Abstract Current geostationary satellite imaging instruments such as the Advanced Baseline Imager (ABI) show poor skill in resolving low‐level moisture features. Adding radiance information from low‐earth‐orbiting hyperspectral sounders, such as the Cross‐track Infrared Sounder (CrIS), of five online water vapor rotational channels in the infrared (IR) window along with adjacent offline channels move the low‐level temperature and humidity retrievals, derived from ABI data, closer to those possible with a full capability geostationary hyperspectral sounder. These 10 online and offline CrIS channels have differing absorption strengths and weighting functions that suggest sensitivity to moisture changes near the surface between 900 and 700 hPa. This study offers a partial look into the enhanced capability of the next‐generation geostationary satellites with hyperspectral IR sounders onboard, providing detailed vertical profiles of temperature and moisture to benefit a variety of applications like weather monitoring and nowcasting operations.

This paper provides a history of salient points of the evolution of the European geostationary satellite programme Meteosat from its inception in the early 1970s until the end of satellite operations at the European Space Operations Centre (ESOC) of ESA (European Space Agency). This happened in 1995 when the Meteosat operations were handed over to EUMETSAT. Specific to this paper is that key technical aspects of the operational Meteosat suite are described. Also recalled are scientific achievements in image processing, real-time calibration, and for operational products. We also recall some stories around the water vapour (WV) channel which Meteosat First Generation was the first geostationary meteorological satellite to feature. Examples of international cooperation are given which advanced the use of Meteosat data. Overall, achievements with the first Meteosat generation laid the foundation for the successful operational European Meteosat programmes which have recently entered into their third generation.Foreword: Readers may ask what is unique about this paper? This paper goes beyond telling the Meteosat history by recalling high-level decisions taken by delegate bodies of member states. The authors describe technical and scientific aspects which led to the ‘sought-after’ quantitative utilisation of the early Meteosat satellites. The group of authors covers relevant perspectives because of their in-depth involvement during the time covered by this paper. The authors had the following positions: Johannes (Han) de Waard was the Head of the Meteosat Exploitation Project (MEP) at ESOC; Tillmann Mohr was Head of the German delegation for the Meteosat Programme at ESA, Chairman of the Programme Board Operational Meteosat (1983–1986) and Chair of the Policy Advisory Committee of EUMETSAT; later in 1995, he became the second Director-General of EUMETSAT; Frank Diekmann was the image engineer in MEP at ESOC; Paul Menzel was a senior scientist at NOAA NESDIS and an important counterpart for the cooperation with NOAA; Johannes Schmetz was at that time Senior Scientist in MEP at ESA/ESOC.

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.

Short‐wave infrared (SWIR) radiances around the 4.3 μm CO 2 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.

Weather satellites provide not only 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 midlatitude 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 midlatitude regions. The feasibility of 3D winds using geostationary hyperspectral infrared sounders has also been demonstrated and validated using 15-min 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 relies on radar observations through monitoring and extrapolation. With advanced high-resolution imaging and sounding 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, precipitation, 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 preconvection 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.

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.

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.

Radiance measurements from a geostationary hyperspectral infrared sounder (GeoHIS) with high temporal resolution not only provide a continuous weather cube of atmospheric temperature and moisture information at different pressure levels, but also enable derivation of three‐dimensional (3D) horizontal winds by tracking atmospheric water vapor features. However, GeoHIS radiances are influenced by sub‐footprint cloudiness, which needs to be considered in tracking the moisture features for deriving the atmospheric wind fields. By combining the collocated high spatial resolution cloud information from an imager onboard the same platform, the 3D horizontal wind retrievals can be improved, and the influence of sub‐footprint cloudiness on winds can be quantified for better applications. Using data from the Advanced Geostationary Radiation Imager (AGRI) and Geostationary Interferometric Infrared Sounder onboard the same experimental geostationary satellite Fengyun‐4A, it is found that 3D horizontal wind retrievals can be derived under both clear and partially clear skies with reasonable accuracy. Sub‐footprint cloud information provides noticeable improvement in wind retrievals; higher/lower clouds have more/less influence while thicker/thinner clouds have more/less influence, respectively, on the wind product. The sub‐footprint cloudiness (cloud‐top pressure and cloud coverage) provides a good indication of the quality flag for quantitative applications of the 3D horizontal wind product.

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 on board China's Fengyun-4 series since 2016 and will be on board Europe's Meteosat Third Generation (MTG) series in the 2024 time frame; the United States 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 preconvective environments, conducting impact studies with data from the experimental Geostationary Interferometric Infrared Sounder (GIIRS) on board 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.

