Lawrence E. Flynn

The Ozone Mapping and Profiler Suites (OMPS) Nadir Mapper (NM) is a grating spectrometer within the OMPS nadir instruments onboard the SNPP, NOAA-20, and NOAA-21 satellites. It is designed to measure Earth radiance and solar irradiance spectra in wavelengths from 300 nm to 380 nm for operational retrievals of the nadir total column ozone. This study presents calibration and validation analysis results for the NOAA-21 OMPS NM SDR data to meet the JPSS scientific requirements. The NOAA-21 OMPS SDR calibration derives updates of several previous OMPS algorithms, including the dark current correction algorithm, one-time wavelength registration from ground to on-orbit, daily intra-orbit wavelength shift correction, and stray light correction. Additionally, this study derives an empirical scale factor to remove 2.2% of systematic biases in solar flux data, which were caused by pre-launch solar calibration errors of the OMPS nadir instruments. The validation of the NOAA-21 OMPS SDR data is conducted using various methods. For example, the 32-day average method and radiative transfer model are employed to estimate inter-sensor radiometric calibration differences from either the SNPP or NOAA-20 data. The quality of the NOAA-21 OMPS NM SDR data is largely consistent with that of the SNPP and NOAA-20 OMPS data, with differences generally within ±2%. This meets the scientific requirements, except for some deviations mainly in the dichroic range between 300 nm and 303 nm. The deep convective cloud target approach is used to monitor the stability of NOAA-21 OMPS reflectance above 330 nm, showing a variation of 0.5% over the observed period. Data from the NOAA-21 VIIRS M1 band are used to estimate OMPS NM data geolocation errors, revealing that along-track errors can reach up to 3 km, while cross-track errors are generally within ±1 km.

The Ozone Mapping and Profiler Suite (OMPS) has been onboard the Suomi National Polar-orbiting Partnership (S-NPP) satellite since October 2011, and was followed by an OMPS on NOAA-20 (N20) in November 2017, as part of the US Joint Polar Satellite System (JPSS) program. The OMPS measurements are processed to yield various products of atmospheric composition data for near-real-time monitoring and off-line study, including retrievals of total column ozone (TCO) and an Ultraviolet absorbing aerosol index (AI) based on the version-8 total ozone (V8TOZ) algorithm. With the implementation of changes to employ a broadband channel approach in the NOAA OMPS V8TOZ, the retrieved TCO and AI products become more stable and consistent between S-NPP and N20. Two particular regions have been chosen for building soft-calibration adjustments for both OMPS S-NPP and N20, which force the V8TOZ retrievals to be in quite good agreement from both sensors with little change by seasons. However, bias analysis shows that some noticeable errors / differences still exist after soft-calibration, and those errors appear to be quite persistently associated with solar zenith angle (SZA) and satellite viewing angle (SVA) in the retrievals of TCO and AI for both OMPS S-NPP and N20. Comparisons of TCO and AI from NOAA OMPS retrievals with other products such as those from the Tropospheric Monitoring Instrument (TROPOMI) and the Earth Polychromatic Imaging Camera (EPIC), show that, although the sensor, algorithm and solar spectra are different among them, the overall retrievals from those products are quite similar and consistent.

The Ozone Mapping and Profiler Suite (OMPS) has been onboard the Suomi National Polar-orbiting Partnership (S-NPP) satellite since October 2011, and was followed by an OMPS on NOAA-20 (N20) in November 2017, as part of the US Joint Polar Satellite System (JPSS) program. The OMPS measurements are processed to yield various products of atmospheric composition data for near-real-time monitoring and off-line study, including retrievals of total column ozone (TCO) and an Ultraviolet absorbing aerosol index (AI) based on the version-8 total ozone (V8TOZ) algorithm. With the implementation of changes to employ a broadband channel approach in the NOAA OMPS V8TOZ, the retrieved TCO and AI products become more stable and consistent between S-NPP and N20. Two particular regions have been chosen for building soft-calibration adjustments for both OMPS S-NPP and N20, which force the V8TOZ retrievals to be in quite good agreement from both sensors with little change by seasons. However, bias analysis shows that some noticeable errors / differences still exist after soft-calibration, and those errors appear to be quite persistently associated with solar zenith angle (SZA) and satellite viewing angle (SVA) in the retrievals of TCO and AI for both OMPS S-NPP and N20. Comparisons of TCO and AI from NOAA OMPS retrievals with other products such as those from the Tropospheric Monitoring Instrument (TROPOMI) and the Earth Polychromatic Imaging Camera (EPIC), show that, although the sensor, algorithm and solar spectra are different among them, the overall retrievals from those products are quite similar and consistent.

