| Recently, a number of investigations have been made that point to the robust
effectiveness of the Ensemble Kalman Filter (EnKF) in convective-scale data
assimilation. These studies have focused on the assimilation of ground-based
Doppler radar observations (i.e. radial velocity and reflectivity). The
present study differs from these investigations in two important ways.
First, in anticipation of future satellite technology, the impact of
assimilating spaceborne Doppler-retrieved vertical velocity is examined;
second, the potential for the EnKF to provide an alternative to
instrument-based microphysical retrievals is investigated.
It is shown that the RMS errors of the analyzed fields produced by
assimilation of vertical velocity alone are in general better than those
obtained in previous studies: in most cases assimilation of vertical
velocity alone leads to analyses with small errors (e.g. <1 ms-1 for
velocity components) after only 3 or 4 assimilation cycles. The
microphysical fields are notable exceptions, exhibiting lower errors when
observations of reflectivity are assimilated together with observations of
vertical velocity, likely a result of the closer relationship between
reflectivity and the microphysical fields themselves. It is also shown that
the spatial distribution of the error estimates improves (i.e. approaches the
true errors) as more assimilation cycles are carried out, which could be a
significant advantage of EnKF model-based retrievals. |