MultiSensors Investigation of Atmospheric Water Vapor Probability Distribution Function in the Free Troposphere for a Mediterranean Coastal Site
Abstract
Parameterization of subgrid variability processes is a critical issue for largescale atmospheric numerical models, particularly when used for climate studies. Indeed, the nonlinearity of moist processes and the effects of clouds in energy and mass transport processes cause sensitivity to the definition of Probability Distribution Function (PDF) assumed in the model. The presented study investigates the possibility of deriving a description of the PDF from a set of observations representative of a Mediterranean coastal site. In order to describe the water vapour variability within a given atmospheric volume from a single sensor measurements, PDF's are derived from a set of high resolution (temporal and/or vertical) observations by mean of a set of assumptions on space/time correspondence derived from the analyses of local wind intensity measurements.Observations used in this study are: Time series (from 2002 to date) of radiosoundings from the coastal station of Pratica di Mare (WMO station #16245, 41.67 N, 12.45 E, 35 m a.s.l), for which the original highresolution data (10s sampling, roughly corresponding to 30 m in vertical sampling) are available. A set of measurement sessions, lasting typically 34 hours (1min 75 m resolution original sampling) of water vapour profiles from the ISACCNR Raman Lidar [1] in RomeTor Vergata (41.8 ° N, 12.6 ° E, 107 m a.s.l.), extending up to the free troposphere with a nominal vertical resolution of 75 m.PDF's are derived assuming typical characteristics of the Climate Model LMDZ [2] in terms of horizontal and vertical (σlevels) resolution.The investigation focuses on the description of the functional form of the PDF and on the parameterization of the PDF characterizing parameters.Limits and assumptions in the PDF definition technique are discussed, and in particular: The representativeness of the Raman derived results due to the clear sky/nighttime biased sampling.The results are confronted to the PDF's currently used in the LMDZ General Circulation Model
 Publication:

Earth Observation and Water Cycle Science
 Pub Date:
 November 2009
 Bibcode:
 2009ESASP.674E..53L