Wildfires emit volatile organic compounds (VOCs) that contribute to ozone and aerosol pollution. Quantification is challenged by the diversity of emitted species and by their complex dependence on fire characteristics, with scarce field observations available for model evaluation. Remote sensing in the thermal infrared (IR) is a powerful tool for detecting fire VOCs: many compounds exhibit distinct signatures at these wavelengths, and measurements are unaffected by fine aerosols prevalent in smoke. Here, we develop the first thermal IR VOC measurements from an aircraft-based platform, using radiance observations from the Scanning High-resolution Interferometer Sounder (S-HIS) deployed aboard the NASA ER-2 during the 2019 FIREX-AQ campaign. We focus on methanol and ethene, and employ a neural network retrieval adapted from Cross-track Infrared Sounder (CrIS) algorithms. The S-HIS retrievals achieved high precision (R-2 = 0.95-0.99) and accuracy (median absolute bias <5.5 & times; 10(15) molec./cm(2)) versus the full training data set. However, at low-to-moderate concentrations, retrieval performance is degraded by instrument noise. When considering scenes below the median methanol signal encountered during FIREX-AQ, 30-fold aggregation is needed to achieve R-2 = 0.8, and no amount of aggregation yields the performance that would be achievable for a single pixel with the 10 & times; lower noise of CrIS. The S-HIS VOC observations exhibit clear enhancements over and downwind of fires that align with those seen by CrIS. Our results provide a foundation for future aircraft-based VOC measurements in the thermal IR, and emphasize the critical importance of instrument noise for the design of future airborne and spaceborne sounders.

The Cross-track Infrared Sounder (CrIS) is an infrared Fourier Transform Spectrometer onboard the Suomi-NPP (SNPP), JPSS-1, and JPSS-2 satellites. The CrIS instrument was designed to provide an optimum combination of optical performance, high radiometric accuracy, and compact packaging. While CrIS was developed primarily as a temperature and water vapor profiling instrument for weather forecasting, its high accuracy and extensive information about trace gases, clouds, dust, and surface properties make it a powerful tool for climate applications.The goal of the NASA CrIS Level 1B project is to support NASA climate research by providing a climate quality Level 1B (geolocation and calibration) algorithm and create long-term measurement records for the CrIS instruments currently on-orbit on the SNPP, JPSS-1, and JPSS-2 satellites, and for those to be launched on JPSS-3 and JPSS-4. The long-term objectives of the project include:Create well-documented and transparent software that produces climate quality CrIS Level 1B data to continue or improve on EOS-like data records, and to provide this software and associated documentation to the NASA Sounder Science Investigator-led Processing System (SIPS). Provide long-term monitoring and validation of the CrIS Level 1B data record from SNPP and JPSS-1 through JPSS-4, and long-term maintenance and refinement of the Level 1B software to enable full mission reprocessing as often as needed. Provide a homogeneous radiance product across all CrIS sensors through the end of the CrIS series lifetime, with rigorous radiance uncertainty estimates. Develop and support of the CrIS/VIIRS IMG software and datasets, which provide a subset of Visible Infrared Imaging Radiometer Suite (VIIRS) products that are co-located to the CrIS footprints. Develop and support of the Climate Hyperspectral Infrared Product (CHIRP) for the AIRS and CrIS sounders. The CHIRP product converts the parent instrument's radiances to a common Spectral Response Function (SRF) and removes inter-satellite biases, providing a consistent inter-satellite radiance record. The NASA CrIS products are available via the NASA Goddard Earth Sciences (GES) Data and Information Services Center (DISC) at https://www.earthdata.nasa.gov/sensors/cris. This presentation will include (1) an overview of the NASA Level 1B calibration algorithm and product, (2) example post-launch calibration/validation results demonstrating the accuracy and stability of the CrIS Level 1B data, and (3) example science results.

