Here, we present a new prototype algorithm for the simultaneous retrieval of the atmospheric profiles (temperature,
humidity, ozone and aerosol) and the surface reflectance from hyperspectral radiance measurements
obtained from air/space-borne, hyperspectral imagers such as the 'Airborne Visible/Infrared Imager (AVIRIS)
or Hyperion on board of the Earth Observatory 1. The new scheme, proposed here, consists of a fast radiative
transfer code, based on empirical orthogonal functions (EOFs), in conjunction with a 1D-Var retrieval scheme.
The inclusion of an 'exact' scattering code based on spherical harmonics, allows for an accurate treatment of
Rayleigh scattering and scattering by aerosols, water droplets and ice-crystals, thus making it possible to also
retrieve cloud and aerosol optical properties, although here we will concentrate on non-cloudy scenes. We successfully
tested this new approach using two hyperspectral images taken by AVIRIS, a whiskbroom imaging
spectrometer operated by the NASA Jet Propulsion Laboratory.
Atmospheric thermodynamic parameters and surface properties are basic meteorological variables for weather
forecasting. A physical geophysical parameter retrieval scheme dealing with cloudy and cloud-free radiances observed
with satellite ultraspectral infrared sounders has been developed and applied to data from the Infrared Atmospheric
Sounding Interferometer (IASI) and the Atmospheric InfraRed Sounder (AIRS). The retrieved parameters presented
herein are from radiance data gathered during the Joint Airborne IASI Validation Experiment (JAIVEx). JAIVEx
provided intensive aircraft observations obtained from airborne Fourier Transform Spectrometer (FTS) systems, in-situ
measurements, and dedicated dropsonde and radiosonde measurements for the validation of the IASI products. Here,
IASI atmospheric profile retrievals are compared with those obtained from dedicated dropsondes, radiosondes, and the
airborne FTS system. The IASI examples presented here demonstrate the ability to retrieve fine-scale horizontal features
with high vertical resolution from satellite ultraspectral sounder radiance spectra.
Atmospheric and surface thermodynamic parameters retrieved with advanced hyperspectral remote sensors of Earth observing satellites are critical for weather prediction and scientific research. The retrieval algorithms and retrieved parameters from satellite sounders must be validated to demonstrate the capability and accuracy of both observation and data processing systems. The European AQUA Thermodynamic Experiment (EAQUATE) was conducted mainly for validation of the Atmospheric InfraRed Sounder (AIRS) on the AQUA satellite, but also for assessment of validation systems of both ground-based and aircraft-based instruments which will be used for other satellite systems such as the Infrared Atmospheric Sounding Interferometer (IASI) on the European MetOp satellite, the Cross-track Infrared Sounder (CrIS) from the NPOESS Preparatory Project and the following NPOESS series of satellites. Detailed inter-comparisons were conducted and presented using different retrieval methodologies: measurements from airborne ultraspectral Fourier transform spectrometers, aircraft in-situ instruments, dedicated dropsondes and radiosondes, and ground based Raman Lidar, as well as from the European Center for Medium range Weather Forecasting (ECMWF) modeled thermal structures. The results of this study not only illustrate the quality of the measurements and retrieval products but also demonstrate the capability of these validation systems which are put in place to validate current and future hyperspectral sounding instruments and their scientific products.
Measured cloud spectra have been used to develop an initial cloud detection scheme for the assimilation of Infrared Atmospheric Sounding Interferometer (IASI) data. Using realistic data before the instrument is in orbit will help ensure that IASI data can be used at numerical weather prediction (NWP) centers soon after launch. The measured data have been taken by the Airborne Research Interferometer Evaluation System (ARIES) - specifically designed to gather data representative of IASI from an aircraft. The development of the cloud detection scheme and its final form are discussed. The scheme was designed to require no additional background information. Representative spectra are used to create a set of empirical orthogonal functions (EOF). EOF sets were based on 78 diverse modeled clear air spectra, supplemented by selected measured spectra. IASI data could be compressed using such EOF. Tests were carried out on various cloud detection procedures using separate measured spectra. Video data gave independent verification of cloudy and cloud free views. The results were encouraging; clouds were detected in the measured test data with the prospect of extending the results to more general data.
New infrared satellite sounders will give greatly increased spectral resolution. The expected improvements, such as increased vertical resolution of temperature and humidity profiles in numerical weather prediction (NWP) models, will rely on accurate cloud detection. Simulation of the expected radiances requires infrared spectra from clouds with known physical properties. ARIES, the Airborne Research Interferometer Evaluation System, is mounted on the U.K. Meteorological Office's research aircraft to gather data in preparation for the Infrared Atmospheric Sounding Interferometer (IASI). ARIES has a 1 cm<SUP>-1</SUP> wavenumber maximum spectral resolution over the range 600 to 3000 cm<SUP>-1</SUP> wavenumbers (wavelength, 16(DOT)7 to 3(DOT)3 micrometer). Infrared data over various cloud types have been measured along with in-situ temperature and humidity profiles -- often including microphysical measurements from within the cloud. With spectra from adjacent cloud free air, these provide data to model the cloud signature for NWP assimilation cloud detection. The data readily demonstrate the basic spectral signatures due to cloud:reduction of brightness temperature in the window regions, slope varying with cloud properties, solar reflection in the near-infrared and the opaque cloud top in the CO<SUB>2</SUB> sounding regions. A cloud detection algorithm is being developed that is intended as the first step in NWP processing. The algorithm takes advantage of the likely method of data compression to be used for IASI spectral data, using Empirical Orthogonal Functions (EOF). The EOFS used here are for cloud-free spectra and the cloud detection algorithm uses the magnitude of a residual -- which will reflect the presence of cloud, amongst other spectral features not represented in the EOFS. If additional EOFS representing cloud where added the cloud detection algorithm could also use these additional values which would be contained in the predictor for the EOFS.
Near coincident data from satellite and aircraft overpasses of stratocumulus in the South Atlantic have been analyzed. The satellite data are from the Along Track Scanning Radiometer-2 (ATSR-2) onboard the European Remote Sensing satellite-2 (ERS- 2) and are measurements of reflectance at wavelengths of 0.87 micrometer and 1.6 micrometer. From these, retrieval algorithms estimate the cloud optical depth and effective drop size using well established principles. The aircraft data consist of reflectance measurements made using the Scanning Airborne Filter Radiometer (SAFIRE) from a transit made just above the cloud, and liquid water content (LWC) and effective drop size measurement made using an FSSP probe from a transit made approximately 100 m below cloud top. The aircraft flights were made as part of the South Atlantic Tropical Experiment-2 which took place off the Namibian coast in October 1995 and which was designed to coincide with ERS-2 overpasses where possible. One particular flight, A423, has been studied here as offering the best chance of intercomparison of the respective systems measurements. Two flight legs have been analyzed, one for validation of reflectance measurements and one for validation of cloud effective radius. Poor correlation in initial comparisons based on the geolocation of the two instruments was improved greatly by allowing for, and estimating, the advection of the cloud deck by the local wind. Other adjustments included compensating a small error in the ATSR geolocation and allowing for differences in the respective instrument view angles. Following these adjustments, good agreement is shown for the 11 micrometer brightness temperatures and for the 0.87 micrometer reflectances. Large biases in the 1.6 micrometer reflectances confirm calibration errors that were already suspected for both instruments. Using the same wind advection the cloud effective radius retrievals were compared for the previous flight leg. Agreement is shown to be within 0.5 micrometer for measurements within 5 minutes of the exact collocation time. This is a remarkable result considering the sensitivity of the ATSR retrievals to 1.6 micrometer calibration errors.