A method is described for the retrieval of cirrus cloud temperature and optical depth using thermal infrared data from the along-track scanning radiometer. The method utilizes above cloud and nearby clear sky thermal infrared data at two different viewing angles and assumes that the cirrus cloud is nonscattering, isothermal and semitransparent. The sensitivity of the method to small uncertainties in the input parameters is calculated. It is shown that vertical inhomogeneity can cause large errors in the retrieved quantities for a wide range of cloud types. However, for the majority of expected cirrus cloud optical and physical thicknesses retrieved quantities remain within usable limits, with optical depth being retrieved to an accuracy of around 10 percent or better and temperature to 10K.

Quantitative assessments on the performance of automated cloud analysis algorithms require the creation of highly accurate, manual cloud, no cloud (CNC) images from multispectral meteorological satellite data. In general, the methodology to create ground truth analyses for the evaluation of cloud detection algorithms is relatively straightforward. However, when focus shifts toward quantifying the performance of automated cloud classification algorithms, the task of creating ground truth images becomes much more complicated since these CNC analyses must differentiate between water and ice cloud tops while ensuring that inaccuracies in automated cloud detection are not propagated into the results of the cloud classification algorithm. The process of creating these ground truth CNC analyses may become particularly difficult when little or no spectral signature is evident between a cloud and its background, as appears to be the case when thin cirrus is present over snow-covered surfaces. In this paper, procedures are described that enhance the researcher's ability to manually interpret and differentiate between thin cirrus clouds and snow-covered surfaces in daytime AVHRR imagery. The methodology uses data in up to six AVHRR spectral bands, including an additional band derived from the daytime 3.7 micron channel, which has proven invaluable for the manual discrimination between thin cirrus clouds and snow. It is concluded that while the 1.6 micron channel remains essential to differentiate between thin ice clouds and snow. However, this capability that may be lost if the 3.7 micron data switches to a nighttime-only transmission with the launch of future NOAA satellites.

A cloud detection scheme is being developed at the UK Met. Office that compares the observed satellite sounder brightness temperatures calculated from a short term forecast of a numerical weather prediction (NWP) model. The scheme will be used in the first step of the operational processing of sounder data for assimilation into the NWP models. The data are from TOVS on the NOAA polar orbiting satellites, and will soon also include data from the new advanced TOVS (ATVOS). The aim of the scheme is to use one calculation to maximize the information assimilated from the infrared channels into the NWP model, while preventing the assimilation of cloud contaminated data. Where no cloud is detected by the scheme the maximum number of infrared channels shall be used in the subsequent retrieval of the data. Where cloud is detected by the scheme the affected infrared channels will be excluded from the later 1DVAR processing. Being in the same program as the 1DVAR, the existing error covariance matrices and radiative transfer code are readily available to the cloud detection scheme. Details are given of the principles behind the cloud detection scheme. The cloud detection results are compared with data form: AVHRR imagery, the results from a 1DVAR cloud retrieval and the current operational cloud detection scheme.

The present understanding of moist atmospheric processes and the role of clouds in the hydrologic cycle shows severe gaps of knowledge. Water vapor plays an essential part in atmospheric dynamics. For example, the release of large amounts of latent heat, due to the condensation in convective clouds, plays an important role in the general circulation. Knowledge of the distribution of clouds and its transport is essential to understand atmospheric dynamics. Clouds can have a positive as well as a negative contribution to the greenhouse effect. A cloud cover climatology in a 15 km grid resolution has been retrieved by means of the APOLLO algorithm using the 5 calibrated AVHRR channels. The monthly means of total cloud cover are about 15 percent too high compared to conventional data, the standard deviation is +/- 12 percent. The high resolution cloud cover maps show topometeorological features like 'Fohn' on single days but not in monthly means, because these events are too rare. But increased cloud cover in the luff regions are detected in monthly means as well as some cloud sparse regions like Lake Garda, Ticino or the Swiss Rhone valley. The different annual cycles of cloud cover show the different climatic regions, which are temperate, Alpine, and Mediterranean climate. This is indicated, for example, by the remarkably smaller cloud cover in the Alpine region in winter as compared to the northern and southern forelands.

