W. Paul Menzel’s research while affiliated with University of Wisconsin–Madison and other places

Plain Language Summary Hyperspectral infrared sounders onboard the geostationary orbital satellites enable viewing the three‐dimensional atmosphere frequently. China has such an instrument called Geostationary Interferometric Infrared Sounder onboard both Fengyun‐4A and Fengyun‐4B, Europe will have Infra‐Red Sounder (IRS) onboard MTG in the 2025/2026‐time frame, and U.S. is planning for the GeoXO sounder (GXS) in the next decade. Other countries like Japan, Korea, and India are also planning for geostationary hyperspectral IR sounder (GeoHIS) systems. IRS and GXS will have a spatial resolution of 4 km at nadir and a temporal resolution of 1 hr or better, helping scientists understand the Earth's atmosphere by monitoring changes of atmospheric temperature, moisture, and trace gases in detail. However, assuming that the atmosphere is homogeneous can lead to errors. Our study looks at how small, sub‐footprint atmospheric variations (or so‐called sub‐footprint atmospheric spatial inhomogeneity [SASI] effects) can change the measurements that these instruments make. Using numerical simulations with high resolution data, we found that these SASI effects can make a significant difference in the measurements, especially when looking at temperature and moisture in the atmosphere. This means that scientists need to consider these SASI effects to get more accurate determinations of atmospheric temperature, moisture, and trace gases from these GeoHIS instruments.

Short‐wave infrared (SWIR) radiances around the 4.3 μm CO2 absorption band from polar‐orbiting hyperspectral sounders provide useful thermodynamic information for numerical weather prediction (NWP) models. They are not assimilated in any of the operational NWP models because the Non‐Local Thermodynamic Equilibrium (NLTE) effects can increase the brightness temperature by more than 10 K. Directly assimilating NLTE‐affected SWIR radiances is challenging because of two reasons: (1) the radiative transfer model like the Community Radiative Transfer Model (CRTM) underestimates NLTE effects by 0.76 K from the old CRTM NLTE coefficients and by 0.46 K from the new CRTM NLTE coefficients, leading to day/night discrepancies in observation minus background (OMB) bias; and (2) CRTM does not simulate aurora‐related NLTE effects, which can happen during day and night. In this study, methodologies are developed to bias correct CRTM NLTE simulations to minimize the day/night discrepancies in OMB biases and to quality control SWIR radiances that cannot be well simulated by CRTM. The NLTE estimates from the Spectral Correlations to Estimate Non‐local Thermal Equilibrium (SCENTE) method — which exhibit better agreement between observations and background than those from CRTM simulation—were used as a reference to develop the linear regression‐based bias correction scheme. Extensive evaluations were carried out to understand the performance of the bias correction and the quality control schemes. Results showed that the schemes reduced day/night discrepancies in OMB bias to less than 0.1 K for different seasons and 0.14 K for different satellite zenith angles. These small discrepancies open the potential to assimilate daytime and nighttime SWIR radiances simultaneously. In addition, the quality control procedure is effective in screening out SWIR radiances affected by aurora‐related NLTE effects. A larger percentage of nighttime data were filtered out compared to daytime, underscoring the importance of addressing nighttime SWIR radiance assimilation. Lastly, the large OMB biases in high latitudes reported in previous studies are eliminated after the bias correction and quality control.

The next‐generation geostationary satellites are expected to have hyperspectral infrared (IR) sounders, providing hemispheric coverage of satellite‐derived vertical profiles of temperature, moisture, and wind in clear skies and above clouds. Derivation of winds, or atmospheric motion vectors (AMVs), from IR hyperspectral sounders was first demonstrated using Aqua Atmospheric Infrared Sounder retrievals. The AMVs on discrete pressure levels (3D winds) provided, for the first time, vertical profiles of wind information in the polar regions. Since then, the capability has been extended to tracking features in global profile retrievals of humidity and ozone derived from Cross‐track Infrared Sounder (CrIS) and Infrared Atmospheric Sounding Interferometer radiances. And, it is now demonstrated for the first time globally using retrievals at single field‐of‐view resolution from successive overpasses of three CrIS instruments on NOAA‐21, NOAA‐20, and SNPP flying in formation. 3D winds from polar‐orbiting satellites can provide all‐latitude (“global”) coverage giving insight into capabilities when all geostationary satellites are equipped with IR sounders.

Weather satellites not only provide atmospheric thermodynamic and hydrometric information, but also important dynamic information when high temporal data are used. Atmospheric motion vectors (AMVs) have been routinely derived from global geostationary satellite imagers over tropical and mid-latitude regions, and polar orbiting satellite imagers over high-latitude regions since the 1990s and have been widely used in numerical weather prediction (NWP). These AMVs result from tracking clouds and moisture primarily from the infrared and visible bands. While the coverage is good where there are clouds and moisture targets, AMVs can only provide winds for a few tropospheric layers and thus lack vertical information. Recently, active remote sensing technologies have been developed for vertical wind profiling from satellites. Those wind estimates have good accuracy but limited spatial coverage. Expanding wind estimates from two-dimensional (2D) to three-dimensional (3D) over expansive domains is important for improving nowcasting and NWP applications. Hyperspectral infrared sounder observations from polar orbiting satellites have been used for 3D wind exploration, but lack the temporal resolution needed for 3D winds over tropical and middle latitude regions. The feasibility of 3D winds using geostationary hyperspectral infrared sounders has also been demonstrated and validated using 15-minute Geostationary Interferometric Infrared Sounder observations. Tropospheric 3D winds will be better achieved through combining both active and passive observations in the future. This paper provides an overview on tracking features from satellites for obtaining tropospheric winds and the evolution from 2D to 3D coverage, along with their potential applications, challenges and future perspectives.

