A hydrometeorologic forecast system (HFS) has been developed that takes adv
antage of new high-resolution rainfall datasets from the WSR-88D radar syst
em, the Oklahoma Mesonet, and Oklahoma Local Analysis and Prediction System
(OLAPS). New schemes to analyze precipitation and to adjust radar rainfall
rates have been proposed to improve the quantitative precipitation forecas
t (QPF) for hydrologic purposes. Adjusted WSR-88D rainfall rates were advec
ted by the 700-mb wind field from OLAPS to produce an extrapolation QPF Sev
eral experiments were conducted to evaluate the effect of the rainfall adju
stment and wind field upon the extrapolation QPF. In addition, mesoscale mo
del-produced QPFs were generated using The Pennsylvania State University-Na
tional Center for Atmospheric Research Mesoscale Model. Control and rainfal
l assimilation experiments were performed using both Kuo and Kain-Fritsch c
umulus parameterization schemes for three rainfall events from April 1994.
All model runs were integrated forward 12 h and then verified against the a
nalyzed precipitation held.
Both the extrapolation and model-produced QPFs were used to produce hydrolo
gic forecasts for the Dry Creek watershed in north-central Oklahoma. Result
s indicate that extrapolation QPFs degrade exponentially with time and beco
me inferior to the QPF from a mesoscale model after 2 h. When the extrapola
ted rainfall estimates were input into a hydrologic model, an underestimate
of the peak flow occurred since the time evolution of precipitating system
s is not handled by extrapolation. Due to the lag time between the peak in
precipitation and the peak in streamflow, the greatest impact upon the accu
racy of hydrologic forecasts resulted from improvements in the analyzed pre
cipitation field.
On the Ether hand, mesoscale forecast simulations revealed that the assimil
ation of analyzed rainfall had a limited impact upon the evolution of model
-produced precipitation forecasts out to 4 h. However, model-produced QPFs
improved after 8 h into the integration. While the Kuo scheme produced less
dispersion error, the Kain-Fritsch scheme created less amplitude error. Th
e assimilation of analyzed rainfall through the convergence factor of the K
uo scheme had a greater impact upon the performance of the mesoscale model
than did the Kain-Fritsch rainfall assimilation through the adjustment of i
ts precipitation efficiency factor. Therefore, re new generation HFS has be
en developed to take advantage of new technology and new scientific methods
in an attempt to mitigate the age-old issue of devastating floods that occ
ur without warning. Each component has been tested and evaluated. The resul
ts of testing and evaluating each component of the proposed HFS are present
ed in this paper.