Space-born Radiometer Observations during Shallow Precipitation Events

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Abstract

Observations retrieved from radiometers aboard several satellites are
combined in the Global Precipitation Measurement mission (GPM) to
provide a global precipitation dataset. Radiometers are able to sense
the radiance naturally emitted by the Earth's surface or
emitted/scattered by hydrometeors. These observations, also known as
brightness temperatures, are converted into precipitation estimates by
the GPM Profiling Algorithm (GPROF). Although this algorithm is already
in use for several decades and the conversion of brightness temperatures
to precipitation estimates in general has been studied extensively,
persistent challenges remain. Two of these challenges are: 1. the
retrieval of precipitation formed close to the Earth’s surface, also
referred to as shallow precipitation, and 2. low-intensity
precipitation. Increased understanding of the physics behind these
precipitation types will help to improve the accuracy of the conversion
of brightness temperatures to precipitation.
This study couples observations from radiometers to both ground-based
precipitation observations and reflectivity profiles from ground-based
weather radars over the Netherlands. The Netherlands is an ideal study
area for this purpose as both precipitation types (shallow and
low-intensity) occur regularly over the Netherlands (~52°N)
and high-quality (gauge-adjusted) radar data is available. We use
brightness temperatures from conical scanning radiometers belonging to
the GPM in this study. Firstly, we investigate the relationship between
brightness temperatures from different channels (frequency-dependent)
and precipitation intensities. Within this analysis we try to take the
effect of different footprint sizes of the different channels (related
to the differences in the employed radio frequencies) into account, in
order to limit the dependence of the retrieved relations on the
footprint size. Secondly, we couple the observations of the radiometers
with ground-based radar reflectivity profiles to gain insight in the
vertical structure of the precipitation types and how these affect
brightness temperatures.