The Ozone Mapping and Profiler Suite (OMPS) has been onboard the Suomi National Polar-orbiting Partnership (S-NPP) satellite since October 2011, and was followed by an OMPS on NOAA-20 (N20) in November 2017, as part of the US Joint Polar Satellite System (JPSS) program. The OMPS measurements are processed to yield various products of atmospheric composition data for near-real-time monitoring and off-line study, including retrievals of total column ozone (TCO) and an Ultraviolet absorbing aerosol index (AI) based on the version-8 total ozone (V8TOZ) algorithm. With the implementation of changes to employ a broadband channel approach in the NOAA OMPS V8TOZ, the retrieved TCO and AI products become more stable and consistent between S-NPP and N20. Two particular regions have been chosen for building soft-calibration adjustments for both OMPS S-NPP and N20, which force the V8TOZ retrievals to be in quite good agreement from both sensors with little change by seasons. However, bias analysis shows that some noticeable errors / differences still exist after soft-calibration, and those errors appear to be quite persistently associated with solar zenith angle (SZA) and satellite viewing angle (SVA) in the retrievals of TCO and AI for both OMPS S-NPP and N20. Comparisons of TCO and AI from NOAA OMPS retrievals with other products such as those from the Tropospheric Monitoring Instrument (TROPOMI) and the Earth Polychromatic Imaging Camera (EPIC), show that, although the sensor, algorithm and solar spectra are different among them, the overall retrievals from those products are quite similar and consistent.

The Ozone Mapping and Profiler Suite (OMPS) has been onboard the Suomi National Polar-orbiting Partnership (S-NPP) satellite since October 2011, and was followed by an OMPS on NOAA-20 (N20) in November 2017, as part of the US Joint Polar Satellite System (JPSS) program. The OMPS measurements are processed to yield various products of atmospheric composition data for near-real-time monitoring and off-line study, including retrievals of total column ozone (TCO) and an Ultraviolet absorbing aerosol index (AI) based on the version-8 total ozone (V8TOZ) algorithm. With the implementation of changes to employ a broadband channel approach in the NOAA OMPS V8TOZ, the retrieved TCO and AI products become more stable and consistent between S-NPP and N20. Two particular regions have been chosen for building soft-calibration adjustments for both OMPS S-NPP and N20, which force the V8TOZ retrievals to be in quite good agreement from both sensors with little change by seasons. However, bias analysis shows that some noticeable errors / differences still exist after soft-calibration, and those errors appear to be quite persistently associated with solar zenith angle (SZA) and satellite viewing angle (SVA) in the retrievals of TCO and AI for both OMPS S-NPP and N20. Comparisons of TCO and AI from NOAA OMPS retrievals with other products such as those from the Tropospheric Monitoring Instrument (TROPOMI) and the Earth Polychromatic Imaging Camera (EPIC), show that, although the sensor, algorithm and solar spectra are different among them, the overall retrievals from those products are quite similar and consistent.

The Ozone Mapping and Profiler Suite (OMPS) has been onboard the Suomi National Polar-orbiting Partnership (S-NPP) satellite since October 2011, and was followed by an OMPS on NOAA-20 (N20) in November 2017, as part of the US Joint Polar Satellite System (JPSS) program. The OMPS measurements are processed to yield various products of atmospheric composition data for near-real-time monitoring and off-line study, including retrievals of total column ozone (TCO) and an Ultraviolet absorbing aerosol index (AI) based on the version-8 total ozone (V8TOZ) algorithm. With the implementation of changes to employ a broadband channel approach in the NOAA OMPS V8TOZ, the retrieved TCO and AI products become more stable and consistent between S-NPP and N20. Two particular regions have been chosen for building soft-calibration adjustments for both OMPS S-NPP and N20, which force the V8TOZ retrievals to be in quite good agreement from both sensors with little change by seasons. However, bias analysis shows that some noticeable errors / differences still exist after soft-calibration, and those errors appear to be quite persistently associated with solar zenith angle (SZA) and satellite viewing angle (SVA) in the retrievals of TCO and AI for both OMPS S-NPP and N20. Comparisons of TCO and AI from NOAA OMPS retrievals with other products such as those from the Tropospheric Monitoring Instrument (TROPOMI) and the Earth Polychromatic Imaging Camera (EPIC), show that, although the sensor, algorithm and solar spectra are different among them, the overall retrievals from those products are quite similar and consistent.

