Inferring Relative Humidity Profiles from 3DNEPH Cloud Data: Technique Development and Data Impact Study

摘要

We study the inference of humidity profiles from cloud data, using the 3DNEPH database as the source of the cloudiness information. The 3DNEPH (now RTNEPH) is a high resolution cloud database produced operationally by the USAF Global Weather Central. A colocation study of cloud data with radiosonde measurements of relative humidity over North America is used to develop and test a statistical method for inferring humidity profiles; a global data impact study is used to assess the utility of this moisture information. We review some previously developed methods for inferring humidity from cloud cover data, describe the database and processing used in our colocation study, and discuss the development and testing of the new method for inferring humidity. Regression equations were developed for the first two empirical orthogonal functions of relative humidity, using vertically compacted and horizontally averaged 3DNEPH cloud cover values as predictors. The regression equations were found to have smaller errors than existing level-to-level cloud to humidity conversion techniques in tests in which no attempt was made to tune the existing methods for optimal performance. The utility of the bogus RH data for operational data assimilation was studied in a global observing system experiment, using the AGGL global data assimilation system. The impact of the additional RH data was evident in analyses in the early part of the assimilation runs but was lost in the noise of the assimilation system at later times. (edc)