Cloud base height (CBH) is an important parameter to describe cloud state and is highly related to the vertical motions in the atmosphere. CBH information is critical for both aviation safety and synoptic analysis. In this study, daytime CBH is estimated directly from Geostationary Operational Environmental Satellite-R Series (GOES-16) Advanced Baseline Imager (ABI) level lb data and the European Centre for Medium-Range Weather Forecasts' (ECMWF) fifth generation reanalysis (ERAS) data using the Gradient Boosted Regression Trees (GBRT) machine learning technique. The CBH estimate algorithm, which is named as GETCBH, covers the same areal extent as the full disk of the ABI/GOES-16 and only for single-layer clouds. The 2-years of CBH measurements from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) aboard Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) satellite is used as the label (which is the true value/class of the model output for regression/classification problem in machine learning terminology). A quality flag algorithm using another machine learning technique, the Gradient Boosted Decision Trees machine learning technique is developed to provide a confidence level for the CBH estimate. The evaluations show an overall root mean square error (RMSE) of 1.87 km and Pearson's correlation coefficient (Pearson's r) of 0.92 before any quality control. After excluding CBH estimates with low confidence (19.2% of all samples), the RMSE is reduced to 1.14 km, Pearson's r increases to 0.97, and 96% of the estimates are within 2 km of the CALIOP results. By analyzing model bias and feature importance, cloud phase information has the biggest impact on the CBH estimate, although all input features have positive impact on the estimate accuracy. Limited by the penetrability of CALIOP, GETCBH is valid for clouds with COD < 8.5. The CBH estimates have reduced accuracy (Pearson's r of 0.88) for optically thin clouds (clouds with cloud optical depth [COD] < 0.1) where little cloud information is contained in the ABI measurements, as well as for optically thick clouds (clouds with COD >= 3) where a larger proportion of opaque clouds is excluded. Furthermore, for the GBTCBH model using 9 months of CloudSat measurements as label, the CBH estimates are improved with an RMSE of 1.41 km and Pearson's r of 0.92. In a case study of Hurricane Dorian, CBHs for most of the single-layer clouds are successfully estimated with small errors and flagged with high confidence, for both high and low clouds. Deep convective clouds and multi-layer clouds, both of which are not included in the training, are reasonably flagged as low confidence with large CBH estimate errors. In this particular case, 65% of cloudy pixels have CBH estimate with high confidence in the scene. Daytime CBH with high spatial (2 km) and temporal (10 min) resolution can be derived from ABI measurements using this methodology.

Severe storms are often associated with high temporal and spatial variations in atmospheric moisture deviation. Satellite‐based hyperspectral IR sounders are widely used for weather forecasting and data assimilation in numerical weather prediction. Current infrared (IR) sounders have spatial resolutions ranging from 12 to 16 km, with future sounders improved to 4–8 km. It is important to understand if measurements from the current and future IR sounders can capture small‐scale atmospheric moisture variations, especially during mesoscale weather events. Using measurements from three Advanced Himawari Imager moisture absorption bands, different sounder resolutions are simulated for sub‐footprint moisture variation analysis. Current sounders are limited when attempting to capture small‐scale moisture variations, especially over land and in the pre‐convection environment. In contrast, future sounders such as the InfraRed Sounder with 4 km resolution can better capture such small‐scale variations. In addition, the higher spatial resolution IR sounders provide more clear sky observations for applications.

Four‐dimensional (4D) wind fields were derived from radiance measurements of the Geosynchronous Interferometric Infrared Sounder (GIIRS) onboard the FengYun‐4A satellite with 15‐min temporal resolution during Typhoon Maria (2018). Results are evaluated with independent ERA5 reanalysis, Global Data Assimilation System (GDAS) analysis and dropsonde wind profiles, and show a statistical root mean squared error less than 2 m/s for U and V components in troposphere against ERA5 and GDAS. The temporal variation of the wind fields from GIIRS at 15‐min intervals is consistent with that of the hourly ERA5. The added value of wind profiles over the numerical weather predictions (NWP) background field is also revealed. Further experiments confirm that higher temporal resolution from geostationary infrared (IR) sounder measurements could provide better dynamic information. 4D dynamic information can be extracted from high temporal resolution geostationary hyperspectral IR radiances in a consistent and continuous manner that can be used together with the thermodynamic information for various quantitative applications such as NWP data assimilation, near real‐time weather monitoring, situational awareness and nowcasting.

