James L. Carr

The “stereo height assignment method” developed for NASA and NOAA for GOES-R ABI Atmospheric Motion Vectors (AMVs), a purely geometric method using the parallax observed from different satellites, has been included in the NWCSAF AMV product (NWCSAF GEO-I HRW, High Resolution Winds) as an additional height assignment option for AMVs in the region jointly observed by MTG-I and GOES-East over the Atlantic Ocean. Stereo and the alternative non-stereo height assignment (“Cross Correlation Contribution (CCC)”) are compared with ECMWF ERA5 reanalysis winds and EarthCARE ATLID Mie Attenuated Backscatter (MAB) curtains. For low-level clouds, both methods generally conform well with apparent cloud tops in MAB curtains. For higher clouds, more differences are seen between stereo and non-stereo heights. Compared with ERA5 winds, stereo shows the most improvement above 6 km. However, the stereo method produces 70–90% less AMVs since additional high-quality matches are needed from both FCI and ABI imagery. An updated HRW will be released to NWCSAF users in 2027 as version “NWCSAF GEO-I v2027.” The combined provision of both stereo and non-stereo CCC height assignment methods will enable further studies (already planned) of the AMV best-fit level for different satellite channels and cloud types, heights and depths.

The Tropospheric Emissions: Monitoring of Pollution (TEMPO) instrument is the first spaceborne hyperspectral spectrometer that measures backscattered sunlight over North America in a geostationary orbit. The two charge‐coupled device (CCD) detectors of TEMPO, with spectral coverages of 293–494 and 538–741 nm and resolutions of 0.53–0.63 nm, are capable of identifying absorption features of key trace gases, including ozone, nitrogen dioxide, formaldehyde, and others. Using a step‐and‐stare scanning mechanism, the TEMPO instrument measures backscattered Earth radiance spectra hourly during the middle of the day (nominal scans) and every 40 min in the early morning and late afternoon (optimized scans) to effectively cover the sunlit portions of the continent, with scans during twilight when permitted by instrument safety constraints. Solar irradiance measurements are also conducted nominally with a weekly frequency. This article describes the Version 3 algorithm for TEMPO Level 1b data processing, which provides radiometrically and spectrally calibrated solar irradiance and Earth radiance spectra as the primary outputs. The processing includes the conversion of digitized Level‐0 signals to radiance or irradiance, image navigation and registration for Earth spectra, and spectral calibration. This article also discusses calibration key data derived from pre‐launch instrument characterization and in‐flight calibration results.

The Tropospheric Emissions: Monitoring of Pollution (TEMPO) instrument provides continuous, high‐resolution observations of atmospheric pollutants over North America from geostationary orbit. This study introduces an on‐orbit spectral calibration algorithm implemented in the TEMPO Version 3 Level 0–1 processor, covering both operational irradiance and radiance wavelength calibrations and offline slit function retrievals. Irradiance wavelength calibration accuracy was evaluated, with the TSIS‐1 hybrid solar reference spectrum chosen due to its low fitting residuals. Accordingly, first‐ and second‐order Chebyshev‐polynomial fittings are applied to UV and VIS, respectively, to derive the wavelength grid. Earth‐view radiance wavelength calibration updates the wavelength grid based on the latest solar irradiance calibration result by fitting a wavelength shift. To optimize efficiency and accuracy, a narrow spectral window of 100 channels (320–340 nm for UV and 630–650 nm for VIS) was selected, with wavelength shift uncertainties of 0.002 nm (UV) and 0.006 nm (VIS). Radiance calibration results shows that the wavelength shifts of inhomogeneous pixels vary relatively significantly. We perform a 22‐month trend analysis of the TEMPO solar irradiance spectral performance. Compared to first light, the wavelength shift gradually increases, reaching 0.08–0.09 nm in July 2024, and then remains stable. The offline slit function parameters, retrieved from several narrow spectral windows using a super‐Gaussian function, show minor variations during the 22‐month on‐obit operation and did not deviate significantly from prelaunch. This study supports the long‐term L1b data processing for TEMPO and provides an instrument spectral calibration framework applicable for future geostationary orbit spectrometers.