During the conference on 'passive remote sensing of clouds and the atmosphere III' in 1995, a comparison of cloud amounts derived from two retrieval schemes, APOLLO and CHAPS, was presented. It showed good results over ocean but not so good ones over land surfaces. Reasons for the discrepancy have been suggested. Meanwhile, a modified version of the APOLLO scheme has been developed and compared to a one year data set of synop data. They agree quite well. This modified version of APOLLO is used for a new comparison with CHAPS. Using the same data set, the agreement is very god. The remaining difference is probably due to insufficient cloud detection with CHAPS.

A new method of particle size retrieval is proposed of rice crystal and mixed phase clouds. The method enables us to identify each component of a bi-component cloud composed namely of ice crystals and water droplets and to retrieve separately size distributions of each cloud component. Its capability is explored as usually by using 'synthetic' multi-angular data of scattered light intensity. Various cloud microphysical characteristics are modeled by assuming two non-interacting cloud components such as liquid or supercooled droplets and cubic or hexagonal ice crystals with regular simple geometrical shapes as a first approximation. The sensitivity of the method is tested for different relative concentrations of the cloud components varying over a wide range. Firstly, we investigate the applicability limits of the single-component cloud approximation in retrieving particle size distributions of a bi-component cloud. Secondly, we test the method to retrieve simultaneously the size distributions of both the components in mixed-phase clouds, and discuss the conditions of its applicability.

The Atmospheric Infrared Sounder (AIRS) is being developed for the NASA Earth Observing System (EOS) program with a scheduled launch on the first post meridian platform in the year 2000. AIRS is designed to provide both new and more accurate data about the atmosphere, land, and oceans for application to climate studies and weather prediction. Among the important parameters to be derived from AIRS observations are atmospheric temperature profiles with an average accuracy of 1 K in 1 kilometer layers in the troposphere and surface temperatures with an average accuracy of 0.5 K. The AIRS measurement technique is based on very sensitive passive infrared remote sensing using a precisely calibrated, high resolution grating spectrometer operating in the 3.7 micrometers to 15.4 micrometers region. The instrument concept uses passively cooled multi-aperture eschelle array spectrometer approach in combination with advanced state-of-the-art focal plane and cryogenic refrigerator technology to achieve unparalleled performance capability in a practical long life configuration. AIRS is a key component of NASA's global change research program, and is expected to play an important role in the converged National Polar Orbiting Environmental Satellite System, now under study. This paper provides a brief description of the AIRS instrument design and focuses on the current development status of hardware currently being fabricated for the engineering model. In particular, the paper will address the status and expected performance of the AIRS focal plane assembly, the cryocooler, and components of the optical spectrometer.

High resolution limb emission spectra were measured by the balloon-borne FTIR spectrometer MIPAS-B in the Arctic vortex in March 1992. These spectra are significantly affected by the Mt. Pinatubo stratospheric aerosol. A method has been developed for separating the radiance signal of emission lines of trace gases from the aerosol continuum. By applying this method to the MIPAS-B spectra aerosol extinction coefficients have been retrieved at approximately 60 spectral positions in the 750-980 cm^-1 and 1180-1380 cm^-1 spectral ranges. The spectral shape of the mid- IR aerosol extinction has been derived for the tangent altitudes 11.3 km, 14.5 km and 16.1 km. On the basis of Mie- calculations it has been demonstrated that the spectral aerosol extinction coefficient is sensitive to the aerosol composition as well as to the particle size distribution. An algorithm has been developed to retrieve microphysical parameters by least-squares fitting of the derived spectral extinction coefficients to Mie-generated extinction coefficients. The retrieved aerosol parameters indicate the significance of scattering even in the mid-IR. Related corrections on the basis of multiple scattering calculations were performed. Retrieved compositions and effective volume densities of the Pinatubo aerosol in the Arctic vortex are presented.

The FTIR spectrometer is devoted to detect and study the concentration and spatial distribution of atmospheric trace gases and of natural ozone in the wavelength band 2-16 micrometers with spectral resolution 0.1 cm^-1 and in the height range between 10km to 70km with vertical spatial resolution approximately 2km. Measurements will take place during sunset and sunrise for absorption spectrum. The instrument will be looking at the Sun through the Earth's atmosphere. These measurements will be very useful in the study of the Earth's environment. Moreover, the instrument is used to study the designing and manufacturing of light and compact FTIR spectrometers for low-cost small satellite missions. The instrument will be placed on board the small satellite CESAR, which is a Sun pointing satellite with position accuracy better than 1 degree. CESAR satellite orbital parameters are : perigee-400km, apogee-1000km, inclination 70 degrees, period-98.8 min. The general description of the instrument and preliminary measurements are presented.