An operational data product available for both the Suomi National Polar-orbiting Partnership (S-NPP) and National Oceanic and Atmospheric Administration-20 (NOAA-20) platforms provides high-spatial-resolution infrared (IR) absorption band radiances for Visible Infrared Imaging Radiometer Suite (VIIRS) based on a VIIRS and Crosstrack Infrared Sounder (CrIS) data fusion method. This study investigates the use of these IR radiances, centered at 4.5, 6.7, 7.3, 9.7, 13.3, 13.6, 13.9, and 14.2 µm, to construct atmospheric moisture products (e.g., total precipitable water and upper tropospheric humidity) and to evaluate their accuracy. Total precipitable water (TPW) and upper tropospheric humidity (UTH) retrieved from hyperspectral sounder CrIS measurements are provided at the associated VIIRS sensor's high spatial resolution (750 m) and are compared subsequently to collocated operational Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) and S-NPP VIIRS moisture products. This study suggests that the use of VIIRS IR absorption band radiances will provide continuity with Aqua MODIS moisture products.

A long-term archive of cloud properties (cloud top pressure, CTP; and cloud effective emissivity, ε) determined from High-resolution Infrared Radiation Sounder (HIRS) data is investigated for evidence of regional cloud cover change. In the 17 years between 1985 and 2001, different cloud types are analysed over the Australian region (10° S–45° S, 105° E–160° E) and areas of change in total cloud frequency examined. Total cloud frequency change over the Australian region between two adjacent eight-year time periods (1994 to 2001 minus 1985 to 1992) shows the largest increases (ranges between 6% and 12%) of average HIRS total cloud cover occurring over the offshore regions to the northwest and northeast of the continent. Over land, the largest reduction of average HIRS total cloud frequency is in the southwestern region of Australia (between 2% and 8%). Through central Australia, there is a 2% to 7% increase in average HIRS total cloud frequency when comparing these eight-year periods. This paper examines the regional cloud changes in 17 years over Australia that are embedded in global cloud statistics. Examining total HIRS cloud cover frequency over Australia and comparing two different eight-year time periods, has highlighted notable areas of average change. Preliminary reporting of satellite-derived HIRS cloud products and Global Precipitation Climatology Project (GPCP) rainfall products during La Niña seasons between 1985 and 2001 has also been undertaken.

This paper compares the tropospheric moisture data records derived from High-resolution Infrared Radiation Sounder (HIRS) and Moderate Resolution Imaging Spectro-radiometer (MODIS) measurements from the years 2003 through 2013. Total Precipitable Water Vapor (TPW) and Upper Tropospheric Precipitable Water Vapor (UTPW) are derived using the infrared spectral bands in the CO2 and H2O absorption bands as well as in the atmospheric windows. Retrieval of TPW and UTPW uses a statistical regression algorithm performed using clear sky radiances (and Brightness Temperatures) measured over land and ocean for both day and night. The TPW and UTPW seasonal cycles of HIRS and MODIS observations are found to be in synchronization with zonal mean values for one degree latitude bands within 2.0 mm and 0.07 mm, respectively.

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.

Abstract. Retrieval of semitransparent ice cloud properties from the Visible Infrared Imaging Radiometer Suite (VIIRS) satellite sensor on the Suomi-NPP and NOAA-20 platforms is challenging due to the absence of infrared (IR) water vapor and CO2 absorption channels. However, on these platforms, there is a companion sensor called the Crosstrack Infrared Sounder (CrIS) that provides these spectral measurements, but at a lower spatial resolution (~ 15 km at nadir). To mitigate the lack of VIIRS spectral measurements in these IR absorption channels, recent studies suggest an approach to supplement VIIRS measurements by fusion of the imager and sounder data. In particular, Weisz et al. (2017) demonstrate a method to construct IR water vapor and CO2 absorption channel radiances for VIIRS at 750 m spatial resolution. Based on these constructed channels for both Suomi-NPP and NOAA-20, this study evaluates three cloud properties – cloud mask, cloud thermodynamic phase, and cloud top height – through comparison to the CALIPSO/CALIOP V4-20 cloud layer products and MODIS Collection 6.1 cloud top products. Each of these cloud properties show improvement with the use of these constructed channel radiances. The major improvement for the cloud mask is found over polar regions, where the correct cloud detection percentage increases due to decrease in missed cloud and/or false detection. For cloud thermodynamic phase, the ice cloud fraction increases over non-polar regions and the combined liquid water and ice cloud discrimination improves in comparison with CALIPSO. The retrieved cloud top height for semitransparent ice clouds increases over non-polar regions and tends to be closer to the true CALIPSO/CALIOP cloud top height. Moreover, the uncertainty of cloud top height retrievals decreases globally for these clouds.