Artificial Light at Night (ALAN) poses risks to public health and ecosystems. While long-term remote sensing has tracked global nighttime light, spectrally-resolved light at night (SLAN) data from geostationary orbit only became available with NASA’s Tropospheric Emissions: Monitoring of Pollution (TEMPO) mission. Its Level 1 twilight radiance product enables detailed spaciotemporal analysis of ALAN’s spectral characteristics. This study introduces algorithms for processing TEMPO Level 1 data into Level 2 SLAN data using two methods for solar background removal: scattering-angle correction and spectra correction. The first method uses the relationship between scattering angle and radiance to suppress background, while the second uses the inherent spectral relations in the solar radiation in 290–390 nm range, where artificial light emissions are minimized, to estimate direct twilight contributions. Combined, these methods yield more stable correction results. The results are validated against two independent datasets: the Visible Infrared Imaging Radiometer Suite (VIIRS) Day/Night Band (DNB) Black Marble product and astronaut photographs taken from the International Space Station (ISS) over Houston. Comparisons include (1) city light classifications from Black Marble vs. both raw and corrected TEMPO data, (2) pixel-to-pixel radiance measurements between TEMPO and VIIRS, and (3) spectral angle analyses between ISS and TEMPO data. We also compare CONUS nighttime light maps from VIIRS DNB, TEMPO VIS, and TEMPO UV; TEMPO VIS agrees closely with VIIRS DNB, while both diverge from TEMPO UV in gas-flaring regions, highlighting the complementary information these instruments provide.

Retrievals of ocean color (OC) properties from space are important for understanding the ocean ecosystem, the carbon cycle, and monitoring events such as harmful algal blooms (HABs). The recently launched U.S. National Aeronautics and Space Administration (NASA) Earth Venture Instrument, the geostationary Tropospheric Emissions: Monitoring of Pollution (TEMPO), provides a unique opportunity to examine diurnal variability in ocean ecology across coastal waters of North America and prepare for future hyperspectral geostationary OC missions. Although TEMPO does not match the spatial resolution or spectral coverage of planned coastal ocean sensors, such as NASA's Geosynchronous Littoral Imaging and Monitoring Radiometer or the U.S. National Oceanic and Atmospheric Administration Geostationary Extended Observations Ocean Color Instrument, it provides hourly observations at approximately 5 km over U.S. coastal regions and the Great Lakes. Here, we apply a newly developed atmospheric correction approach based on principal component analysis combined with machine learning (ML) to retrieve OC properties using TEMPO's hyperspectral measurements. Principal component coefficients derived from measured reflectances are used to train a neural network to estimate OC properties, including chlorophyll concentration, informed by collocated physically‐based retrievals from MODIS, VIIRS, and Ocean and Land Color Instrument. This ML‐based approach complements traditional radiative transfer retrievals, particularly under challenging conditions such as glint and moderate cloud coverage. This approach demonstrates the value of near‐real‐time OC products, with significant potential for monitoring HABs and transient oceanic phenomena.

The abundant nighttime (twilight) spectra from October 2024 are used for characterization of on‐orbit instrument performance of the Tropospheric Emissions: Monitoring of Pollution (TEMPO, a geostationary imaging spectrometer). We select 250 lightning flashes and measure the flash sizes and flash positions in 6 spectral domains spread across the two TEMPO detectors. Some of the flash sizes come close to ≈1 pixel ground‐based estimates of the instantaneous field of view in the North‐South direction. On average, spectral measurements across the two detectors are co‐registered to better than 0.15 pixels, thus also matching the pre‐flight assessments.

The NASA Tropospheric Emissions: Monitoring of Pollution (TEMPO) instrument is hosted on a geostationary commercial communications satellite. TEMPO is an imaging spectrometer with primary mission to measure trace‐gas concentrations from the observed spectra of reflected sunlight over the Continental United States and parts of Canada, Mexico, and the Caribbean. TEMPO produces an ultraviolet (UV, 293–494 nm) and a visible (538–741 nm) spectrum for each spatial pixel. TEMPO saw first light in August 2023. At night, TEMPO can observe city lights, gas flaring, maritime lights from fishing and offshore oil platforms, clouds and snow in the moonlight, lightning, aurorae, and nightglow without interfering with its primary daytime air quality/chemistry mission. This paper describes the capabilities of TEMPO to make nighttime observations and surveys of some early results. Repetitive coverage of North America enables production of clearest‐sky composites that are similar to VIIRS Day‐Night Band (DNB) “Black Marble” products. Spectra of urban areas contain spectral signatures of artificial lighting of various types that allow the radiance from each class of lighting to be estimated. Moonlight imaging of clouds provides a useful capability for discriminating clouds and fog. Lightning illuminating cloud tops from below is seen with distinct spectral features. Gas flares, associated with oil production, are observed and flare temperatures can be estimated from their spectra. Known auroral and nightglow spectral lines of atomic oxygen and molecular nitrogen are seen in the UV and visible spectra. The sodium d‐layer is also observed.