The Cross-track Infrared Sounder (CrIS) is an infrared Fourier Transform Spectrometer onboard the Suomi-NPP (SNPP), JPSS-1, and JPSS-2 satellites. The CrIS instrument was designed to provide an optimum combination of optical performance, high radiometric accuracy, and compact packaging. While CrIS was developed primarily as a temperature and water vapor profiling instrument for weather forecasting, its high accuracy and extensive information about trace gases, clouds, dust, and surface properties make it a powerful tool for climate applications.The goal of the NASA CrIS Level 1B project is to support NASA climate research by providing a climate quality Level 1B (geolocation and calibration) algorithm and create long-term measurement records for the CrIS instruments currently on-orbit on the SNPP, JPSS-1, and JPSS-2 satellites, and for those to be launched on JPSS-3 and JPSS-4. The long-term objectives of the project include:Create well-documented and transparent software that produces climate quality CrIS Level 1B data to continue or improve on EOS-like data records, and to provide this software and associated documentation to the NASA Sounder Science Investigator-led Processing System (SIPS). Provide long-term monitoring and validation of the CrIS Level 1B data record from SNPP and JPSS-1 through JPSS-4, and long-term maintenance and refinement of the Level 1B software to enable full mission reprocessing as often as needed. Provide a homogeneous radiance product across all CrIS sensors through the end of the CrIS series lifetime, with rigorous radiance uncertainty estimates. Develop and support of the CrIS/VIIRS IMG software and datasets, which provide a subset of Visible Infrared Imaging Radiometer Suite (VIIRS) products that are co-located to the CrIS footprints. Develop and support of the Climate Hyperspectral Infrared Product (CHIRP) for the AIRS and CrIS sounders. The CHIRP product converts the parent instrument's radiances to a common Spectral Response Function (SRF) and removes inter-satellite biases, providing a consistent inter-satellite radiance record. The NASA CrIS products are available via the NASA Goddard Earth Sciences (GES) Data and Information Services Center (DISC) at https://www.earthdata.nasa.gov/sensors/cris. This presentation will include (1) an overview of the NASA Level 1B calibration algorithm and product, (2) example post-launch calibration/validation results demonstrating the accuracy and stability of the CrIS Level 1B data, and (3) example science results.

Presented is a methodology to explicitly identify and account for cloud-free satellite measurements below a sensor's measurement detection level. These low signals can often be found in satellite observations of minor atmospheric species with weak spectral signals (e.g., ammonia (NH3)). Not accounting for these non-detects can high-bias averaged measurements in locations that exhibit conditions below the detection limit of the sensor. The approach taken here is to utilize the information content from the satellite signal to explicitly identify non-detects and then account for them with a consistent approach. The methodology is applied to the CrIS Fast Physical Retrieval (CFPR) ammonia product and results in a more realistic averaged dataset under conditions where there are a significant number of non-detects. These results show that in larger emission source regions (i.e., surface values > 7.5 ppbv) the non-detects occur less than 5% of the time and have a relatively small impact (decreases by less than 5%) on the gridded averaged values (e.g., annual ammonia source regions). However, in regions that have low ammonia concentration amounts (i.e., surface values < 1 ppbv) the fraction of non-detects can be greater than 70%, and accounting for these values can decrease annual gridded averaged values by over 50% and make the distributions closer to what is expected based on surface station observations.

This paper provides a procedure for the simulation of radiances from the U. S. National Oceanic and Atmospheric Administration (NOAA) Cross-track Infrared Sounder (CrIS) Fourier Transform Spectrometer to include spectral ringing effects caused by the finite-band, non-flat instrument spectral response to incident radiation. A simulation using a line-by-line radiative transfer model is performed to illustrate the magnitude of the effect and to indicate which spectral channels are likely to be impacted. Comparisons with CrIS observations are made to show that for most channels this effect is negligibly small compared to errors in the radiative transfer calculations but for the longwave edge of the CrIS longwave band and a few other regions, the brightness temperature ringing is significant. While the ringing artifact described in this paper may appear to be removed when Hamming apodization is applied, as is done for the assimilation of CrIS data into Numerical Weather Prediction (NWP) models, it is still present, and its influence reappears if the spectral correlation induced by apodization is properly handled to preserve the information content that derives from high spectral resolution. Inclusion of the instrument responsivity in calculated spectra to properly mimic the observed spectra as defined here eliminates artifacts from this type of ringing. Users of CrIS radiances should consider whether this effect is important for their application.

