Geosynchronous Imaging Fourier Transform Spectrometer Research Articles

Can geosynchronous imaging Fourier transform spectrometer capture vertical and temporal variability of a convective atmosphere?

Insufficient high vertical and temporal resolution data have limited the precipitation forecast skill of convective initiation. The Geosynchronous Imaging Fourier Transform Spectrometer (GIFTS), a new hyperspectral geostationary satellite measurement system, could provide top-of-atmosphere (TOA) radiances across two broad spectral regions with high-resolutions in spectral, horizontal and temporal spaces within a fixed domain. A set of modeled and observed vertical profiles of atmospheric moisture and temperature during a convective initiation (CI) event within the observing period of the International H2O Project (IHOP_2002) are used to assess the potential values of GIFTS measurements to convective precipitation forecast. First, it is shown that the model simulation captures reasonably well the movement of the precipitation bands and the gradient structures of temperature and water vapor of the convectively initiated storm. Second, the observed vertical and temporal variability of water vapor during the CI period is shown to be quite significant in the lower troposphere. The differences between observations and model simulation are also noticed. Using both the observed and the model-predicted profiles as input to GIFTS radiative transfer model (RTM), it is finally shown that the simulated GIFTS radiance could capture the high vertical and temporal variability of the real and modeled atmosphere prior to the CI, as well as the differences between observations and model forecasts. The study suggests the potential for GIFTS to make important contributions to the improvement of the forecast skill of convective precipitation.

Ground-based measurements with the Geosynchronous Imaging Fourier Transform Spectrometer (GIFTS) engineering demonstration unit - experiment description and first results

The Geosynchronous Imaging Fourier Transform Spectrometer (GIFTS) Engineering Demonstration Unit (EDU) is an imaging infrared spectrometer designed for atmospheric soundings. It measures the infrared spectrum in two spectral bands (14.6 to 8.8 um, 6.0 to 4.4 um) using two 128x128 detector arrays with an unapodized spectral resolution of 0.57 cm-1 (i.e., with a maximum optical path difference of ~0.88 cm) and a full spectral resolution scan duration of ~11 seconds. From a geosynchronous orbit, the instrument will have the capability of taking successive measurements of different geographical areas to scan any desired region of the globe, from which atmospheric temperature and moisture soundings, cloud and surface parameters, wind profiles, as well as other derived products can be retrieved. The GIFTS EDU provides a flexible and accurate testbed for the new challenges of the emerging hyperspectral era. The EDU ground-based measurement experiment, held in Logan, Utah during September 2006, demonstrated extensive capabilities and the potential for geosynchronous satellite and other platform Earth observing environmental measurements. This paper addresses the ground-based experiment objectives and provides first-look results illustrating the overall performance of the sensor system with a focus on the GIFTS EDU imaging capability and proof of the GIFTS measurement concept.

Effect of the improvement of the HITRAN database on the radiative transfer calculation

The line parameters of the HITRAN 2004 have been updated, as compared with the older editions (the 2000 edition and the 1996 edition). In order to know the effect of the modifications on radiative transfer calculation with high spectral resolution, comparison in optical depth and radiance spectrum have been given between different editions. Four infrared spectral regions are selected, and they cover the three bands of atmospheric infrared sounder (AIRS) and one of geosynchronous imaging fourier transform spectrometer (GIFTS). The comparison has shown that the relative difference between HITRAN 2000 and 2004 and that between HITRAN 1996 and 2004 is decreasing. But the maximal discrepancy between the latest two editions in some spectral intervals is over 1%. It is important to estimate the error of calculation with the line parameters correctly or one has to use the new edition of HITRAN.