The Tropospheric Emissions: Monitoring of Pollution (TEMPO) instrument is the first space-borne hyperspectral spectrometer that measures backscattered sunlight over North America in a geostationary orbit. The two charge-coupled device (CCD) detectors of TEMPO, with spectral coverages of 293–494 and 538–741 nm and resolutions of 0.53–0.63 nm, are capable of identifying absorption features of key trace gases, including ozone, nitrogen dioxide, formaldehyde, and others. Using a step-and-stare scanning mechanism, the TEMPO instrument measures backscattered Earth radiance spectra hourly during the middle of the day (nominal scans) and every 40 minutes in the early morning and late afternoon (optimized scans) to effectively cover the sunlit portions of the continent, with scans during twilight when permitted by instrument safety constraints. Solar irradiance measurements are also conducted nominally with a weekly frequency. This article describes the Version 3 algorithm for TEMPO Level 1b data processing, which provides radiometrically and spectrally calibrated solar irradiance and Earth radiance spectra as the primary outputs. The processing includes the conversion of digitized Level-0 signals to radiance or irradiance, image navigation and registration for Earth spectra, and spectral calibration. This article also discusses calibration key data derived from pre-launch instrument characterization and in-flight calibration results.

Retrievals of ocean color (OC) properties from space are important for understanding the ocean ecosystem, the carbon cycle, and monitoring events such as harmful algal blooms (HABs). NASA’s recently launched Earth Venture Instrument (EVI), the geostationary Tropospheric Emissions: Monitoring of Pollution (TEMPO), provides a unique opportunity to examine diurnal variability in ocean ecology across coastal waters of North America and prepare for future hyperspectral geostationary OC missions. Although TEMPO does not match the spatial resolution or spectral coverage of planned coastal ocean sensors, such as NASA’s Geosynchronous Littoral Imaging and Monitoring Radiometer (GLIMR) or NOAA’s Geostationary Extended Observations Ocean Color Instrument (GeoXO OCX), it provides hourly observations at approximately 5\,km over U.S. coastal regions and the Great Lakes. Here, we apply a newly developed atmospheric correction approach based on principal component analysis combined with machine learning (ML) to retrieve OC properties using TEMPO’s hyperspectral measurements. Principal component coefficients derived from measured reflectances are used to train a neural network to estimate OC properties, including chlorophyll concentration, informed by collocated physically-based retrievals from MODIS, VIIRS, and OLCI. This ML-based approach complements traditional radiative transfer retrievals, particularly under challenging conditions such as glint and moderate cloud coverage. This approach demonstrates the value of near-real-time OC products, with significant potential for monitoring HABs and transient oceanic phenomena.

This Algorithm Theoretical Basis Document (ATBD) describes the retrieval algorithm and sensitivities of the Version 3 cloud product derived from the spectra collected by the Tropospheric Emissions: Monitoring of POllution (TEMPO) instrument. The cloud product is primarily produced for supporting the retrievals of TEMPO trace gases that are important for understanding atmospheric chemistry and monitoring air pollution. The TEMPO cloud algorithm is adapted from NASA's Ozone Monitoring Instrument (OMI) oxygen collision complex (O₂‐O₂) cloud algorithm. The retrieval generates effective cloud fraction (ECF) from the normalized radiance at 466 nm and generates cloud optical centroid pressure (OCP) using the O₂‐O₂ column amount derived from the spectral absorption feature near 477 nm. The slant column of O₂‐O₂ is retrieved using Smithsonian Astrophysical Observatory's spectral fitting code with optimized retrieval parameters. ECF and OCP are used by TEMPO trace gas retrievals to calculate Air Mass Factors which convert slant columns to vertical columns. The sensitivities of the cloud retrieval to various input parameters are investigated.