lmd_Seze1985_abstracts.html

1985 .

(5 publications)

W. B. Rossow, F. Mosher, E. Kinsella, A. Arking, M. Desbois, E. Harrison, P. Minnis, E. Ruprecht, G. Seze, C. Simmer, and E. Smith. ISCCP Cloud Algorithm Intercomparison. Journal of Applied Meteorology, 24:887-903, September 1985. [ bib | DOI | ADS link ]

The International Satellite Cloud Climatology Project (ISCCP) will provide a uniform global climatology of satellite-measured radiances and derive an experimental climatology of cloud radiative properties from these radiances. A pilot study to intercompare cloud analysis algorithms was initiated in 1981 to define a state-of-the-art algorithm for ISCCP. This study compared the results of applying six different algorithms to the same satellite radiance data. The results show that the performance of all current algorithms depends on how accurately the clear sky radiances are specified; much improvement in results is possible with better methods for obtaining these clear-sky radiances. A major difference between the algorithms is caused by their sensitivity to changes in the cloud size distribution and optical properties: all methods, which work well for some cloud types or climate regions, do poorly for other situations. Therefore, the ISCCP algorithm is composed of a series of steps, each of which is designed to detect some of the clouds present in the scene. This progressive analysis is used to retrieve an estimate of the clear sky radiances corresponding to each satellite image. Application of a bispectral threshold is then used as the last step to determine the cloud fraction. Cloudy radiances are interpreted in terms of a simplified model of cloud radiative effects to provide some measure of cloud radiative properties. Application of this experimental algorithm to produce a cloud climatology and field observation programs to validate the results will stimulate further research on cloud analysis techniques as part of ISCCP.

W. B. Rossow, F. Mosher, E. Kinsella, A. Arking, M. Desbois, E. Harrison, P. Minnis, E. Ruprecht, G. Seze, C. Simmer, and E. Smith. ISCCP Cloud Algorithm Intercomparison. Journal of Applied Meteorology, 24:877-903, September 1985. [ bib | DOI | ADS link ]

M. Desbois, L. Picon, and G. Sèze. Retrieval of some climatic elements of Africa from METEOSAT data analysis. Advances in Space Research, 5:49-52, 1985. [ bib | DOI | ADS link ]

A study of some climatic elements of Africa from METEOSAT imagery has been undertaken at our laboratory. The general objectives of this project and its interaction with a Sahelian climate simulation with the LMD GCM are described. The problems relative to the measurement of seasonal land surface albedo variations are outlined. Preliminary results of a simple method comparing January and April 1982 are shown and discussed.

W. B. Rossow, F. Mosher, E. Kinsella, A. Arking, M. Desbois, E. Harrison, P. Minnis, E. Ruprecht, G. Sèze, and E. Smith. ISCCP cloud analysis algorithm intercomparison. Advances in Space Research, 5:185-185, 1985. [ bib | DOI | ADS link ]

The International Satellite Cloud Climatology Project (ISCCP) will provide a uniform global climatology of satellite-measured radiances and derive a climatology of cloud radiative properties from these radiances. For this purpose, a pilot study of cloud analysis algorithms was initiated to define a state-of-the-art algorithm for ISCCP. This study compared the results of applying the nine different algorithms to the same satellite radiance data. The comparison allowed for a sharper understanding of the process of detecting clouds and shows that all algorithms can be improved by better information about clear sky radiance values (essentially equivalent to surface property information) and by better understanding of cloud size distribution variations. The dependence of all methods on cloud size distribution led to selection of an advanced bispectral threshold technique for ISCCP because this method is currently better understood and more developed. Further research on cloud algorithms is clearly suggested by these results.

G. Sèze, C. Belcour, and M. Desbois. Cloud cover analysis using spectral and spatial characteristics of meteosat images. Advances in Space Research, 5:165-168, 1985. [ bib | DOI | ADS link ]

New developments of a cloud classification scheme based on histogram clustering by a statistical method are studied. Use of time series of satellite pictures and of spatial variances is introduced and discussed.