This study evaluated rainfall estimates from ground radar network and four satellite algorithms with a
relatively dense rain gauge network over Taiwan Island for the 2009 extreme Typhoon Morakot at various
spatiotemporal scales (from 0.04 to 0.25 and hourly to event total accumulation). The results show that
all the remote-sensing products underestimate the rainfall as compared to the rain gauge measurements,
in an order of radar (18%), 3B42RT (19%), PERSIANN-CCS (28%), 3B42V6 (36%), and CMORPH (61%).
The ground radar estimates are also most correlated with gauge measurements, having a correlation
coefficient (CC) of 0.81 (0.82) at 0.04 (0.25) spatial resolution. For satellite products, CMORPH has
the best spatial correlation (0.70) but largely underestimates the total rainfall accumulation. Compared
to microwave ingested algorithms, the IR-dominant algorithms provide a better estimation of the total
rainfall accumulation but poorly resolve the temporal evolution of the warm cloud typhoon, especially
for a large overestimation at the early storm stage. This study suggests that the best performance comes
from the ground radar estimates that could be used as an alternative in case of the gauge denial. However,
the current satellite rainfall products still have limitations in terms of resolution and accuracy, especially
for this type of extreme typhoon.
2012