Poster Summaries
603
layer clouds were seperated by a threshold in the standard deviation field of the IR image.
Comparisons with surface observations and visual analysis were encouraging.
Michelson et al.: Image processing methods were applied to identify and suppress undesired
effects in C-band weather radar imagery. The first method removes echoes that are static in
time and space, using a time series of images. The second method uses a radial wind velocity
image from Doppler radar to remove precipitation echoes that are not matched with wind
information.
Booysen and Teuter: Ground radar and Meteosat image data were used to develop a procedure that produces daily rainfall maps over South Africa. This system is based on the
assumption that rain rate is proportional to cloud depth. Cloud depth is determined from
satellite image data in terms of the difference in temperature pixels between cloud top and
cloud base. Rain-rates are determined from ground radar data on a 2000 m Constant Altitude
Plan Position Indicator (CAPPI). A cloud classification scheme is used to assign the satellite
imagery to rainfall criteria. Statistical relationships between cloud depth and rain rates are
then determined which are used to compile rainfall maps by using Meteosat image data alone.
Jones: A new precipitation climatology for the tropical oceans has been developed, using
available observations of rainfall from atoll stations, and mean Outgoing Longwave Radiation
(OLR) flux measurements. The climatology spans the period June 1974 to November 1994,
and is a gridded dataset of monthly precipitation accumulations, at a spatial resolution of 2.5 0
of latitude and longitude.
To close our presentation, we illustrated the scope of our projects on a chart of remote sensing
measurements required for continuing studies, and invited our friends in the audience to fill in
the blanks during the remainder of the week.
Bennartz R
A semi-statistical approach for cloud and rain identification using SSM/I and SSM/T2 data
Booysen RG, Teuter MT
A real time rainfall remote sensing system
Dioszeghy M, Fejes E
Cloud classification derived from METEOSAT data involving the standard deviation fields of
the brightness values
Fiig C
Resolution enhancement of microwave observations over the baltic sea
Jones C
Development of a tropical ocean precipitation climatology from OLR flux measurements
Lemke H, Oldag J
Theoretical studies for remote sensing with a 95 GHz radar
Michelson DB, Anderson T, Haggemark L
Precipitation analysis with radar effects of anomalous propagation echoes
Oury S, Testud J, Kabeche A
The stereoradar analysis
Simpson P
Dual-wavelength radar estimate of ice particle size
603
layer clouds were seperated by a threshold in the standard deviation field of the IR image.
Comparisons with surface observations and visual analysis were encouraging.
Michelson et al.: Image processing methods were applied to identify and suppress undesired
effects in C-band weather radar imagery. The first method removes echoes that are static in
time and space, using a time series of images. The second method uses a radial wind velocity
image from Doppler radar to remove precipitation echoes that are not matched with wind
information.
Booysen and Teuter: Ground radar and Meteosat image data were used to develop a procedure that produces daily rainfall maps over South Africa. This system is based on the
assumption that rain rate is proportional to cloud depth. Cloud depth is determined from
satellite image data in terms of the difference in temperature pixels between cloud top and
cloud base. Rain-rates are determined from ground radar data on a 2000 m Constant Altitude
Plan Position Indicator (CAPPI). A cloud classification scheme is used to assign the satellite
imagery to rainfall criteria. Statistical relationships between cloud depth and rain rates are
then determined which are used to compile rainfall maps by using Meteosat image data alone.
Jones: A new precipitation climatology for the tropical oceans has been developed, using
available observations of rainfall from atoll stations, and mean Outgoing Longwave Radiation
(OLR) flux measurements. The climatology spans the period June 1974 to November 1994,
and is a gridded dataset of monthly precipitation accumulations, at a spatial resolution of 2.5 0
of latitude and longitude.
To close our presentation, we illustrated the scope of our projects on a chart of remote sensing
measurements required for continuing studies, and invited our friends in the audience to fill in
the blanks during the remainder of the week.
Bennartz R
A semi-statistical approach for cloud and rain identification using SSM/I and SSM/T2 data
Booysen RG, Teuter MT
A real time rainfall remote sensing system
Dioszeghy M, Fejes E
Cloud classification derived from METEOSAT data involving the standard deviation fields of
the brightness values
Fiig C
Resolution enhancement of microwave observations over the baltic sea
Jones C
Development of a tropical ocean precipitation climatology from OLR flux measurements
Lemke H, Oldag J
Theoretical studies for remote sensing with a 95 GHz radar
Michelson DB, Anderson T, Haggemark L
Precipitation analysis with radar effects of anomalous propagation echoes
Oury S, Testud J, Kabeche A
The stereoradar analysis
Simpson P
Dual-wavelength radar estimate of ice particle size