Hyperspectral Satellite Radiance Atmospheric Profile Information Content and Its Dependence on Spectrometer Technology

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.

[1]  J. Eyre,et al.  Assimilation of satellite data in numerical weather prediction. Part I: The early years , 2019, Quarterly Journal of the Royal Meteorological Society.

[2]  Henry Buijs,et al.  Suomi‐NPP CrIS radiometric calibration uncertainty , 2013 .

[3]  W. Menzel,et al.  Inferring Convective Weather Characteristics with Geostationary High Spectral Resolution IR Window Measurements: A Look into the Future , 2009 .

[4]  Christopher D. Barnet,et al.  Hyperspectral Earth Observation from IASI: Five Years of Accomplishments , 2012 .

[5]  Andrew Collard,et al.  Selection of IASI channels for use in numerical weather prediction , 2007 .

[6]  E. Weisz,et al.  Dual-Regression Approach for High-Spatial-Resolution Infrared Soundings , 2018 .

[7]  William L. Smith,et al.  A principal component noise filter for high spectral resolution infrared measurements , 2004 .

[8]  H. B. Howell,et al.  Radiometric calibration of IR Fourier transform spectrometers: solution to a problem with the High-Resolution Interferometer Sounder. , 1988, Applied optics.

[9]  Ming Hu,et al.  Satellite Radiance Data Assimilation within the Hourly Updated Rapid Refresh , 2017 .

[10]  T. Kyle,et al.  Temperature soundings with partially scanned interferograms. , 1977, Applied Optics.

[11]  William L. Smith,et al.  Dual-Regression Retrieval Algorithm for Real-Time Processing of Satellite Ultraspectral Radiances , 2012 .

[12]  Masahiro Kazumori,et al.  All‐sky satellite data assimilation at operational weather forecasting centres , 2018 .

[13]  Stefano Migliorini,et al.  On the Equivalence between Radiance and Retrieval Assimilation , 2012 .

[14]  Jean-Luc Moncet,et al.  A comparison of radiative transfer models for simulating Atmospheric Infrared Sounder (AIRS) radiances , 2007 .

[15]  Clive D. Rodgers.  Information content and optimization of high-spectral-resolution measurements , 1996, Optics + Photonics.

[16]  B. Connor,et al.  Intercomparison of remote sounding instruments , 1999 .

[17]  Gail E. Bingham,et al.  IASI temperature and water vapor retrievals – error assessment and validation , 2009 .

[18]  Steven A. Ackerman,et al.  High-Spectral- and High-Temporal-Resolution Infrared Measurements from Geostationary Orbit , 2009 .

[19]  Sang Joon Kim,et al.  A Mathematical Theory of Communication , 2006 .

[20]  E. Weisz,et al.  Improved Severe Weather Forecasts Using LEO and GEO Satellite Soundings , 2020, Journal of Atmospheric and Oceanic Technology.

[21]  Henry Buijs,et al.  Spectral calibration and validation of the Cross‐track Infrared Sounder on the Suomi NPP satellite , 2013 .

[22]  William L. Smith,et al.  Technical Note: Evolution, current capabilities, and future advance in satellite nadir viewing ultra-spectral IR sounding of the lower atmosphere , 2009 .

[23]  R. Saunders,et al.  A new Infrared Atmospheric Sounding Interferometer channel selection and assessment of its impact on Met Office NWP forecasts , 2017, Advances in Atmospheric Sciences.

[24]  Niels Bormann,et al.  The assimilation of Cross‐track Infrared Sounder radiances at ECMWF , 2017 .

[25]  William L. Smith,et al.  The Use of Eigenvectors of Statistical Covariance Matrices for Interpreting Satellite Sounding Radiometer Observations , 1976 .

[26]  The Retrieval of Atmospheric Profiles From Satellite Radiances For NWP Data Assimilation , 2016 .

[27]  William L. Smith,et al.  The Use of Interferometric Radiance Measurements for Sounding the Atmosphere. , 1979 .

[28]  C. Rodgers.  Characterization and Error Analysis of Profiles Retrieved From Remote Sounding Measurements , 1990 .

[29]  Xu Liu,et al.  Principal component-based radiative transfer model for hyperspectral sensors: theoretical concept. , 2006, Applied optics.

[30]  Clive D Rodgers,et al.  Inverse Methods for Atmospheric Sounding: Theory and Practice , 2000 .

[31]  W. Paul Menzel,et al.  Satellite-Based Atmospheric Infrared Sounder Development and Applications , 2017 .

[32]  Robert O. Knuteson,et al.  Hyperspectral data noise characterization using principle component analysis: application to the atmospheric infrared sounder , 2007 .

[33]  William L. Smith,et al.  AIRS: Improving Weather Forecasting and Providing New Data on Greenhouse Gases. , 2006 .

[34]  Fuzhong Weng,et al.  Characterization of Long-Term Stability of Suomi NPP Cross-Track Infrared Sounder Spectral Calibration , 2017, IEEE Transactions on Geoscience and Remote Sensing.