262
C. Simmer
Three techniques have been decribed to increase the quality and flexibility of the GPI:
Microwave Adjusted GPI: The constant of proportionality a is assumed to be a function of
longitude and latitude and computed by a = RR(SSM/I)/RR(GPI) from monthly coincidences
of the DMSP and GMS-satellites (Adler et al., 1993).
NAWT (Negri-Adler Wetzel-Technique): In a first step the area of raining clouds is
defined by Tc < 235K. For the coldest 10% of the cloud the rain rate is assumed to be 8 mm/h;
for the next warmest 40% of the cloud area 2 mm/h is assumed, and the rest of the area is
assumed to be covered with non-raining clouds (Negri et al., 1984; Negri and Adler, 1993).
CST (Convective-Stratiform Technique): The area of raining clouds is defined by Tc <
235K. For this area the relative minima in cloud-top temperature distribution and the slopes
of the cloud-top temperature in the vicinity of the minima are determined. It follows a division
into stratiform (2 mm/h assumed rainrate) and convective rain (8 mm/h assumed rainrate)
using both qualifiers (Adler and Negri, 1988; 1993).
11.6.2 Microwaves
In the microwave spectral region the radiances are more directly related to the hydrometeors
in the satellite field of view. Contrary to the visible and infrared spectral region the whole
state of the atmosphere decribed by the vertical profiles of temperature, water vapour, cloud
and rain liquid and ice profiles, and the shape of the particles determine the outgoing radiances
at the top of the atmosphere. So any parameter retrieval is at least partially an inversion of
the radiative transfer equation. Concerning rain basically three paths have been followed to
construct rain retrieval algorithms:
Complete Inversion: A complete description of the state of the atmosphere is sought which,
by feeding its physical description into the equation of radiative transfer, results into radiances
sufficiently close to the measured radiances to be inverted.
Statistical Inversion: A functional relation is sought between the radiances and the desired
parameter. This function may be linear or non-linear.
Indexing: By physical reasoning indices are derived from the radiances which can be related
to the effect of precipitation, like the transmission of the atmosphere or the effect scattering by
upper ice particles has on the radiances. The relation between these indices and the rain rate
is determined by assumptions about the structure of the hydrometeor profiles.
Published rain rate retrieval algorithms can seldomely be associated with only one of these
paths. The number of variables influencing the radiances is far greater than the number of
spectral channels available for inversion. In complete inversion algorithms the reduction of
unknowns is achieved by making assumptions about the structure of the profiles of temperature,
humidity, and hydrometeors. These assumptions are mostly extracted from statistical analysis.
Indexing methods are subject to similar restrictions when the relations between the indices and
the rain rate is determined. In the following paragraphs examples for each class of will be given.
11.6.3 Complete inversion
A prerequisite for a complete inversion algorithm is a radiative transfer model. The algorithm searches for a state of the atmosphere which reproduces up to the assumed error of the
radiometer the measured radiances. Two principles can be followed to achieve this goal:
• Newton iteration
C. Simmer
Three techniques have been decribed to increase the quality and flexibility of the GPI:
Microwave Adjusted GPI: The constant of proportionality a is assumed to be a function of
longitude and latitude and computed by a = RR(SSM/I)/RR(GPI) from monthly coincidences
of the DMSP and GMS-satellites (Adler et al., 1993).
NAWT (Negri-Adler Wetzel-Technique): In a first step the area of raining clouds is
defined by Tc < 235K. For the coldest 10% of the cloud the rain rate is assumed to be 8 mm/h;
for the next warmest 40% of the cloud area 2 mm/h is assumed, and the rest of the area is
assumed to be covered with non-raining clouds (Negri et al., 1984; Negri and Adler, 1993).
CST (Convective-Stratiform Technique): The area of raining clouds is defined by Tc <
235K. For this area the relative minima in cloud-top temperature distribution and the slopes
of the cloud-top temperature in the vicinity of the minima are determined. It follows a division
into stratiform (2 mm/h assumed rainrate) and convective rain (8 mm/h assumed rainrate)
using both qualifiers (Adler and Negri, 1988; 1993).
11.6.2 Microwaves
In the microwave spectral region the radiances are more directly related to the hydrometeors
in the satellite field of view. Contrary to the visible and infrared spectral region the whole
state of the atmosphere decribed by the vertical profiles of temperature, water vapour, cloud
and rain liquid and ice profiles, and the shape of the particles determine the outgoing radiances
at the top of the atmosphere. So any parameter retrieval is at least partially an inversion of
the radiative transfer equation. Concerning rain basically three paths have been followed to
construct rain retrieval algorithms:
Complete Inversion: A complete description of the state of the atmosphere is sought which,
by feeding its physical description into the equation of radiative transfer, results into radiances
sufficiently close to the measured radiances to be inverted.
Statistical Inversion: A functional relation is sought between the radiances and the desired
parameter. This function may be linear or non-linear.
Indexing: By physical reasoning indices are derived from the radiances which can be related
to the effect of precipitation, like the transmission of the atmosphere or the effect scattering by
upper ice particles has on the radiances. The relation between these indices and the rain rate
is determined by assumptions about the structure of the hydrometeor profiles.
Published rain rate retrieval algorithms can seldomely be associated with only one of these
paths. The number of variables influencing the radiances is far greater than the number of
spectral channels available for inversion. In complete inversion algorithms the reduction of
unknowns is achieved by making assumptions about the structure of the profiles of temperature,
humidity, and hydrometeors. These assumptions are mostly extracted from statistical analysis.
Indexing methods are subject to similar restrictions when the relations between the indices and
the rain rate is determined. In the following paragraphs examples for each class of will be given.
11.6.3 Complete inversion
A prerequisite for a complete inversion algorithm is a radiative transfer model. The algorithm searches for a state of the atmosphere which reproduces up to the assumed error of the
radiometer the measured radiances. Two principles can be followed to achieve this goal:
• Newton iteration