High spectral resolution infrared sounders are an integral component of the global observing system and are used in a broad range of applications. This is enabled by their high accuracies which are ensured by rigorous calibration/validation activities. One of these activities is the post‐launch intercomparison with other high spectral resolution infrared sounders using simultaneous nadir overpasses (SNOs). This paper introduces a novel application of the previously developed SNO methodology by including time difference histogram symmetrization and a spatial sampling uncertainty. Where possible, radiometric measurement uncertainties are included and propagated through the statistics. Comparisons of Atmospheric Infrared Sounder (AIRS), METOP‐A/B/C Infrared Atmospheric Sounding Interferometer (IASI), and Cross‐track Infrared Sounder (CrIS) from 1 October 2019, to 1 October 2020, are analyzed. Results show AIRS and IASI differences as well as CrIS and AIRS differences are generally less than 0.4 K across the spectrum, and CrIS and IASI differences are generally less than 0.25 K. Comparison of the Suomi National Polar‐Orbiting Partnership and NOAA‐20 CrIS instruments via IASI and AIRS shows differences are generally less than 0.1 K across all bands and that the two CrIS instruments statistically agree within their radiometric uncertainties except for the narrow 2,370 cm −1 region where artifacts due to brightness temperature conversion are prone to occur.

The potential for high accuracy of airborne sensors, combined with the ability to perform pre- and post-campaign calibration tests to confirm the radiometric performance and update traceability to absolute standards, makes satellite under-flight comparisons uniquely capable among existing approaches for assessing the accuracy of infrared satellite observations. The Scanning High-resolution Interferometer Sounder (S-HIS) has proven to be an extremely valuable tool for airborne calibration validation of on-orbit infrared sensors and has demonstrated robust performance, high calibration accuracy, and traceability to NIST standards. An introduction to high-altitude airborne radiometric calibration-validation, an overview of the S-HIS instrument, and results for radiometric validation of the Cross-track Infrared Sounder and the Advanced Baseline Imager with the S-HIS are presented in this chapter.

The Cross-track Infrared Sounder (CrIS) is an infrared Fourier-transform spectrometer that measures the Earth’s infrared radiance at high spectral resolution and high accuracy. The potential for polarization errors contributing significantly to the radiometric uncertainty of infrared remote sounders has been well recognized and documented, particularly due to polarization-dependent scene select mirrors operated in conjunction with grating-based instruments. The issue is equally applicable to FTS-based sensors. While the CrIS sensor utilizes an unprotected gold scene select mirror which has extremely low polarization in the infrared and the angle of incidence at the mirror is maintained for all calibration and Earth scene views, the radiometric bias due to polarization effects was determined to be non-negligible for cold scenes. A model for the polarization-induced calibration bias and the associated correction is presented for the CrIS instrument, along with details of the model parameter determination, and the impact of the correction on the calibrated radiances for a range of scene temperatures and types.

Today's state-of-the-art infrared hyperspectral sounders in Low Earth Orbit have demonstrated very high performance in several basic, but very critical, performance characteristics. Because of this, and the high information content of the infrared hyperspectral radiance spectra, the data has proven valuable for a range of applications including 1) radiance data assimilation for medium range numerical weather forecasting, 2) atmospheric soundings for various meteorological applications, 3) trace gases studies, 4) reference inter-calibration, and 5) climate process studies and radiance trending. Following previous work [1], this paper will discuss the desirable baseline characteristics of the next generation of the US infrared hyperspectral sounder, envisioned to continue the hyperspectral data record after the JPSS series ends in the late 2030s, in order to maintain very high value and return on investment, and even improve the quality of the available data over the current generation.

The Suomi National Polar-orbiting Partnership (SNPP) cross-track infrared sounder (CrIS) has provided critical observations for environmental applications for nearly ten years. However, on 26 March 2019, the Joint Polar Satellite System (JPSS) interface data processing segment (IDPS) stopped producing the operational SNPP CrIS sensor data record (SDR) product due to a failure of the midwave infrared (MWIR) band. Following a comprehensive risk assessment, the switch from primary Side-1 to redundant Side-2 electronics was made on 24 June 2019, successfully recovering the full capabilities of the sensor. Comprehensive assessment results demonstrate the high quality of the CrIS SDR product resulting from the sensor recalibration, thus meeting the JPSS Level-1 requirements with margin. The spectral calibration prioritized consistency with the CrIS SDR product prior to the side switch to minimize the impact on users. The results show that the radiometric impact on the CrIS SDR product resulting from the side switch is not significant and is within the calibration radiometric uncertainty. It is demonstrated that after instrument restoration, the SNPP CrIS SDR product recovers the quality needed to be used as radiometric reference for calibration and validation of infrared remote sensing instruments. The recovery of the SNPP CrIS MWIR band is expected to support improvements in numerical weather forecasting by restoring the MWIR band channels sensitive to tropospheric water vapor. This should also help maintain continuity and redundancy of one of the backbone observations of the global observing system.

