Large wildfires and their induced thunderstorms, pyrocumulonimbus (pyroCb), are getting increasing interest and attention. Most previous studies are based on broadband satellite data, and the use of hyperspectral infrared data for pyroCb detection has not been explored. Australia’s unprecedented fires at the end of 2019 to early 2020 induced an extreme pyroCb outbreak, and the largest event occurred on 30 December 2019 was successfully captured by the Cross-track Infrared Sounder (CrIS) onboard JPSS-1 and S-NPP. Analysis of these CrIS data demonstrated that the slopes and standard deviations of the spectral brightness temperature (BT), derived from a linear fitting to the spectrum in 800-980 cm-1, along with the split-window technique using selected CrIS channels, can aid in pyroCb detection. An inverted “V” feature in the spectra near 9.6 μm is associated with high pyroCb, and its depth, H_index, can provide information of cloud top height. These characteristics are verified through radiative transfer model (RTM) simulations and analysis of another case of pyroCb induced from California Creek fire on 5 September 2020. It is found that a combination of H_index and BT difference between 1231 and 677 cm-1is promising to distinguish high pyroCbs. A more accurate determination of pyroCb plume height can be achieved from the single Field of View Sounder Atmospheric Products (SiFSAP), which indicate that several pyroCb pixels reach 3-6 km above the tropopause. These approaches could be applied to study more pyroCbs using over 20 years of hyperspectral sounder data.

NASA’s Climate Absolute Radiance and Refractivity Observatory (CLARREO) Pathfinder (CPF) mission will deploy an Earth-observing reflected solar (RS) spectrometer, designed to measure Earth-reflected solar radiation from the International Space Station with a remarkable SI-traceable radiometric uncertainty of 0.3%-0.6% (k=1). The high-accuracy CPF measurements will provide an on-orbit reference for intercalibrating other spaceflight RS instruments. The CPF intercalibration team will showcase an innovative on-orbit intercalibration approach, wherein two other RS sensors—the shortwave (SW) channel of the Clouds and the Earth’s Radiant Energy System (CERES) and the Reflective Solar Bands (RSB) of the Visible Infrared Imager Radiometer Suite (VIIRS)—are intercalibrated against CPF benchmark measurements, with an unprecedented intercalibration methodology uncertainty of 0.3% (k=1).

Different retrieval algorithms have been developed to process top-of-atmosphere (TOA) spectral radiance data provided by hyperspectral infrared sounder missions. Those algorithms are either optimal estimation method (OEM) based schemes with radiative transfer calculation involved in the retrieval process, or machine learning based methods that allow ultra-efficient data procession but lack of radiometric consistency validation based on the directly measured information. Combining both approaches leverages their respective technical advantages, leading to more accurate results. This study introduces a hyperspectral sounder fingerprinting algorithm to explore this hybrid approach. This approach involves the use of a spectral information-based classification method to identify an reference geophysical state and the corresponding radiative kernel. This enables the efficient retrieval of geophysical variables of interest through a radiative kernel-based linear inversion procedure. The fingerprinting method has been applied to analyze a decadelong hyperspectral sounder data record.

The Hunga Tonga-Hunga Ha'apai volcanic eruption, with the largest eruption occurring on 15 January 2022, ejected unprecedented amounts of water vapor (H2O) and SO2into the stratosphere. Using the hyperspectral infrared sounder CrIS on S-NPP and JPSS-1 (also NOAA-20), we present some unique features of the spectral near 9.6 μm and its great potential value for detecting plumes or clouds with tops near or above tropopause. We identified the existence of two umbrella clouds and observed the continued westward propagation of the upper plume even 8-9 hours after the eruption onset, as well as its dissipation from two CrIS observations onboard JPSS-1 and S-NPP taken in 50 minutes apart. Using a new Single Field-of-view Sounder Atmospheric Products (SiFSAP) from CrIS and ATMS on JPSS-1, which has a high spatial resolution of about 14 km, this study analyzes the impact of Hunga Tonga eruption on the distribution of temperature, H2O and ozone near the tropopause. These results demonstrate the value of hyperspectral infrared sounder and its single-field-view retrieval products for monitoring the volcanic eruptions and their impact on the lower stratosphere.

The Climate Absolute Radiance and Refractivity (CLARREO) Pathfinder (CPF) mission will take Système Internationale (SI)-traceable spectral reflectance measurements of Earth at an unprecedented accuracy of 0.3% (k=1). CPF will also take measurements to support intercalibration of other satellite-based sensors. To achieve the desired intercalibration methodology uncertainty of 0.3% (k=1), the CPF intercalibration measurements need to closely match those from target sensors in time, space, angles, and wavelength. This paper introduces an innovative angular correction method to significantly reduce errors due to angular mismatches between CPF and target sensor measurements. The method leverages the spectral correlations among the reflected solar radiances from the same surface target at two adjacent angles. Our studies have shown that the spectral radiance or reflectance difference measured at angles slightly deviating from the CPF observation angles can be accurately predicted based on the hyperspectral CPF measurements. The method will serve as part of the operational algorithms to support the core mission goal of conducting intercalibration analysis with measurements from the shortwave channel of the Clouds and the Earth’s Radiance Energy System (CERES) and the reflective solar bands of the Visible Infrared Imaging Radiometer Suite (VIIRS); however, it can also be extended for other reference-target intercalibration applications.

