Abstract
Abstract. The Infrared Atmospheric Sounding Interferometer (IASI) is an ultra-spectral satellite sensor with 8461 spectral channels. IASI spectra contain high information content on atmospheric, cloud, and surface properties. The instrument presents a challenge for using thousands of spectral channels in a physical retrieval system or in a Numerical Weather Prediction (NWP) data assimilation system. In this paper we describe a method of simultaneously retrieving atmospheric temperature, moisture, and cloud properties using all available IASI channels without sacrificing computational speed. The essence of the method is to convert the IASI channel radiance spectra into super-channels by an Empirical Orthogonal Function (EOF) transformation. Studies show that about 100 super-channels are adequate to capture the information content of the radiance spectra. A Principal Component-based Radiative Transfer Model (PCRTM) is used to calculate both the super-channel magnitudes and derivatives with respect to atmospheric profiles and other properties. A physical retrieval algorithm then performs an inversion of atmospheric, cloud, and surface properties in the super channel domain directly therefore both reducing the computational need and preserving the information content of the IASI measurements. While no large-scale validation has been performed on any retrieval methodology presented in this paper, comparisons of the retrieved atmospheric profiles, sea surface temperatures, and surface emissivities with co-located ground- and aircraft-based measurements over four days in Spring 2007 over the South-Central United States indicate excellent agreement.
Highlights
Modern satellite sensors such as Atmospheric Infrared Sounder (AIRS), Infrared Atmospheric Sounding Interferometer (IASI), and Cross-track Infrared Sounder (CrIS) all have two orders of magnitude more spectral channels relative to traditional operational sounders such as the High Resolution Infrared Radiation Sounder (HIRS) and the Geostationary Operational Environmental Satellites (GOES) sounder
AIRS is a grating instrument with 2378 spectral channels that was launched on 4 May 2002 aboard of the NASA Earth Observing System (EOS) Aqua satellite
We have demonstrated that by converting IASI spectra into super channels, we can retrieve atmospheric and surface near surface air temperature is still small
Summary
Modern satellite sensors such as Atmospheric Infrared Sounder (AIRS), Infrared Atmospheric Sounding Interferometer (IASI), and Cross-track Infrared Sounder (CrIS) all have two orders of magnitude more spectral channels relative to traditional operational sounders such as the High Resolution Infrared Radiation Sounder (HIRS) and the Geostationary Operational Environmental Satellites (GOES) sounder. Radiance spectra measured by these new sounders can be inverted to provide high resolution atmospheric temperature profiles, humidity profiles, cloud properties, and surface properties They provide improved weather and climate observations and forecasting. These models are orders of magnitude faster than line-by-line radiative transfer models Because these fast forward models deal with one spectral channel at a time, it is still challenging to incorporate thousands of channel radiances into data assimilation systems. Even if the forward models are fast enough, the Jacobian and channel covariance matrices are so large that it is time consuming to perform matrix operations in an inversion process Another way to use these thousands of channels is to transform them into some kind of super channels. We will present our summary and conclusions on the super channel retrieval approach
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