance over an extended dataset demonstrates a significant improvement in the Advanced Clear-Sky Processor for Oceans (ACSPO) VIIRS SST image quality, with normalized improvement factors (NIF) varying between 5% and 25%. [ABSTRACT FROM AUTHOR]

The MEdium-Resolution Spectral Imager (MERSI), onboard the second-generation Chinese polar-orbit meteorological satellite FY-3A, is a MODIS-like sensor with 19 solar bands and one thermal infrared band. Although there is a visible onboard calibration device, it can only be used for tracking temporal instrument degradation. The vicarious calibration (VC) campaign at the Dunhuang site, conducted once a year, has been the main postlaunch absolute radiometric calibration method for MERSI in the solar bands. To increase the in-flight calibration frequency, a multisite radiometric calibration tracking method is presented. This method relies on simulated radiation over several stable sites, and a daily calibration updating model is built from long-term trending of calibration coefficient series. The MERSI calibration reference is evaluated against the observations of Aqua MODIS, showing mean relative biases within 5% from 0.4 to 2.1 μm . The short-wave channels of MERSI are found to experience large degradation, particularly the 412-nm band with an annual degradation rate of 9.7%, whereas the red and near-infrared bands are relatively stable with annual degradation rates within ±1%. Several approaches have been used to analyze the reliability of MERSI calibration results. A comparison of the calibration slopes shows that the relative biases between the multisite method and the annual Dunhuang VC campaign are below 3.8%. Aqua MODIS is used as a reference to monitor the data quality of the recalibrated MERSI. A double-difference analysis shows that the mean relative biases are almost within 5% over stable deserts, and the synchronous nadir observation analysis also reveals good agreement. [ABSTRACT FROM AUTHOR]

The polar-orbiting satellite sensor, which can observe the entire Earth's surface with good spatial and spectral resolution, is a potential tool for estimation of global downward shortwave radiation (DSR). However, it can only provide a couple of snapshots in one day, which should be extended to daily-integrated DSR in order to drive the ecosystem models. In this paper, the temporal and spatial uncertainties for estimating of daily-integrated DSR from instantaneous measurements of polar-orbiting satellites are evaluated using geostationary Geosynchronous Meteorological Satellite-5 ( GMS-5) observations over East Asia. Those overpass times-including 1030, 1200, and 1330 local time (LT), which correspond to Terra/Moderate Resolution Imaging Spectroradiometer (MODIS), Sea-Viewing Wide Field-of-View Sensor (SeaWiFS), and Aqua/MODIS-are evaluated. The combinations of multiobservations are also assessed. The results show that the daily-integrated DSR from polar-orbiting satellite observations of 1030, 1200, and 1330 underestimate solar radiation by 2.16% (0.46 MJ m−2), 5.44% (1.16 MJ m−2), and 5.54% (1.09 MJ m−2), with an RMSE of 2.05 MJ m−2 (12.92%), 2.50 MJ m−2 (13.33%), and 2.34 MJ m−2 (13.95%) in East Asia with large spatial and seasonal variations. In general, the bias is higher in the southern than in the northern part of East Asia. It is low in January, February, and March, then increases from April and reaches the maximum in June and July, and decreases rapidly to lower than 1.0 MJ m−2 in October. The uncertainties of daily-integrated DSR could be reduced by averaging multiday observations or combining of multitime observations. These uncertainties' distributions are important for evaluation the usability of daily-integrated DSR from polar-orbiting satellite data and probably can be used for its calibration. [ABSTRACT FROM AUTHOR]