396
Multiscale Hydrologic Remote Sensing: Perspectives and Applications
where k is the specific attenuation, Z is the reflectivity factor, and α and β are known
parameters. In addition to the power-law dependence, β has to be constant in range
for the Hitschfeld and Bordan methodology to apply. Grecu et al. (2011) showed that
Equation 16.6, with being β constant, does not have to be satisfied if an iterative solution of an implicit equation is derived. Specifically, a constant in range parameter β
can be determined such that k = α/Z β is a weak function of Z in an implicit equation.
In summary, the formulation in Equation 16.3 is general and allows for the deri6.3 is general and allows for the deri.3 is general and allows for the derivation of improved estimates of precipitation over land. Improvements are not likely
to originate in better methodologies to combine the satellite information but in better
interpretation of satellite information through more accurate and computational effective physical models. The methodology of Grecu and Olson (2006) can be used to attach
latent heating profiles to the retrieved precipitation profiles. Specifically, cloud-resolving
model simulations can be used to create lookup tables of the mean latent heating vertical
structure and surface precipitation rate. The model heating vertical profiles and surface
precipitation rates can be sorted by convective–stratiform classification, and the radar
echo top and mean model heating profiles and surface rain rates can be calculated and
tabulated as functions of the convective–stratiform class and the radar echo top. Given
the convective–stratiform classification and the echo-top height, the corresponding
tabulated heating profile can be extracted and rescaled by the combined surface precipitation rate estimate. The improved solid-phase precipitation estimates can be used
to filter out inappropriate cloud model simulations. That is, given that the most recent
CRMs (e.g., the Weather Research and Forecasting Model) feature several microphysical schemes, the microphysical schemes producing solid-phase hydrometeors statistically inconsistent with the combined retrievals can be eliminated from the latent heating
database. Thus, more realistic latent heating lookup tables can be derived, which will
facilitate the improvement of the latent heating estimates.
16.4 CONCLUSIONS
In this study, the problem of retrieving precipitation over land from spaceborne
combined radar and radiometer observations is considered. Combined retrievals
are deemed superior to radar-only retrievals, but the utility of combined retrievals
over land has not been fully assessed yet. Difficulties are expected to arise due to
the high emissivity of land. A sensitivity analysis is performed to assess the main
cause of variability in 85-GHz brightness temperatures in precipitating clouds. It is
found that the 85-GHz brightness temperatures are mostly sensitive to the amount of
hydrometeors above the freezing level. This is an indication that 85-GHz brightness
temperatures can be used to improve the accuracy of both solid- and liquid-phase
estimates relative to radar-only retrievals. A general combined retrievals methodology is presented in the chapter. The use of 3-D radiative transfer models and efficient
computational methodologies are likely to facilitate more accurate combined retrievals. In particular, the determination of the radiative transfer model Jacobian at the
same time with the brightness temperatures along with a more flexible radar profile
algorithm is expected to positively affect the retrievals.
The derivation of combined radar–radiometer precipitation retrievals from overland GPM observations can facilitate the development of physically consistent
Multiscale Hydrologic Remote Sensing: Perspectives and Applications
where k is the specific attenuation, Z is the reflectivity factor, and α and β are known
parameters. In addition to the power-law dependence, β has to be constant in range
for the Hitschfeld and Bordan methodology to apply. Grecu et al. (2011) showed that
Equation 16.6, with being β constant, does not have to be satisfied if an iterative solution of an implicit equation is derived. Specifically, a constant in range parameter β
can be determined such that k = α/Z β is a weak function of Z in an implicit equation.
In summary, the formulation in Equation 16.3 is general and allows for the deri6.3 is general and allows for the deri.3 is general and allows for the derivation of improved estimates of precipitation over land. Improvements are not likely
to originate in better methodologies to combine the satellite information but in better
interpretation of satellite information through more accurate and computational effective physical models. The methodology of Grecu and Olson (2006) can be used to attach
latent heating profiles to the retrieved precipitation profiles. Specifically, cloud-resolving
model simulations can be used to create lookup tables of the mean latent heating vertical
structure and surface precipitation rate. The model heating vertical profiles and surface
precipitation rates can be sorted by convective–stratiform classification, and the radar
echo top and mean model heating profiles and surface rain rates can be calculated and
tabulated as functions of the convective–stratiform class and the radar echo top. Given
the convective–stratiform classification and the echo-top height, the corresponding
tabulated heating profile can be extracted and rescaled by the combined surface precipitation rate estimate. The improved solid-phase precipitation estimates can be used
to filter out inappropriate cloud model simulations. That is, given that the most recent
CRMs (e.g., the Weather Research and Forecasting Model) feature several microphysical schemes, the microphysical schemes producing solid-phase hydrometeors statistically inconsistent with the combined retrievals can be eliminated from the latent heating
database. Thus, more realistic latent heating lookup tables can be derived, which will
facilitate the improvement of the latent heating estimates.
16.4 CONCLUSIONS
In this study, the problem of retrieving precipitation over land from spaceborne
combined radar and radiometer observations is considered. Combined retrievals
are deemed superior to radar-only retrievals, but the utility of combined retrievals
over land has not been fully assessed yet. Difficulties are expected to arise due to
the high emissivity of land. A sensitivity analysis is performed to assess the main
cause of variability in 85-GHz brightness temperatures in precipitating clouds. It is
found that the 85-GHz brightness temperatures are mostly sensitive to the amount of
hydrometeors above the freezing level. This is an indication that 85-GHz brightness
temperatures can be used to improve the accuracy of both solid- and liquid-phase
estimates relative to radar-only retrievals. A general combined retrievals methodology is presented in the chapter. The use of 3-D radiative transfer models and efficient
computational methodologies are likely to facilitate more accurate combined retrievals. In particular, the determination of the radiative transfer model Jacobian at the
same time with the brightness temperatures along with a more flexible radar profile
algorithm is expected to positively affect the retrievals.
The derivation of combined radar–radiometer precipitation retrievals from overland GPM observations can facilitate the development of physically consistent