The Cross-track Infrared Sounder (CrIS) is a Michelson-type Fourier Transform Spectrometer. The CrIS flight module 2 instrument was launched into orbit on November 18, 2017, onboard the NOAA-20 satellite as part of the United States (US) Joint Polar Satellite System (JPSS). The CrIS instrument measures the top-of-atmosphere upwelling spectral radiance in the thermal infrared (IR) spectrum. These measurements provide critical information for medium-range weather forecasting, and the retrieval of atmospheric profiles of temperature, water vapor, and other trace gases. The instrument noise equivalent radiance differential (NEdN) estimates are used by the weather forecasting systems, the trace gas atmospheric retrieval algorithms, and for trending the health and stability of the instrument over time. The current operational NEdN estimate is calculated using instrument observations from the deep space (DS) view and the internal calibration target (ICT). Two alternative methodologies are described here based on the principal component analysis (PCA) of an ensemble of calibrated Earth scene (ES) spectra. The NEdN calculation methods show that the instrument meets the specifications with a margin for all 27 detectors with an exception of one midwave IR (MWIR) field-of-view (FOV) 9, which is borderline. The PCA analysis shows that warmer ES spectra have higher noise, known as scene shot, for the short-wave IR (SWIR) band. Using the PCA analysis, the NEdN for the long-wave IR FOV 5 is 30% higher than the NEdN calculated by the operational algorithm. Correlated noise is also found due to the effect of the instrument self-apodization correction.

other ARM data, an assessment of the radiosonde data quality was performed and post-processing corrections applied producing an ARM site Best Estimate (BE) product. The SNPP targeted radiosondes were integrated into the NOAA Products Validation System (NPROVS+) system, which collocated the radiosondes with satellite products (NOAA, National Aeronautics and Space Administration [NASA], European Organisation for the Exploitation of Meteorological Satellites [EUMETSAT], Geostationary Operational Environmental Satellite [GOES], Constellation Observing System for Meteorology, Ionosphere, and Climate [COSMIC]) and Numerical Weather Prediction (NWP forecasts for use in product assessment and algorithm development. This work was a fundamental, integral, and cost-effective part of the SNPP validation effort and provided critical accuracy assessments of the SNPP temperature and water vapor soundings.

Since early 2012, the cross-track infrared sounder (CrIS) on board the Suomi National Polar-orbiting Partnership (S-NPP) satellite has continually provided the hyperspectral infrared observations for profiling atmospheric temperature, moisture, and greenhouse gases. In this study, the CrIS sensor data record (SDR) data are improved for climate applications with its fine-tuning of calibration coefficients in an NOAA reprocessing project. A specific software system was developed to reprocess the CrIS SDR. This software system was updated with a new calibration algorithm, nonlinearity, and geolocation to improve the SDR data quality and long-term consistency. The calibration coefficients are refined with the latest updates, which were used to calibrate the latest operational SDR products and replace those in the engineering packet (EP) in the raw data record (RDR) data stream. The resampling wavelength was updated based on the metrology laser wavelength and resulted in zero sampling error in the spectral calibration. All the historical SDRs (from February 2012 to March 2017) were generated with the same calibration coefficients and same version of the processing software system, resulting in improved accuracy and stability in terms of spectral and radiometric calibration during the CrIS lifetime mission. The quality of the reprocessed CrIS SDR data at nominal spectral resolution (NSR) is assessed in terms of its radiometric and spectral calibration. Comparisons against the operational SDR data are carried out to demonstrate the improved long-term stability of the reprocessed CrIS SDR data. Overall radiometric biases are found to be small and highly stable over the instrument mission, the FOV-to-FOV differences are less than ~10 mK, and much better than that from the operational SDR data. It is shown that the CrIS metrology laser wavelength varies within 4 ppm as measured by the neon calibration system. The reprocessed SDR data have spectral errors less than 0.5 ppm, which is much better than the operational SDR data with about 4 ppm. This baseline version of the reprocessed SNPP CrIS SDR data is suitable for long-term climate monitoring and model assessments and can provide an infrared reference observation to assess other narrow- or broadband infrared instruments’ calibration accuracy.

