Analysis and improvements of cloud models for propagation studies

Abstract

[1] Two cloud models currently in use in propagation and remote sensing simulations in the presence of nonprecipitating clouds were analyzed. A new cloud model is also proposed: a modification of a humidity threshold to better identify clouds is suggested, as is a new cloud density function for computing cloud liquid and ice content within a cloud. The performances of the threshold functions were examined at the Atmospheric Radiation Measurement (ARM) Program's Southern Great Plaints (SGP) site in Oklahoma, USA, by using radiosonde and ceilometer data. The new threshold showed an improvement in the cloud detection (15%) and a reduction of false cloud identification in clear-sky conditions (26%). Next, the cloud density models were evaluated in the brightness temperature (Tb) domain, by comparing simulated Tb values in cloudy conditions with those measured by dual-channel microwave radiometers at several ARM sites. The new model provided good results in comparison with the radiometer measurements, with overall root mean square (RMS) differences of 3.10 K, reducing the RMS by about 16% with respect to the best of the other models. Improvements can be noticed in particular at SGP (20%), and in the tropics (37%).Citation: Mattioli, V., P. Basili, S. Bonafoni, P. Ciotti, and E. R. Westwater (2009), Analysis and improvements of cloud models for propagation studies, Radio Sci., 44, RS2005,

On the Use of Microwave Radiometers for Deep Space Mission Applications by Means of a Radiometric-Based Scalar Indicator

“…The model proposed by Rosenkranz [31], [32] for gaseous absorption has been used in applying the radiative transfer scheme and the cloud model in [33] was used to generate cloud liquid water profiles. The resulting database contains 6469 profiles and it spans the entire range of the expected path delay, water vapor, and cloud liquid water conditions.…”

The role of both location and radiometer accuracy on the SSI performance in discriminating the atmospheric conditions

“…To this purpose a RAOB dataset (see Tab. 1) was employed to compute simulated T b (f) values through the MPM91 using the Rosenkranz model [Rosenkranz, 1999] to calculate the gaseous absorptions, and the modified Salonen model [Salonen and Uppala, 1991] for the non precipitating cloud contributions [Mattioli et al, 2009]. Thanks to a proper set of retrieval coefficients, the integrated water vapour (IWV) and the non precipitating cloud liquid path (LWP) were computed from simulated T b (f) values, associated with each RAOB profile for the three sites [Fionda et al, 2008].…”

“…These latter are candidate to be among the nodes of the European Alphasat ground-segment. Specifically, all the analysis discussed hereafter are based on simulated T b (f) values computed by using a radiative transfer forward model (MPM91) [Liebe et al, 1991] also including a microphysical-consistent non-precipitating 2D cloud structure model [Salonen and Uppala, 1991;Mattioli et al, 2009], applied to each radiosonde profile (RAOB) collected during 2002-2008 in the selected sites. As a result of the study, the coefficient for the computation of SSI is expressed as a linear function of the air mass (mean elevation angles), for each of the selected sites.…”

Atmospheric attenuation at 100 and 300 GHz estimated with radiosonde data

“…Therefore, assuming this regime, cloud attenuation caused by water droplets is linearly related to the liquid water content. The calculation of this parameter, as well as the detection of cloud layers, can be achieved using cloud identification algorithms, well detailed in the literature [9]- [11], based on data extracted from vertical meteorological profiles.…”