Visible Infrared Imaging Radiometer Suite Sea Surface Temperature Research Articles

The Effects of VIIRS Detector-Level and Band-Averaged Relative Spectral Response Differences Between S-NPP and NOAA-20 on the Thermal Emissive Bands

The Joint Polar Satellite System-1 (renamed NOAA-20 after reaching the polar orbit) was successfully launched on November 18, 2017, into an afternoon orbit with a local equator crossing time of ∼1:30 p.m. , in the same orbital plane as the Suomi National Polar-orbiting Partnership (S-NPP) but with a time separation of 50 min. The NOAA-20 Visible Infrared Imaging Radiometer Suite (VIIRS) will become the primary operational imager succeeding the VIIRS onboard S-NPP, which has been in orbit for more than six years. Although the VIIRS onboard S-NPP and NOAA-20 have identical designs, there are small differences in the relative spectral response (RSR) in most bands. Previous studies have shown that minor differences in the S-NPP RSRs at thermal emissive bands (TEBs) can lead to several effects at the detector level, such as striping in sensor data record (SDR) products. Such differences may explain the striping pattern found in S-NPP VIIRS sea surface temperature (SST) products. This article analyzes the detector-level and operational band-averaged RSRs for NOAA-20 VIIRS TEBs and examines the radiometric response to them using the line-by-line radiative transfer model at a very high spectral resolution for convolving with the RSRs. We also evaluate the impact of RSR differences between S-NPP and NOAA-20 for radiometric biases and potential striping in VIIRS TEB SDR brightness temperature. This article will contribute toward measurement consistency for long-term observations in the thermal infrared bands and ensure the quality of retrieval data produced by VIIRS, such as SST, fire, and other retrievals.

Evaluation and selection of SST regression algorithms for JPSS VIIRS

AbstractTwo global level 2 sea surface temperature (SST) products are generated at NOAA from the Suomi National Polar‐Orbiting Partnership Visible Infrared Imaging Radiometer Suite (VIIRS) sensor data records (L1) with two independent processing systems, the Joint Polar Satellite System (JPSS) Interface Data Processing Segment (IDPS) and the NOAA heritage Advanced Clear‐Sky Processor for Oceans (ACSPO). The two systems use different SST retrieval and cloud masking algorithms. Validation against in situ and L4 analyses has shown suboptimal performance of the IDPS product. In this context, existing operational and proposed SST algorithms have been evaluated for their potential implementation in IDPS. This paper documents the evaluation methodology and results. The performance of SST retrievals is characterized with bias and standard deviation with respect to in situ SSTs and sensitivity to true SST. Given three retrieval metrics, all being variable in space and with observational conditions, an additional integral metric is needed to evaluate the overall performance of SST algorithms. Therefore, we introduce the Quality Retrieval Domain (QRD) as a part of the global ocean, where the retrieval characteristics meet predefined specifications. Based on the QRDs analyses for all tested algorithms over a representative range of specifications for accuracy, precision, and sensitivity, we have selected the algorithms developed at the EUMETSAT Ocean and Sea Ice Satellite Application Facility (OSI‐SAF) for implementation in IDPS and ACSPO. Testing the OSI‐SAF algorithms with ACSPO and IDPS products shows the improved consistency between VIIRS SST and Reynolds L4 daily analysis. Further improvement of the IDPS SST product requires adjustment of the VIIRS cloud and ice masks.