PRECIPITATION REMOTE SENSING
BASED ON SPACE-BORNE MULTI-FREQUENCY MICROWAVE RADIOMETRY
P. BASILI 1 , P. CIOTTI 2 , F.S. MARZANO 3 , N. PIERDICCA 3 , M. ALBERTONE 3
'Istituto di Elettronica, University of Perugia.
Santa Lucia, 06143 Perugia, Italy
2 Dipartimento di Ingegneria Elettrica, University of L'Aquila,
Poggio di Roio, 67040 L'Aquila, Italy
3 Dipartimento di Ingegneria Elettronica, University 'La Sapienza"of Roma
Via Eudossiana 18, 00184 Roma; Italy
ABSTRACT:
A processing technique for precipitation retrieval using satellite multi-frequency brightness temperature
measurements is illustrated. Microwave signature of precipitation is analyzed for a convective cloud system
over the Italian peninsula, observed by the Special Sensor Microwave / Imager. Image resolution enhancing
and a technique for identifying rainfall areas through a double-clustering discriminant algorithm are applied to
space-borne radiometer data. The surface rain-rate retrieval is performed on a pixel base by means of a
max imum likelihood algorithm trained on a simulated cloud-radiation dataset. Finally, the application of the
retrieval algorithm to a r ainfall event over Liguria is shown and discussed.
KEY WORDS: Space-borne remote sensing. Microwave radiometry. Precipitation retrieval
1 - INTRODUCTION
The use of space-borne microwave radiometers for monitoring precipitation on a global scale has received an
increasing attention in the last years, due to the launch at the beginning of 1987 of the Defense Meteorological
Satellite Program (DMSP) platform carrying on the Special Sensor Microwave / Imager (SSM/I). A great
amount of multi-frequency brightness temperature data has been made available to the microwave remote
sensing community (Hollinger et al„ 1989). Unfortunately, the scarcity of in situ meteorological data,
concerning cloud systems and precipitation, makes it necessary to tackle the problem through cloud and
radiative transfer models. Over the past decades, many studies have been made to delineate modeling
frameworks for interpreting microwave observations of precipitating clouds from space (Wilheit et al., 1977),
(Spencer et al., 1989), (Smith et al., 1992). The aim is the retrieval of relevant cloud parameters, regarding
especially hydrometeors in iced and liquid phases, and the surface rainfall rate (Mugnai et al., 1993).
In this work, the use of SSM/I measurements over the Mediterranean area has allowed us to
test the potential of a simulated cloud-radiation dataset, that includes a large number of simulated precipitating
clouds and their related brightness temperatures (Tb's). The major feature of this cloud-radiation dataset is the
consideration of the correlations among the various hydrological parameters, characterizing the vertical cloud
structure. The simulated space-borne Tb's have been computed through a discrete-ordinate radiative transfer,
both over sea and land surfaces. The inversion algorithm has been developed with the objective of estimating
the vertical distribution of the liquid and iced hydrometeor contents, and the associate surface rain rate. The
surface rain-rate retrieval is performed on a pixel-base by means of a maximum likelihood criterion, used to
select the most probable cloud structure within the simulated cloud-radiation dataset. The estimation
procedure has been applied to SSM/I data after having identified the actual precipitating area through a
double-clustering technique. A comparison of the retrieval results with the rainfall rates measured by a rain-
gauge network during an intense storm detected in September 1992 over Liguria (Italy) has been carried out.
2 - CLOUD AND RADIATIVE TRANSFER MODELING
Modeling the precipitating cloud structures and their related brightness temperatures has allowed us to
generate a large cloud-radiation dataset. This is crucial for understanding the microwave radiative transfer
properties through precipitating atmospheres and for tr aining the retrieval algorithm.
