The scientific goal of this study is to improve our understanding of the small-scale variability of rainfall. This goal is motivated by the need to develop a mechanistic understanding of the linkage between rainfall variability and land surface processes. A related goal is development of procedures for estimating rainfall rate from weather radar and rain gage observations at small time and space scales, i.e. the spatial and temporal scales for which the governing equations for land surface processes are developed. These scales are quite different from those that have been conventionally been employed for radar rainfall estimation. Using analytical, computational, and observational tools, the team proposes to address the following scientific questions: How do storm structure, storm motion, and storm evolution determine the observed variability and scaling properties of rainfall? What are the physical processes that control the distributional properties of rainfall rate? What are the dominant physical processes that are responsible for uncertainty in radar-rainfall estimates? What is the scaling structure of rainfall at scales below 2 km (a typical spatial scale for conventional radar rainfall estimates) and is it consistent with that observed at scales greater than 2 km? If there are changes in rainfall scaling below 2 km, what physical processes are responsible for breaks in the scaling? The group will examine these questions through a coordinated program of field measurements, data analysis, and statistical modeling. Lagrangian and Eulerian representations of variability of rainfall from multicell thunderstorm systems will be utilized for addressing the research questions. The field sites will be located in eastern Iowa (Iowa City), northern Mississippi (Goodwin Creek experimental watershed) and Baltimore. The investigators have developed experimental programs at these locations that incorporate observations from dense rain gage networks, the National Weather Service WSR-88D radars, disdrometers (for raindrop size distributions), and research radars. These observational resources will be enhanced through field campaigns in Iowa and Baltimore. The intellectual merit of the proposed work centers on elucidating the structure of rainfall rate fields at spatial and temporal scales important to land surface hydrologic processes. The broader impacts include advancing discovery while promoting teaching, training and learning; providing research opportunities for underrepresented groups, enhancing the infrastructure for research and education; and broad dissemination of experimental and analytical results. The proposed research will provide students with an exceptional opportunity to develop expertise in hydrologic technology, especially through participation in field experiments. The proposed work will also provide important insights to the measurement technology needed for hydrologic experimentation, especially as envisioned under the CUAHSI (Consortium of Universities for the Advancement of Hydrologic Science, Inc.) initiatives. The benefits for society will be through improvements in remote sensing of rainfall, which will lead to better prediction and control of water resources systems, and timely warnings against natural hazards such as floods, landslides, and hurricanes.
