Luciana Cunha

NEXRAD NWS Polarimetric Precipitation Product Evaluation for IFloodS

AbstractThe NEXRAD program has recently upgraded the WSR-88D network observational capability with dual polarization (DP). In this study, DP quantitative precipitation estimates (QPEs) provided by the current version of the NWS system are evaluated using a dense rain gauge network and two other single-polarization (SP) rainfall products. The analyses are performed for the period and spatial domain of the Iowa Flood Studies (IFloodS) campaign. It is demonstrated that the current version (2014) of QPE from DP is not superior to that from SP mainly because DP QPE equations introduce larger bias than the conventional rainfall–reflectivity [i.e., R(Z)] relationship for some hydrometeor types. Moreover, since the QPE algorithm is based on hydrometeor type, abrupt transitions in the phase of hydrometeors introduce errors in QPE with surprising variation in space that cannot be easily corrected using rain gauge data. In addition, the propagation of QPE uncertainties across multiple hydrological scales is investig...

An Early Performance Evaluation of the NEXRAD Dual-Polarization Radar Rainfall Estimates for Urban Flood Applications

AbstractDual-polarization radars are expected to provide better rainfall estimates than single-polarization radars because of their ability to characterize hydrometeor type. The goal of this study is to evaluate single- and dual-polarization radar rainfall fields based on two overlapping radars (Kansas City, Missouri, and Topeka, Kansas) and a dense rain gauge network in Kansas City. The study area is located at different distances from the two radars (23–72 km for Kansas City and 104–157 km for Topeka), allowing for the investigation of radar range effects. The temporal and spatial scales of radar rainfall uncertainty based on three significant rainfall events are also examined. It is concluded that the improvements in rainfall estimation achieved by polarimetric radars are not consistent for all events or radars. The nature of the improvement depends fundamentally on range-dependent sampling of the vertical structure of the storms and hydrometeor types. While polarimetric algorithms reduce range effects...

Using Cellular Network Signal Strength to Monitor Vegetation Characteristics

We demonstrate a new application for cellular communications equipment in monitoring vegetation. We analyze how the vegetation in a cornfield affects the received signal power recorded at cell modems in the field, and we show that the received signal power exhibited long-term and diurnal patterns related to the properties of the vegetation biomass. A novel aspect of this letter is that we recorded the signal strength data at the cellular modem in the field rather than at a cell phone tower and therefore does not require the cooperation of the cell tower owner.

SIMULATION OF A DISTRIBUTED FLOOD CONTROL SYSTEM USING A PARALLEL ASYNCHRONOUS SOLVER FOR SYSTEMS OF ODES

A recently developed parallel asynchronous solver for systems of ordinary differential equations (ODEs) is used to simulate flows along the channels in a river network. In our model, precipitation is applied over the hillslopes adjacent to the river network links and water movement from hillsope to link and along the river network is represented as a system of ODEs. The numerical solver is based on dense output Runge-Kutta methods that allow for asynchronous integration. A static partition method is used to distribute the workload among different processes, enabling a parallel implementation that capitalizes on a distributed memory system. Communication between processes is performed asynchronously. We illustrate the solver capabilities by integrating flow transport equations for a 32,000 km 2 river basin subdivided into 574,000 sub-watersheds that are interconnected by the river network. We show that the runtime for an eight month-long simulation forced by 1-km resolution NEXRAD rainfall is completed in under 4 minutes using 64 computing nodes. In addition, we include equations to simulate small reservoirs spread throughout the river network and estimate changes in hydrographs at multiple locations. Our results provide a firm theoretical basis for the concept of distributed flood control systems.

The Regional Water Cycle and Heavy Spring Rainfall in Iowa: Observational and Modeling Analyses from the IFloodS Campaign

AbstractThe regional water cycle is examined with a special focus on water vapor transport in Iowa during the Iowa Flood Studies (IFloodS) campaign period, April–June 2013. The period had exceptionally large rainfall accumulations, and rainfall was distributed over an unusually large number of storm days. Radar-derived rainfall fields covering the 200 000 km2 study region; precipitable water from a network of global positioning system (GPS) measurements; and vertically integrated water vapor flux derived from GPS precipitable water, radar velocity–azimuth display (VAD) wind profiles, and radiosonde humidity profiles are utilized. They show that heavy rainfall is relatively weakly correlated with precipitable water and precipitable water change, with somewhat stronger direct relationships to water vapor flux. Thermodynamic properties tied to the vertical distribution of water vapor play an important role in determining heavy rainfall distribution, especially for periods of strong southerly water vapor flux...

Toward economic flood loss characterization via hazard simulation

Among all natural disasters, floods have historically been the primary cause of human and economic losses around theworld. Improving flood riskmanagement requires amulti-scale characterization of the hazard and associated losses—theflood loss footprint. But this is typically not available in a precise and timelymanner, yet. To overcome this challenge, we propose a novel andmultidisciplinary approachwhich relies on a computationally efficient hydrologicalmodel that simulates streamflow for scales ranging from small creeks to large rivers.We adopt a normalized index, the flood peak ratio (FPR), to characterize floodmagnitude acrossmultiple spatial scales. The simulated FPR is then shown to be a key statistical driver for associated economic flood losses represented by the number of insurance claims. Importantly, because it is based on a simulation procedure that utilizes generally readily available physically-based data, ourflood simulation approach has the potential to be broadly utilized, even for ungauged and poorly gauged basins, thus providing the necessary information for public and private sector actors to effectively reduce flood losses and save lives.