Assessment of S-NPP VIIRS On-Orbit Radiometric Calibration and Performance

Xiong, Xiaoxiong; Butler, James J.; Chiang, K.; Efremova, Boryana; Fulbright, Jon P.; Lei, Ning; McIntire, Jeff; Oudrari, Hassan; Wang, Zhipeng; Wu, Aisheng

doi:10.3390/rs8020084

Cited by 43 publications

(34 citation statements)

References 44 publications

(63 reference statements)

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“…Recall that the AVHRR sensor was not designed with climate objectives in mind. As such, its calibration remains challenging and is unlikely to reach the accuracy and precision achieved with the more advanced MODIS and VIIRS sensors [23][24][25]. However, the time series of the calibration, derived BTs and L2 products can be stabilized.…”

Section: Discussionmentioning

confidence: 99%

Sensor Stability for SST (3S): Toward Improved Long-Term Characterization of AVHRR Thermal Bands

Ignatov

Kihai

et al. 2016

Remote Sensing

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Abstract:Recently, the National Oceanic and Atmospheric Administration (NOAA) performed sea surface temperature (SST) reanalysis (RAN1) from seven AVHRR/3s onboard NOAA-15 to -19 and Metop-A and -B, from 2002-present. Operational L1b data were used as input. The time series of clear-sky ocean brightness temperatures (BTs) and derived SSTs were found to be unstable. The SSTs were empirically stabilized against in situ SSTs using a 90-day moving filter, while the measured BTs were left intact. However, some users are interested in direct radiance assimilation and need stable BTs. Additionally, stabilized BTs will greatly benefit SST (by minimizing the need for their empirical stabilization), and other Level 2 products derived from AVHRR. To better understand the AVHRR calibration and stabilize its BTs, the Sensor Stability for SST (3S; www.star.nesdis.noaa.gov/sod/sst/3s/) system was established at NOAA, which monitors orbital statistics of the sensor measured blackbody temperatures (BBTs), blackbody counts (BCs), and the space counts (SCs), along with the derived calibration gains and offsets. Analyses are performed separately for the satellite night (when the satellite is in the Earth's shadow) and day (on the sunlit part of its orbit). Factors affecting the BBT, BC and SC are also monitored, including the Sun and Moon position relative to the sensor, local equator crossing time, and duration of the satellite night. All AVHRRs show long-term and band-specific smooth changes in the calibration gains and offsets, which are occasionally perturbed by spurious non-monotonic anomalies. The most prominent irregularities occur shortly after the satellite crosses from the night into day, or when it is in a (near) full Sun orbit for extended periods of time. We argue that the operational quality control (QC) and calibration procedures are suboptimal and should be improved. Analyses in 3S suggest that a more stringent QC is needed, and scan lines where the calibration coefficients cannot be derived, due to poor quality SC, BC or BBT data, should be filled in by interpolation from the best parts of orbit or more broadly satellite lifetime. Work is underway to redesign the AVHRR QC and calibration algorithms and create a more stable long-term record of AVHRR calibration and BTs, and use them in the subsequent SST RANs.

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Section: Discussionmentioning

confidence: 99%

Sensor Stability for SST (3S): Toward Improved Long-Term Characterization of AVHRR Thermal Bands

Ignatov

Kihai

et al. 2016

Remote Sensing

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“…The VIIRS optical path from the entrance aperture first passes through the rotating telescope assembly (RTA), which is composed of an afocal three mirror anastigmat followed by a fold mirror [4,6]. The RTA rotates once about every 1.78 s perpendicular to the spacecraft's direction of motion, viewing a ±56 degree swath through the Earth view port.…”

Section: Viirs Overviewmentioning

confidence: 99%

“…On orbit, the calibration of both the reflective and emissive bands is maintained largely through views of the onboard calibration targets (solar diffuser and internal blackbody, respectively) [4,5]. To transfer the calibration from either target to the Earth view data, knowledge of the RVS is required.…”

Section: Viirs Overviewmentioning

confidence: 99%

“…VIIRS is a cross-track scanning radiometer that was designed to fly aboard satellites in a polar, sun-synchronous orbit, giving it the capacity to image the Earth twice a day [4,7]. The VIIRS optical path from the entrance aperture first passes through the rotating telescope assembly (RTA), which is composed of an afocal three mirror anastigmat followed by a fold mirror [4,6].…”

