With the high temporal resolution and high spectral resolving power, GEO hyperspectral IR sounders will have the capability to characterize the diurnal variations of several geophysical parameters better than GEO IR imagers, including surface emissivity, trace gas, dust, etc. For example, the high spectral resolution emissivity spectra with diurnal variation
Li, Z., J. Li, Y. Li, Y. Zhang, T. J. Schmit, L. Zhou, M. Goldberg, and W. Paul Menzel, 2012: Determining Diurnal Variations of Land Surface Emissivity from Geostationary Satellites, Journal of Geophysical Research – Atmospheres, 117, D23302, doi:10.1029/2012JD018279. (link)
Li, J., and J. Li, 2008: Derivation of global hyperspectral resolution surface emissivity spectra from advanced infrared sounder radiance measurements, Geophys. Res. Lett., 35, L15807, doi:10.1029/2008GL034559. (link)
Synergistic application with GEO imager
ITSC-20 has made a recommendation to operational NWP centers: Consider including a map of the sub-pixel information derived from imager pixels within hyperspectral sounder FOVs, should bandwidth allow (link). The high spatial resolution IR imagers allow improved sounder sub-pixel cloud characterization, which is beneficial for radiance assimilation. A good example of this synergistic application is use imager for IR sounder cloud-clearing, i.e. MODIS for AIRS (Li et al. 2005) and VIIRS for CrIS (Wang et al. 2014, 2015, 2017)
Wang Pei, Jun Li, Z. Li, A. H. N. Lim, Jinlong Li, T. J. Schmit, and M. D. Goldberg, 2017: The Impact of Cross-track Infrared Sounder (CrIS) Cloud-Cleared Radiances on Hurricane Joaquin (2015) and Matthew (2016) Forecasts, Journal of Geophysical Research – Atmospheres, 122, DOI: 10.1002/2017JD027515. (link)
Wang, P., Jun Li, M. Goldberg, T. J. Schmit, et al., 2015: Assimilation of thermodynamic information from advanced IR sounders under partially cloudy skies for regional NWP, Journal of Geophysical Research – Atmosphere, 120, doi:10.1002/ 2014JD022976.(link)
Wang, Pei, Jun Li, Jinlong Li, Zhenglong Li, Timothy J. Schmit, and Wenguang Bai, 2014: Advanced infrared sounder subpixel cloud detection with imagers and its impact on radiance assimilation in NWP, Geophysical Research Letters, 41, 1773 – 1780. (link)
The high spectral accuracy from the hyperspectral IR sounders such as AIRS, IASI, and CrIS on polar orbiting satellites allows them to be used as benchmark to inter-calibrate other sensors. This is particular useful for GEO sensors like ABI, GOES Imagers, and SEVIRI etc, see the Global Space-based Inter-Calibration System (GSICS) at WMO, NOAA, and EUMETSAT. For polar orbiting sensors, the inter-calibration is somehow limited due to mis-match in time and angle unless both are on the same platform. GEO hyperspectral IR sounders, will allow inter-calibrate co-hosted GEO imagers and polar orbiting sensors, including broadband imagers and hyperspectral IR sounders. Below shows selected studies on inter-calibration using hyperspectral IR sounders. Besides, there are a number of publications on GSICS here.
Goldberg M., G. Ohring, J. Butler, C. Cao, R. Datla, D. Doelling, V. Gärtner, T. Hewison, B. Iacovazzi, D. Kim, T. Kurino, J. Lafeuille, P. Minnis, D. Renaut, J. Schmetz, D. Tobin, L. Wang, F. Weng, X. Wu, F. Yu, P. Zhang and T. Zhu., 2011: The Global Space-based Inter-Calibration System (GSICS), Bulletin of the American Meteorology Society, 92, 467475, DOI: 10.1175/2010BAMS2967.1
Hewison, T.J., and M. König, 2008: Inter-Calibration of Meteosat imagers and IASI. Proc. of the 2008 EUMETSAT Meteorological Satellite Conf., Darmstadt, Germany, EUMETSAT. (link)
Tobin, D. C., H. E. Revercomb, C. C. Moeller, and T. S. Pagano (2006), Use of Atmospheric Infrared Sounder high–spectral resolution spectra to assess the calibration of Moderate resolution Imaging Spectroradiometer on EOS Aqua, J. Geophys. Res., 111, D09S05, doi:10.1029/2005JD006095.
