Search

This contribution to the EUCREX mission 206 series aims at evaluating the performances of three methods considered for the retrieval of cloud microphysical properties (optical depth, droplet effective radius and liquid water path (LWP)) from Advanced Very High Resolution Radiometer (AVHRR) satellite images. These procedures, namely a set of empirical parameterizations, a physically based inversion code, and a neuronal approach, are tested with the mission 206 case study. The influence of horizontal averaging on the retrieved cloud properties is also investigated to assess the limitations of the comparison between satellite observations and aircraft measurements performed at a smaller scale.

Bidirectional reflectance distribution functions (BRDFs) of natural surfaces which are best represented by measured biconical reflectance factors (BRDFs) frequently do not fulfill the Helmholtz reciprocity requirement, although theory does not permit deviations. A new set of measured radiance data has been used to derive the BCRF by two different techniques to investigate the validity of the reciprocity requirement in measured data. Both techniques consider sky radiance. The interpolation technique replaces missing measurements by interpolated values. The resulting BRDFs show deviations from reciprocity but reproduce the measured radiances perfectly. This technique has been previously used. The new reciprocity technique replaces missing measurements by the requirement of reciprocity. The resulting BRDFs fulfill reciprocity completely but partly fail to reproduce the measurements. A discussion is given on the differences between the two sets of BRDFs, which are mostly small, and their possible reasons. The conclusion is that the truth is not known but may be in between the results obtained from the two techniques.

Postlaunch calibration of the Meteosat visible (VIS) channel has been performed with Meteosat-1, Meteosat-2, and Meteosat-4. The radiance at the satellite radiometer aperture has been determined by independent means and has been related to the simultaneous satellite radiometer count. This technique has been named vicarious calibration. Airborne radiance measurements over homogeneous targets (two land surfaces, clear ocean, and stratiform clouds) have been performed. The derived calibration factors are scene dependent because of the nonrectangular shape of the Meteosat VIS channel spectral responsivity curve. The latter and, hence, the scene dependence, slightly differs between the three satellites. Therefore, the calibration factors also differ within ±15%. Average values of the calibration factors are about 11 W m−2 sr−1 per count for land surfaces and clouds and about 1.5 W m−2 sr−1 per count for ocean.

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.© (1996) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

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.© (1996) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

Cloud detection from satellite data usually relies on the assignment of reflectance and radiation temperature of a pixel to a cloud or a cloud free surface according to preset thresholds. It also exploits the contrast between adjacent pixels. It will be shown that the so called split window information like that provided by the `Advanced Very High Resolution Radiometer' (AVHRR) onboard the NOAA satellites is a powerful tool to reduce ambiguity in cloud detection. The reflected part of the medium infrared spectral information is used for phase detection. Double view information like that of the `Along Track Scanning Radiometer' (ATSR) on ERS-1 may be of substantial help in cloud identification, but a careful georeferencing is required. An algorithm package called `AVHRR Processing scheme Over cLouds, Land and Ocean' (APOLLO) which can also process ATSR data, is used to derive cloud masks from AVHRR and ATSR data for day and night satellite overpasses. Several products can be obtained from the image files together with the cloud mask. From the cloud free pixels surface products can be derived. Cloud cover is derived from all pixels while cloud properties like the liquid water path are derived from fully cloudy pixels only. Examples are shown which are derived from a regional cloud climatology.

Clouds play an important role in the hydrological cycle and they are a climatic component. It is therefore necessary to known the distribution of clouds. A high-spatial resolution climatology of monthly mean cloud cover has been produced from the daily afternoon passages of the NOAA satellites since September 1991. The APOLLO (AVHRR Processing scheme Over cLouds, Land and Ocean) algorithm has been applied to AVHRR data to obtain a pixel by pixel cloud mask for an area of 560 X 560 km2 over the Alps and their forelands. Cloud cover is calculated for subareas of 14 X 15 km2 for the following classifications: all clouds, thick clouds, thin clouds, thick clouds with low, medium or high tops. This regional cloud climatology reveals topometeorological features like an increased cloud cover in the luff regions at the edges of the Alps. A strong horizontal inhomogeneity on a regional scale is typical in summertime. The seasonal changes of cloud cover are greater in the south than in the north of the Alps due to different climate types. Although the APOLLO algorithm still needs improvement it has proved to be a powerful tool for cloud detection and classification.© (1994) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

Die Welt ist so gros und breit, Der Himmel auch so hehr und weit, Ich mus das alles mit Augen fassen, Will sich aber nicht recht denken lassen. Dich im Unendlichen zu finden, Must unterscheiden und dann verbinden; Drum danket mein beflugelt Lied Dem Manne der Wolken unterschied.

The directional reflected radiation of natural surfaces may change even if nothing save the distribution of the irradiation over the hemisphere varies. This is due to the angular anisotropy of the reflection properties of natural surfaces. The quantitative determination of this effect for four different vegetated surfaces is the aim of this investigation. In this paper, results for the first of the four surfaces, a savannah, are shown. The directional reflected radiation may change by ± 1% per degree change of the solar zenith angle and by ± 1 per 6% change of the spectral atmospheric turbidity factor at 0.52 μm.

The albedo of four vegetated surfaces was investigated to derive its variability with differing distributions of the irradiance. The results are based on measured values of the spectral biconical reflectance factor, which are combined with calculated spectral irradiances for low and high atmospheric turbidity. The solar zenith angle is varied from 0° to 80°. The derived spectral albedos are then integrated with respect to wavelength in order to achieve the albedo. It is found that the variability of the albedo with respect to the atmospheric turbidity is less than 0.01 in nearly all cases. The variability of the albedo with respect to the solar elevation angle, however, is larger than 0.02 in many cases. For solar elevation angles from 20° to 60°, the variability of the albedo of the four surfaces can be represented by a mean curve which fits the individual variabilities with an accuracy of 0.015.

The average variability of the reflected radiation field due to differing distributions of the irradiation in case of a savannah was given in a previous paper. In this paper, equivalent results are given for three more surfaces: bog, pasture land, and coniferous forest. Because the results are rather similar, mean values for vegetated surfaces can be derived. They indicate a change of the reflected radiance by ± 1% per degree change of the solar zenith angle and per 10% change of the optical depth of the atmosphere.