Physically Retrieving Cloud and Thermodynamic Parameters from Ultraspectral IR Measurements

Abstract A physical inversion scheme has been developed dealing with cloudy as well as cloud-free radiance observed with ultraspectral infrared sounders to simultaneously retrieve surface, atmospheric thermodynamic, and cloud microphysical parameters. A fast radiative transfer model, which applies to the clouded atmosphere, is used for atmospheric profile and cloud parameter retrieval. A one-dimensional (1D) variational multivariable inversion solution is used to improve an iterative background state defined by an eigenvector-regression retrieval. The solution is iterated in order to account for nonlinearity in the 1D variational solution. It is shown that relatively accurate temperature and moisture retrievals can be achieved below optically thin clouds. For optically thick clouds, accurate temperature and moisture profiles down to cloud-top level are obtained. For both optically thin and thick cloud situations, the cloud-top height can be retrieved with relatively high accuracy (i.e., error <1 km). National Polar-orbiting Operational Environmental Satellite System (NPOESS) Airborne Sounder Testbed Interferometer (NAST-I) retrievals from the The Observing-System Research and Predictability Experiment (THORPEX) Atlantic Regional Campaign are compared with coincident observations obtained from dropsondes and the nadir-pointing cloud physics lidar (CPL). This work was motivated by the need to obtain solutions for atmospheric soundings from infrared radiances observed for every individual field of view, regardless of cloud cover, from future ultraspectral geostationary satellite sounding instruments, such as the Geosynchronous Imaging Fourier Transform Spectrometer (GIFTS). However, this retrieval approach can also be applied to the ultraspectral sounding instruments to fly on polar satellites, such as the Infrared Atmospheric Sounding Interferometer (IASI) on the European MetOp satellite, the Cross-track Infrared Sounder (CrIS) on the NPOESS Preparatory Project, and the follow-on NPOESS series of satellites.

A robust framework for real-time distributed processing of satellite data

It is estimated that future satellite instruments such as the Advanced Baseline Imager (ABI) and the Hyperspectral Environmental Suite (HES) on the GOES-R series of satellites will provide raw data volume of about 1.5 Terabyte per day. Due to the high data rate, satellite ground data processing will require considerable computing power to process data in real-time. Cluster technologies employing a multi-processor system present the only current economically viable option. To sustain high levels of system reliability and operability in a cluster-oriented operational environment, a fault-tolerant data processing framework is proposed to provide a platform for encapsulating science algorithms for satellite data processing. The science algorithms together with the framework are hosted on a Linux cluster. In this paper we present an architectural model and a system prototype for providing performance, reliability, and scalability of candidate hardware and software for a satellite data processing system. Furthermore, benchmarking results are presented for a selected number of science algorithms for the Geosynchronous Imaging Fourier Transform Spectrometer (GIFTS) instrument showing that considerable performance can be gained without sacrificing the reliability and high availability constraints imposed on the operational cluster system.

Principal component-based radiative transfer model for hyperspectral sensors: theoretical concept

Modern infrared satellite sensors such as the Atmospheric Infrared Sounder (AIRS), the Cross-Track Infrared Sounder (CrIS), the Tropospheric Emission Spectrometer (TES), the Geosynchronous Imaging Fourier Transform Spectrometer (GIFTS), and the Infrared Atmospheric Sounding Interferometer (IASI) are capable of providing high spatial and spectral resolution infrared spectra. To fully exploit the vast amount of spectral information from these instruments, superfast radiative transfer models are needed. We present a novel radiative transfer model based on principal component analysis. Instead of predicting channel radiance or transmittance spectra directly, the principal component-based radiative transfer model (PCRTM) predicts the principal component (PC) scores of these quantities. This prediction ability leads to significant savings in computational time. The parameterization of the PCRTM model is derived from the properties of PC scores and instrument line-shape functions. The PCRTM is accurate and flexible. Because of its high speed and compressed spectral information format, it has great potential for superfast one-dimensional physical retrieval and for numerical weather prediction large volume radiance data assimilation applications. The model has been successfully developed for the NAST-I and AIRS instruments. The PCRTM model performs monochromatic radiative transfer calculations and is able to include multiple scattering calculations to account for clouds and aerosols.