Section: Viirs Overviewmentioning

confidence: 99%

“…Space-borne remote sensing instruments have been critical to the development of Earth science, including applications to land, ocean, and atmospheric science disciplines [1][2][3]; one such sensor is the Visible Infrared Imaging Radiometer Suite (VIIRS) that has flown on the Suomi National Polar-orbiting Partnership (SNPP) since 2011 [4,5] and is scheduled to launch on the Joint Polar Satellite System 1 (JPSS-1) platform in November 2017 [6]. The third sensor in the series, scheduled to launch aboard the Joint Polar Satellite System 2 (JPSS-2) platform in 2021, is currently undergoing ground testing at the sensor vendor test facility (Raytheon El Segundo).…”

Section: Introductionmentioning

confidence: 99%

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Pre-Launch JPSS-2 VIIRS Response versus Scan Angle Characterization

et al. 2017

Self Cite

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On-orbit whisk-broom sensors have scanning mirror assemblies, whose reflectance variations with scan angle must be characterized prior to launch. One such instrument is the Visible Infrared Imaging Radiometer Suite (VIIRS) onboard the Joint Polar Satellite System 2 (JPSS-2) platform. The scanning optics inside VIIRS includes a four mirror rotating telescope assembly (RTA) and a half angle mirror (HAM), rotating at half the speed of the RTA, which de-rotates the light before it enters the aft-optics assembly. The angle of incidence (AOI) on the HAM varies with scan angle; all of the other optical components in VIIRS have a fixed AOI with scan angle. In general, the reflectance of the HAM will vary with AOI. This parameter is difficult to quantify once in orbit and therefore must be characterized pre-launch. Ground measurements were performed in the summer of 2016 to determine the relative reflectance change of the instrument with scan angle, referred to as the response versus scan angle (RVS). This work will describe the RVS testing performed and the results obtained, including an atmospheric water vapor correction and an uncertainty analysis. Results indicate that the reflectance variation with scan angle is small for spectral bands between 0.4 µm and 4 µm (less than 2% over the full range of AOI); in contrast, the reflectance variation is between 3% and 10% for the spectral bands in the 8 µm to 12 µm range. Uncertainties are below 0.05% in the reflective solar spectral region and below 0.26% in the thermal emissive spectral region. Comparisons to previous VIIRS builds (on the SNPP and JPSS-1 satellites) show comparable performance.

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Characterizing the information content of cloud thermodynamic phase retrievals from the notional PACE OCI shortwave reflectance measurements

Coddington

Vukićević²,

Schmidt

et al. 2017

JGR Atmospheres

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We rigorously quantify the probability of liquid or ice thermodynamic phase using only shortwave spectral channels specific to the National Aeronautics and Space Administration's Moderate Resolution Imaging Spectroradiometer, Visible Infrared Imaging Radiometer Suite, and the notional future Plankton, Aerosol, Cloud, ocean Ecosystem imager. The results show that two shortwave‐infrared channels (2135 and 2250 nm) provide more information on cloud thermodynamic phase than either channel alone; in one case, the probability of ice phase retrieval increases from 65 to 82% by combining 2135 and 2250 nm channels. The analysis is performed with a nonlinear statistical estimation approach, the GEneralized Nonlinear Retrieval Analysis (GENRA). The GENRA technique has previously been used to quantify the retrieval of cloud optical properties from passive shortwave observations, for an assumed thermodynamic phase. Here we present the methodology needed to extend the utility of GENRA to a binary thermodynamic phase space (i.e., liquid or ice). We apply formal information content metrics to quantify our results; two of these (mutual and conditional information) have not previously been used in the field of cloud studies.

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Assessment of S-NPP VIIRS On-Orbit Radiometric Calibration and Performance

Cited by 43 publications

References 44 publications

Sensor Stability for SST (3S): Toward Improved Long-Term Characterization of AVHRR Thermal Bands

Sensor Stability for SST (3S): Toward Improved Long-Term Characterization of AVHRR Thermal Bands

Pre-Launch JPSS-2 VIIRS Response versus Scan Angle Characterization

Characterizing the information content of cloud thermodynamic phase retrievals from the notional PACE OCI shortwave reflectance measurements

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