A summary of the Scanning High-resolution Interferometer Sounder (S-HIS) observations from the FIREX-AQ (Fire Influence on Regional to Global Environments and Air Quality) field campaign is presented.

Satellite vertical atmospheric sounding was initiated more than 50 years ago and has evolved to provide the most critical component of today's global observation system. However, the operational use of today's polar orbiting satellite hyperspectral infrared (IR) observations in numerical weather prediction (NWP) has been limited to a small fraction of the radiance information being provided. On the other hand, research systems are in operation that combines high vertical resolution polar hyperspectral radiance measurements with high spatial and time resolution geostationary multispectral radiance measurements that demonstrate the promise of future geo-hyperspectral sounding observations to significantly improve the forecast location and warning time for the development of localized tornadic storms. This article has a twofold objective: 1) to demonstrate that there is much more information available in current IR sounding data, than is being used to benefit the current NWP operation and 2) to illustrate the importance of the spectrometer technology (i.e., Fourier transform vs. dispersive grating) used for achieving the vertical profile resolution required to improve both extended range and localized severe weather forecasts. These objectives are achieved by performing both theoretical physics-based radiance information content (IC) studies and empirical analyses of current hyperspectral radiance measurements. The IC studies clearly demonstrate the unique importance of longwave IR (9−15 μm) radiance observations. The empirical studies demonstrate the importance of using Fourier transform spectrometers for providing the high spectral fidelity needed to resolve the small-scale vertical features in atmospheric temperature and moisture profiles, which impact weather forecast accuracy.

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.

The Absolute Radiance Interferometer (ARI) is an infrared spectrometer designed to serve as an on-orbit radiometric reference with the ultra-high accuracy (better than 0.1 K 3‑σ or k = 3 brightness temperature at scene brightness temperature) needed to optimize measurement of the long-term changes of Earth’s atmosphere and surface. If flown in an orbit that frequently crosses sun-synchronous orbits, ARI could be used to inter-calibrate the international fleet of infrared (IR) hyperspectral sounders to similar measurement accuracy, thereby establishing an observing system capable of achieving sampling biases on high-information-content spectral radiance products that are also < 0.1 K 3‑σ. It has been shown that such a climate observing system with <0.1 K 2‑σ overall accuracy would make it possible to realize times to detect subtle trends of temperature and water vapor distributions that closely match those of an ideal system, given the limit set by the natural variability of the atmosphere. This paper presents the ARI sensor's overall design, the new technologies developed to allow on-orbit verification and test of its accuracy, and the laboratory results that demonstrate its capability. In addition, we describe the techniques and uncertainty estimates for transferring ARI accuracy to operational sounders, providing economical global coverage. Societal challenges posed by climate change suggest that a Pathfinder ARI should be deployed as soon as possible.

To reduce societal impacts from severe weather, the USA should expeditiously implement a Hyperspectral Imaging Infrared Sounder (HIIS) in Geostationary (GEO) orbit. Observations from a GEO HIIS would contain unique information that is crucial for giving the populace more time to react to ensuing severe weather, a key lifesaving capability for a Weather Ready Nation. The GEO HIIS will provide frequent hyperspectral infrared radiance observations for understanding storm scale atmospheric processes and improving weather hazard predictions. These observations will provide the unique ability to detect rapid changes in atmospheric stability and the moisture flux convergence that serves both as a triggering mechanism for initial storm development and a fuel source for continued storm growth.

The Global Space-based Inter-Calibration System (GSICS) routinely monitors the calibration of various channels of Earth-observing satellite instruments and generates GSICS Corrections, which are functions that can be applied to tie them to reference instruments. For the infrared channels of geostationary imagers GSICS algorithms are based on comparisons of collocated observations with hyperspectral reference instruments; whereas Pseudo Invariant Calibration Targets are currently used to compare the counterpart channels in the reflected solar band to multispectral reference sensors. This paper discusses how GSICS products derived from both approaches can be tied to an absolute scale using specialized satellite reference instruments with SI-traceable calibration on orbit. This would provide resilience against gaps between reference instruments and drifts in their calibration outside their overlap period and allow construction of robust and harmonized data records from multiple satellite sources to build Fundamental Climate Data Records, as well as more uniform environmental retrievals in both space and time, thus improving inter-operability.