Hydrological aspects of weather prediction and flood warnings: Report of the Ninth Prospectus Development Team of the US Weather Research Program

Among the many natural disasters that disrupt human and industrial activity in the United States each year, including tornadoes, hurricanes, extreme t emperatures, and lightning, floods are among the most devastating and rank second in the loss of life. Indeed, the societal impact of floods has incre ased during the past few years and shows no sign of abating. Although the s cientific questions associated with flooding and its accurate prediction ar e many and complex, an unprecedented opportunity now exists-in light of new observational and computing systems and infrastructures, a much improved u nderstanding of small-scale meteorological and hydrological processes, and the availability of sophisticated numerical models and data assimilation sy stems-to attack the flood forecasting problem in a comprehensive manner tha t will yield significant new scientific insights and corresponding practica l benefits. The authors present herein a set of recommendations for advancing our under standing of floods via the creation of natural laboratories situated in a v ariety of local meteorological and hydrological settings. Emphasis is given to floods caused by convection and cold season events, fronts and extratro pical cyclones, orographic forcing, and hurricanes and tropical cyclones fo llowing landfall. Although the particular research strategies applied withi n each laboratory setting will necessarily vary, all will share the followi ng principal elements: (a) exploitation of those couplings important to flo oding that exist between meteorological and hydrological processes and mode ls; (b) innovative use of operational radars, research radars, satellites, and rain gauges to provide detailed spatial characterizations of precipitat ion fields and rates, along with the use of this information in hydrologica l models and for improving and validating microphysical algorithms in meteo rological models; (c) comparisons of quantitative precipitation estimation algorithms from both research (especially multiparameter) and operational r adars against gauge data as well as output produced by meso- and storm-scal e models; (d) use of data from dense, temporary river gauge networks to tra ce the fate of rain from its starting location in small basins to the entir e stream and river network; and (e) sensitivity testing in the design and i mplementation of separate as well as coupled meteorological and hydrologic models, the latter designed to better represent those nonlinear feedbacks b etween the atmosphere and land that are known to play an important role in runoff prediction. Vital to this effort will be the creation of effective and sustained linkag es between the historically separate though scientifically related discipli nes of meteorology and hydrology, as well as their observational infrastruc tures and research methodologies.