The Single Field-of-view Sounder Atmospheric Products (SiFSAP) answer the need for a novel high spatial resolution atmospheric data product for major hyper-spectral infrared (IR) sounder missions. SiFSAP include a complete set of atmospheric vertical profiles, cloud, and surface properties, which are physically retrieved from top-of-atmosphere (TOA) spectral radiances under all-sky conditions via a rigorously defined radiative transfer relationship. By using a state-of-art fast radiative transfer model and a carefully designed optimal estimation based physical retrieval scheme, the SiFSAP algorithm ensures both an ultra-fast data processing speed needed for operational weather applications and the radiometric consistency desired by long-term climate studies. SiFSAP supplement existing operational products by providing data at the native spatial resolution of the sounder instruments, the direct and accurate retrieval of cloud scattering properties, and the establishment of ‘radiance closure’.

The Single Field-of-view Sounder Atmospheric Products (SiFSAP), including ozone (0 3 ) and carbon monoxide (CO), from CrIS on SNPP have a spatial resolution of about 14 km at nadir. Such high-resolution sounder products enable us to make process-oriented analysis of CO emission and transport from large wildfires as well as the 0 3 production along the transport of fire plumes. An analysis of SiFSAP CO from Australia's unprecedented wildfires in the end of 2019 to early 2020, as well as comparison with satellite products from TROPOMI and MOPPIT and MERRA-2 reanalysis products, demonstrate an overall good agreement of CO observations among these space-borne sensors. This study also demonstrates the advantage of the SiFSAP CO in capturing the feature of CO transport and 0 3 production from wildfires, which will benefit air quality study.

The Single Field of View (SFOV) retrieval products from CrIS on SNPP have a spatial resolution of ∼ 0.15 by 0.15 degree. Such high resolution observations of the thermodynamic state of atmosphere may provide a very useful dataset to monitor the extreme weather events and strong dynamic transport process. This study compared the SFOV-retrieved temperature and water vapor with ERA5 reanalysis data for one polar vortex breakup case and one stratospheric intrusion event. The results show a good agreement between them in matching the large scale patterns but with some differences in the finer scale features. Comparison of the corresponding SFOV ozone with OMPS measurements demonstrated that the enhancement of ozone can be used to map the air transport. This study suggests that the SFOV sounding products may have a great value to help analyze the mechanism of dynamics, model diagnosis and weather forecasting.

CLARREO Pathfinder is a hyperspectral instrument designed to resolve reflectance of solar radiation from Earth in the wavelength range of 350 nm to 2300 nm with an uncertainty of 0.3% ( k=2) or less. Its success will demonstrate CLARREO's ability to provide on-orbit SI-Traceable calibration of measured spectral reflectance with an advanced accuracy. The CLARREO pathfinder simulator has been developed to generate high-fidelity inter-calibration event data products that can be used for pre-launch inter-calibration algorithm study. A high-fidelity simulation for CLARREO inter-calibration events includes computationally intensive radiative transfer calculations for observations within each individual collocation footprint. A principal component based radiative transfer model is incorporated in the simulator to enable an ultra-fast forward simulation, ensuring a low-latency data processing for month-to year-long intercalibration events. This paper introduces the design and development of the CLARREO pathfinder simulator and some of its applications for inter-calibration matching error evaluation.

A physical retrieval system is developed for all sky single field-of-view (FOV) hyperspectral sounding. This system can be used to retrieve atmospheric temperature, moisture, and trace gas profiles, along with cloud height and cloud microphysical properties simultaneously from single FOV radiances measured by hyperspectral sounders. Single FOV retrieval results allow the users to extract horizontal gradient information with a spatial resolution defined by the size of one FOV. Moreover, the system finds solutions by directly fitting observed spectral radiances and therefore can be used to obtain radiative kernels that fulfill the `radiance closure' needed for climate applications. As a comparison, current operational retrieval algorithms find solutions by fitting the `cloud cleared' radiances generated from several adjacent FOVs. Not only the spatial resolution of those results is several times coarser than that defined by a single FOV, but the results cannot be used to build radiometric consistent radiative kernels under cloudy sky conditions. In this paper, some applications of the system are demonstrated to highlight the benefit of the full spatial resolution retrieval and the capability of building radiometric consistent radiative kernels under all sky conditions.

This paper applies a physical inversion approach to retrieve geophysical properties from the single instrumental field-of-view (FOV) spectral radiances measured by the Infrared Atmospheric Sounding Interferometer (IASI) under all-sky conditions. We demonstrate the use of a principal-component-based radiative transfer model (PCRTM) and a physical inversion methodology to simultaneously retrieve cloud radiative and microphysical properties along with atmospheric thermodynamic parameters. By using a fast parameterization scheme, the PCRTM can include the cloud scattering properties simulation in radiative transfer calculations without incurring much more computational cost. The computational speed achieved for a single FOV forward simulation under cloudy skies is similar to that normally achieved for clear skies. The retrieval algorithm introduced herein adopts a novel cloud phase determination scheme, to stabilize and/or constrain retrieval iterations, based on characteristics of the reflectance and transmittance of ice and water clouds. A modified Gaussian-Newton minimization technique is employed in the iterative inversion process in order to overcome a highly nonlinear cost function introduced by the cloud parameters. We carry out a rigorous error analysis for the retrieval of temperature, moisture, ozone (O3), and carbon monoxide (CO) from IASI measurements under cloudy-sky conditions. Our algorithm is applied to real IASI observations. Retrieval results are validated using European Center for Medium-Range Weather Forecasting data and collocated Lidar/Radar measurements, and the dependence of retrieval accuracy on cloud optical depth is illustrated.