Retrievals of trace gases (ozone, CO, CO2, methane etc)
Beyond highly accurate temperature and moisture profiles, hyspepctral IR sounders allows retrievals of trace gases such as ozone, CO, CO2, methane, ammonia etc. Continuous monitoring of those trace gases from GEO will allow better air quality forecasts.
Van Damme, M., Clarisse, L., Whitburn, S., Hadji-Lazaro, J., Hurtmans, D., Clerbaux, C., and Coheur, P.-F.: Industrial and agricultural ammonia point sources exposed, Nature, 564, 99–103, https://doi.org/10.1038/s41586-018-0747-1, 2018. (link)
Franco, B., Clarisse, L., Stavrakou, T., Müller, J.‐F., Van Damme, M., Whitburn, S., et al. (2018). A general framework for global retrievals of trace gases from IASI: Application to methanol, formic acid, and PAN. Journal of Geophysical Research: Atmospheres, 123, 13,963–13,984. https://doi.org/10.1029/2018JD029633 (link)
Liu, Quanhua & Xiong, Xiaozhen & Iturbide-Sanchez, Flavio & Liu, Xu & Wu, Wan & Gambacorta, Antonia. (2016). Retrievals of trace gases from hyperspectral sounders. 353-355. 10.1109/IGARSS.2016.7729085.(link)
Chahine, M.T., and co-authors (2006) AIRS: Improving Weather Forecasting and Providing New Data on Greenhouse Gases. Bulletin of the American Meteorological Society: Vol. 87, No. 7, pp. 911-926. (link)
Barnet, C.D., M. Goldberg, L. McMillin, and M.T. Chahine (2004), Remote sounding of trace gases with the EOS/AIRS instrument, in Atmospheric and Environmental Remote Sensing Data Processing and Utilization: an End-to-End System Perspective, H.-L. Huang and H.J. Bloom (Eds.), 5548, 300–310, Society of Photo-Optical Instrumentation Engineers, Bellingham, WA, USA. (link)
Nalli, N.R.; Tan, C.; Warner, J.; Divakarla, M.; Gambacorta, A.; Wilson, M.; Zhu, T.; Wang, T.; Wei, Z.; Pryor, K.; Kalluri, S.; Zhou, L.; Sweeney, C.; Baier, B.C.; McKain, K.; Wunch, D.; Deutscher, N.M.; Hase, F.; Iraci, L.T.; Kivi, R.; Morino, I.; Notholt, J.; Ohyama, H.; Pollard, D.F.; Té, Y.; Velazco, V.A.; Warneke, T.; Sussmann, R.; Rettinger, M. Validation of Carbon Trace Gas Profile Retrievals from the NOAA-Unique Combined Atmospheric Processing System for the Cross-Track Infrared Sounder. Remote Sens. 2020, 12, 3245. (link)
An Investigation of the Economic and Social Value of Selected NOAA Data and Products for Geostationary Operational Environmental Satellites (GOES) by CENTREC (2007) found estimated potential benefits from improved information from GOES-R satellites for the following five specific types of economic activities:
- Improved tropical cyclone forecasting resulting in more effective action to protect property and to enable evacuation of individuals residing in the path of the storm: $0.450 billion in 2015 (average of $130,000 per U.S. coastline mile from Maine to Texas) and $2.4 billion from 2015 to 2027 (average of $690,000 per U.S. coastline mile from Maine to Texas)
- Enhanced aviation forecasting resulting in improvements in avoidable delays, value of passenger time avoided, avoidable repair costs due to volcanic ash, and avoidable risk of aircraft/life lost: $0.169 billion in 2015 and $0.768 billion from 2015-2027
- More accurate temperature forecasts contributing to improved energy demand expectations and savings in the electricity and natural gas sectors: $0.512 billion in 2015 and $2.56 billion from 2015-2027
- Enhanced forecasts leading to more efficient irrigation of crops — resulting in water savings, energy savings by not having to pump water, and revenue gains from selling excess water: $0.061 billion in 2015 and $1.09 billion from 2015-2027
- Improved forecasting of tropical cyclones resulting in reduced losses to the recreational boating industry: $0.031 billion in 2015 and $0.141 billion from 2015-2027
Across the five activities, the combined annual value for 2015 exceeds $1.2 billion. The value of the combined estimated benefits for the 2015-2027 period approaches $7 billion.