Mesoscale Precipitation Fields. Part II: Hydrometeorologic Modeling

Abstract

A hydrometeorologic forecast system (HFS) has been developed that takes advantage of new high-resolution rainfall datasets from the WSR-88D radar system, 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 forecast (QPF) for hydrologic purposes. Adjusted WSR-88D rainfall rates were advected by the 700-mb wind field from OLAPS to produce an extrapolation QPF. Several experiments were conducted to evaluate the effect of the rainfall adjustment and wind field upon the extrapolation QPF. In addition, mesoscale model?produced QPFs were generated using The Pennsylvania State University?National Center for Atmospheric Research Mesoscale Model. Control and rainfall assimilation experiments were performed using both Kuo and Kain?Fritsch cumulus parameterization schemes for three rainfall events from April 1994. All model runs were integrated forward 12 h and then verified against the analyzed precipitation field. Both the extrapolation and model-produced QPFs were used to produce hydrologic forecasts for the Dry Creek watershed in north-central Oklahoma. Results indicate that extrapolation QPFs degrade exponentially with time and become inferior to the QPF from a mesoscale model after 2 h. When the extrapolated rainfall estimates were input into a hydrologic model, an underestimate of the peak flow occurred since the time evolution of precipitating systems 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 accuracy of hydrologic forecasts resulted from improvements in the analyzed precipitation field. On the other hand, mesoscale forecast simulations revealed that the assimilation 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. The assimilation of analyzed rainfall through the convergence factor of the Kuo scheme had a greater impact upon the performance of the mesoscale model than did the Kain?Fritsch rainfall assimilation through the adjustment of its precipitation efficiency factor. Therefore, a new generation HFS has been developed to take advantage of new technology and new scientific methods in an attempt to mitigate the age-old issue of devastating floods that occur without warning. Each component has been tested and evaluated. The results of testing and evaluating each component of the proposed HFS are presented in this paper.