HUMIDITY FIELDS ANALYSIS IN DAYTIME CLOUDY SKY WITH MULTI-SPECTRAL SATELLTE INFORMATION

Despite that the retrieval study of hum idity fields in clear sky with TOVS data has been many years,how to obtain the retrieved humidity fields in cloudy sky with satellite remote sensing inform ation is also a problem.This paper addresses the relationship between multispectral satellite information and probed relative humidity in each of standard isobaric surfaces using correlation analysis,least-square fitting and multivariate linear regression separately.Complex correlation coefficient R(≈0.64) of the standard regression scheme is minimal at ground level and then grows with height,reaching>0.7 above 700hPa and>0.8 above 250 hPa,with significance test results (F value) increasing from 30.71 at ground to 119.36 at 200 hPa.When a stepwise regression scheme is adopted,most of insignificant variables have been removed in such a way that only 2-4 variables remain,and F value showing significance level is raised quite considerably.Accordingly,we have established a system of multi-variant linear regression form ulae that can be used in cloudy sky with the aim to determine standard-level RH fields of satellite imagery pixel resolution(8-10 km) directly from multispectral satellite information.