The Global Ozone Monitoring Experiment (GOME) is a new atmospheric chemistry instrument on-board the ERS-2 satellite which was launched in April 1995. The GOME is designed to measure a range of atmospheric trace constituents, with particular emphasis on global ozone distributions. The ground segment for the GOME sensor is with the German Remote Sensing Data Centre (DFD). Raw GOME data are converted into 'calibrated radiances' during the Level 0 to 1 processing by applying a series of calibration algorithms using in-flight observations and pre-flight instrument calibration parameter. Total column abundances of ozone and other trace gases can be derived from the Level 1 Product, comprising the Earth-shine radiance and the extra- terrestrial Solar irradiance, by applying three designated algorithms in the Level 1 to 2 processing step. The Initial Cloud Fitting Algorithm (ICFA) uses the spectral features close to and within the)₂ A-band around 760 nm to determine the fractional cloud cover of the pixel scene. The Differential Optical Absorption Spectroscopy technique is used for the slant columns densities are converted to vertical columns by division with an appropriate Air Mass Factor (AMF), derived from radiative transfer simulations. If clouds are detected by ICFA, an averaged AMF is calculated from the intensity-weighted AMFs to ground and to cloud top. SInce the end of July 1996 the GOME data processing at the DFD is performed operationally.

The variability of the phase function of the submicrometer aerosol at large scattering angels was studied in detail. It was found that the coefficient of variance of the phase function has a minimum around the scattering angle 150 degrees. This fact can be used for solution of different atmospheric optics problems, including atmospheric correction ones.

The accurate knowledge of pressure and temperature profiles is a precondition for the retrieval of race gas profiles from limb emission measurements. A method was investigated which allows the pressure and temperature retrieval from limb emission spectra as expected to be measured by the MIPAS-ENVISAT instrument. Regardless which retrieval scheme will be used, the simultaneous retrievability of pressure and temperature depends largely on the proper selection of microwindows. Microwindows which contain a large amount of information on these target quantities while being insensitive to systematic errors are considered to be the most appropriate ones. A microwindow selection which minimizes the pressure temperature retrieval error has been carried out for the instrument specifications of MIPAS- ENVISAT. Errors under consideration were random noise, calibration uncertainties, and neglection of possible breakdown of thermodynamic equilibrium.

The detection the minor gaseous constituents and the determination of their concentration is important in the study of the Earth's environment. These components can play a substantial role in the atmospheric processes leading even to breaking down the ecological equilibrium. Mid- and long- term observations form ground and from space are necessary to monitor sudden changes and to investigate the long-term trends in the composition of the atmosphere. We propose here a space-ground correlative experiment which gives new possibilities. Simulation of solar absorption spectra of the trace gases in the Earth's atmosphere in 2-16 micrometers spectral range for both types of measurements are presented.

Airborne measurement of stratus is being carried out by ONERA in order to validate NUALUM cloud simulation. The cloud top is measured by a circular variable filter cryogenic spectrometer SICAP. Two observation zenith angles are tested and the azimuth angle is variable. In situ liquid water content (LWC) measurement in performed by a Johnson Williams probe and compared with meteorological sounding. The liquid water content has been valuated inside a layer from 200m to 600m altitude. Mean LWC is equal to 0.3g/m3. Those values are typical of a stratus. The NUALUM cloud radiative transfer code has been developed at ONERA. The optical properties are computed by MIE theory. NUALUM includes the DISORT code to compute the multiple scattering in the cloud, by the mean of the discrete ordinates method. Spectral measurements show great variations of the radiation according to the azimuth angle when the wavelength is less than 4 micrometers . In this range of wavelength, radiation provides from solar reflection which is very sensitive to the scattering angle. Above 4 micrometers , thermal radiance increases. A good correlation is observed between the shape of the phase function of cloud particles and the radiance variation with scattering angle. NUALUM is in agreement with the stratus spectral measurements. During the experiment, sea spectral measurements have also been carried out. Solar reflection on the sea surface of the sea is specular and only occurs for low scattering angles.