The Detection of Autoconversion Processes in Clouds using Ground-Based Passive and Active Microwave Sensors

This project deals with the study of autoconversion process, that is the process of transition between cloud droplets and precipitation: many connected open problems are currently object of study from the scientific community, like for example the need to be able to retrieve LWC for situations in which drizzle and cloud droplets are both present, the necessity to understand under which conditions clouds begin to precipitate and which are the corresponding threshold values for the onset of precipitation for LWP and other important variables. The aim of this PHD is therefore to try to study the process of formation of precipitation and derive such thresholds, verifying if they are consistent with models. Initially, the fellow will analyse LWP values with respect to the onset of precipitation as identified from different sources, then the analysis of temporal developments of Doppler spectra and its higher Doppler moments will be performed in order to identify thresholds values indicative of certain processes. Then, the results obtained will be implemented in the algorithm in order to improve the retrievals.

1) JOYCE: Jülich Observatory for Cloud Evolution, U. Löhnert, J. H. Schween, C. Acquistapace, K. Ebell, M. Maahn, M. Barreraverdejo, A. Hirsikko, B. Bohn, A. Knaps, E. O'connor, C. Simmer, A. Wahner, S. Crewell, Bulletin of the American Meteorological Society, Volume 0, Issue 0 ( ) pp.

Abstract

Full paper (PDF)

2) Satellite-based VIS/IR multispectral screening of precipitating clouds: A case study during summer at mid-latitudes, Elsa Cattani, Claudia Acquistapace, Sante Laviola, and Vincenzo Levizzani, CNR-ISAC, Bologna, Italy, Geophysical Research Abstracts, Vol. 15, EGU2013-PREVIEW , 2013, EGU General Assembly 2013

abstract

Project: what's going on (time line)

1) Analysis of case studies: searching for new observables to be used in detecting drizzle onset.

-Two hours of data are shown below: the first one is taken from a drizzling case study, the other one taken from a non drizzling case study. 2D scatter plots of skewness vs reflectivity of cloud radar doppler spectra are shown with colors assigned depending on the height between cloud base and cloud top. Skewness pattern shows different features in the two cases.

Drizzling hour:

Non drizzling hour:

-Analysis of four different case studies: non drizzling 20131008, 20130610, drizzling 20130105, 20131009. Populations of STD(LWP), vertical gradient of reflectivity, Mean Doppler velocity and Reflectivity are shown.

2) (first year activities) Detection of drizzle onset using current operational tools (Cloudnet).

Statistical analysis of a liquid clouds dataset: populations of rainy and non rainy clouds analyzed as a function of different variables: first results

1) histograms of distributions of rainy and non rainy clouds as a function of LWP

2) histograms of distributions of rainy and non rainy clouds as a function of geometrical depth

3) 2d probability of having rain as a function of LWP and geometrical depth: plotted are the cases in which the probability is smaller than 30 %

4) 2d probability of having rain as a function of LWP and geometrical depth: plotted are the cases in which the probability is bigger than 60 %