This article introduces a method to correct intersensor calibration convolution errors that occur in the convolution of spectral response functions (SRFs) between narrow-band and broad-band instruments. By using the intersensor calibration analysis between Ozone Mapping and Profiler Suite (OMPS) Nadir Mapper (NM) and Global Ozone Monitoring Experiment-2 (GOME-2) as an example, the root cause of convolution errors in the intersensor calibration is addressed through direct comparison of OMPS NM SRF and convolved OMPS SRF with GOME-2 SRF. The results reveal that distorted SRF of the narrow-band instrument is the major cause, which appears for GOME-2 at a wide range of channels. The convolution errors in reflectance, which were ignored in previous studies, can be greater than 2% for wavelength shorter than 320 nm and $\sim 0.5$ % for wavelengths between 320 and 330 nm. This study thus presents a hybrid convolution error correction method that consists of theoretical approximation of the convolution errors and empirical estimates of residuals due to the deviation of the theoretical approximation from the actual convolution errors. According to the validation through simulation, after applying convolution error correction, the mean convolution errors are less than 0.02%, while the root mean square errors are reduced from more than 0.5% to less than 0.1%. In addition, the correction method is applied to the intersensor calibration radiometric bias assessment between the Meteorological Operational satellite–B (Metop-B) GOME-2 and the Suomi National Polar-orbiting Partnership (S-NPP) OMPS NM. The averaged intersensor calibration reflectance differences are decreased by more than 16% after convolution error correction.

The launch of the National Oceanic and Atmospheric Administration (NOAA)/ National Aeronautics and Space Administration (NASA) Suomi National Polar-orbiting Partnership (S-NPP) and its follow-on NOAA Joint Polar Satellite Systems (JPSS) satellites marks the beginning of a new era of operational satellite observations of the Earth and atmosphere for environmental applications with high spatial resolution and sampling rate. The S-NPP and JPSS are equipped with five instruments, each with advanced design in Earth sampling, including the Advanced Technology Microwave Sounder (ATMS), the Cross-track Infrared Sounder (CrIS), the Ozone Mapping and Profiler Suite (OMPS), the Visible Infrared Imaging Radiometer Suite (VIIRS), and the Clouds and the Earth’s Radiant Energy System (CERES). Among them, the ATMS is the new generation of microwave sounder measuring temperature profiles from the surface to the upper stratosphere and moisture profiles from the surface to the upper troposphere, while CrIS is the first of a series of advanced operational hyperspectral sounders providing more accurate atmospheric and moisture sounding observations with higher vertical resolution for weather and climate applications. The OMPS instrument measures solar backscattered ultraviolet to provide information on the concentrations of ozone in the Earth’s atmosphere, and VIIRS provides global observations of a variety of essential environmental variables over the land, atmosphere, cryosphere, and ocean with visible and infrared imagery. The CERES instrument measures the solar energy reflected by the Earth, the longwave radiative emission from the Earth, and the role of cloud processes in the Earth’s energy balance. Presently, observations from several instruments on S-NPP and JPSS-1 (re-named NOAA-20 after launch) provide near real-time monitoring of the environmental changes and improve weather forecasting by assimilation into numerical weather prediction models. Envisioning the need for consistencies in satellite retrievals, improving climate reanalyses, development of climate data records, and improving numerical weather forecasting, the NOAA/Center for Satellite Applications and Research (STAR) has been reprocessing the S-NPP observations for ATMS, CrIS, OMPS, and VIIRS through their life cycle. This article provides a summary of the instrument observing principles, data characteristics, reprocessing approaches, calibration algorithms, and validation results of the reprocessed sensor data records. The reprocessing generated consistent Level-1 sensor data records using unified and consistent calibration algorithms for each instrument that removed artificial jumps in data owing to operational changes, instrument anomalies, contaminations by anomaly views of the environment or spacecraft, and other causes. The reprocessed sensor data records were compared with and validated against other observations for a consistency check whenever such data were available. The reprocessed data will be archived in the NOAA data center with the same format as the operational data and technical support for data requests. Such a reprocessing is expected to improve the efficiency of the use of the S-NPP and JPSS satellite data and the accuracy of the observed essential environmental variables through either consistent satellite retrievals or use of the reprocessed data in numerical data assimilations.