Improving Hurricane Intensity and Streamflow Forecasts in Coupled Hydrometeorological Simulations by Analyzing Precipitation and Boundary Layer Schemes

Hurricanes have been the most destructive and expensive hydrometeorological event in U.S. history, causing catastrophic winds and fl oods. Hurricane dynamics can significantly fi cantly impact the amount and spatial extent of storm precipitation. However, the complex interactions of hurricane intensity and precipitation and the impacts of improving hurricane dynamics on streamflow fl ow forecasts are not well established yet. This paper addresses these gaps by comprehensively characterizing the role of vertical diffusion in improving hurricane intensity and streamflow fl ow forecasts under different planetary boundary layer, microphysics, and cumulus parameterizations. To this end, the Weather Research and Forecasting (WRF) atmospheric model is coupled with the WRF hydrological (WRF-Hydro) model to simulate four major hurricanes landfalling in three hurricane-prone regions in the United States. First, a stepwise calibration is carried out in WRF-Hydro, which remarkably reduces streamflow fl ow forecast errors compared to the U.S. Geological Survey (USGS) gauges. Then, 60 coupled hydrometeorological simulations were conducted to evaluate the performance of current weather parameterizations. All schemes were shown to underestimate the observed intensity of the considered major hurricanes since their diffusion is overdissipative for hurricane fl ow simulations. By reducing the vertical diffusion, hurricane intensity forecasts were improved by-39.5% on average compared to the default models. These intensified fi ed hurricanes generated more intense and localized precipitation forcing. This enhancement in intensity led to-16% and-34% improvements in hurricane streamflow fl ow bias and correlation forecasts, respectively. The research underscores the role of improved hurricane dynamics in enhancing fl ood predictions and provides new insights into the impacts of vertical diffusion on hurricane intensity and streamflow fl ow forecasts. SIGNIFICANCE STATEMENT: Despite significant fi cant recent improvements, numerical weather prediction models struggle to accurately forecast hurricane intensity and track due to many reasons such as inaccurate physical parameterization for hurricane fl ows. Furthermore, the performance of existing physics schemes is not well studied for hurricane fl ood forecasting. This study bridges these knowledge gaps by extensively evaluating different physical parameterizations for hurricane track, intensity, and fl ood forecasts using an atmospheric model coupled with a hydrological model. Then, a reduced diffusion boundary layer scheme is developed, making remarkable improvements in hurricane intensity forecasts due to the overdissipative nature of the considered schemes for major hurricane simulations. This reduced diffusion model is shown to significantly fi cantly enhance hurricane fl ood forecasts, indicating the significance fi cance of hurricane dynamics on its induced precipitation.