Monitoring and predicting highly localized weather events over a very short-term period, typically ranging from minutes to a few hours, are very important for decision makers and public action. Nowcasting these events usually re- lies on radar observations through monitoring and extrapolation. With advanced high-resolution imaging and sound- ing observations from weather satellites, nowcasting can be enhanced by combining radar, satellite, and other data, while quantitative applications of those data for nowcasting are advanced through using machine learning techniques. Those applications include monitoring the location, impact area, intensity, water vapor, atmospheric instability, pre- cipitation, physical properties, and optical properties of the severe storm at different stages (pre-convection, initiation, development, and decaying), identification of storm types (wind, snow, hail, etc.), and predicting the occurrence and evolution of the storm. Satellite observations can provide information on the environmental characteristics in the pre- convection stage and are very useful for situational awareness and storm warning. This paper provides an overview of recent progress on quantitative applications of satellite data in nowcasting and its challenges, and future perspectives are also addressed and discussed.

Multisensor satellite data fusion merges measurements or products from imaging and sounding instruments with different spatial, spectral, and temporal resolution to obtain more comprehensive information about key atmospheric variables and processes. Here, data from low Earth and geostationary orbits, such as the Joint Polar Satellite Systems and Geostationary Operational Environmental Satellites platforms, respectively, are integrated using spatial‐temporal fusion to enhance the detection of trace gas emissions from volcanoes. Not only does this yield trace gas information with improved spatial detail but, more importantly, the fusion product is also made available at significantly increased temporal resolution to help monitor the variable dispersion of trace gas emissions. The emission and dispersion of volcanic sulfur dioxide and ash plumes from the Cumbre Vieja volcano (Canary Islands, Spain) eruptions in October 2021 are studied through the synergistic exploitation of measurements and products from the Visible Infrared Imaging Radiometer Suite, the Cross‐track Infrared Sounder, the TROPOspheric Monitoring Instrument, and the Advanced Baseline Imager. Fusion results show increased spatial and temporal detail and describe evolution and directionality of the volcanic ash plumes; the potential benefits range from improved air quality monitoring to better guidance from aircraft safety systems.

A new version of the PATMOS-x multidecadal cloud record, version 6.0, has been produced and is available from the NOAA National Centers for Environmental Information. A description of the processes and methods used for generating the dataset are presented, with a focus on the differences between version 6.0 and the previous version of PATMOS-x, version 5.3. The new version appears both to be more stable, with less intersatellite variability, and to have more consistent polar cloud detection, phase distribution, and cloud-top height distribution when compared against the MODIS EOS record. Improvements in consistency and performance are attributed to the addition of multidimensional variables for cloud detection, constraining cloud retrievals to radiometric bands available throughout the record, and the addition of data from the HIRS instrument. Significance Statement The PATMOS-x project produces multidecadal cloudiness records from polar-orbiting satellites. Version 6.0 combines imager and sounder data from 15 satellites and shows significant improvements in accuracy and stability.

The synergistic use of data from advanced space-borne instruments of different designs onboard different satellite platforms with different orbital tracks provides advantages in various applications over the use of individual data sets alone. For example, high vertical resolution sounding profiles from advanced sounders like CrIS (Cross-track Infrared Sounder) in a low Earth orbit (LEO) and a high horizontal plus temporal resolution radiance measurements from geostationary (GEO) imagers like ABI (Advanced Baseline Imager) can be effectively combined to benefit severe weather monitoring, prediction, and warning systems. The spatial and temporal fusion approach allows LEO products, such as atmospheric moisture, to be created with increased spatial detail at every GEO measurement time, generating a GEO hyperspectral sounder-like perspective. To demonstrate the potential benefit of a GEO and LEO (i.e., ABI and CrIS) data fusion to real-time applications, time sequences of the moisture profile fusion results are presented in two case studies, namely a tornado outbreak in Nebraska on 5 May 2021 and a severe storm occurrence in Texas on 24 May 2022. The implications of the fusion results for nowcasting and warning operations via comparisons to numerical model forecasts and weather radar reflectivity data are discussed.

A hyperspectral infrared (IR) sounder from geostationary orbit provides nearly continuous measurements of atmospheric thermodynamic and dynamic information within a weather cube, specifically the atmospheric temperature, moisture, and wind information at different pressure levels that are critical for improving high impact weather (HIW) nowcasting and numerical weather prediction (NWP). Geostationary hyperspectral IR sounders (GeoHIS) have been onboard China’s Fengyun-4 series since 2016 and will be onboard Europe’s Meteosat Third Generation (MTG) series in the 2024 time frame; the U.S. and other countries are also planning to include GeoHIS instruments on their next generation of geostationary weather satellites. Although availability of on-orbit GeoHIS data are limited currently, studies have been conducted and progress has been made on developing the applications of high temporal resolution GeoHIS observations. These include but are not limited to deriving three-dimensional wind fields for nowcasting and NWP applications, trending atmospheric instability for warning in pre-convective environments, conducting impact studies with data from the experimental Geostationary Interferometric Infrared Sounder (GIIRS) onboard Fengyun-4A, preparing observing system simulation experiments (OSSEs), and monitoring diurnal variation of atmospheric composition. This paper provides an overview of the current applications of GeoHIS, discusses the data processing challenges, and provides perspectives on future development. The purpose is to provide direction on utilization of the current and assist preparation for the upcoming GeoHIS observations for nowcasting, NWP and other applications.