Bong-Chul Seo

Scale dependence of radar rainfall uncertainty: initial evaluation of NEXRAD's new super-resolution data for hydrologic applications.

Abstract This study explores the scale effects of radar rainfall accumulation fields generated using the new super-resolution level II radar reflectivity data acquired by the Next Generation Weather Radar (NEXRAD) network of the Weather Surveillance Radar-1988 Doppler (WSR-88D) weather radars. Eleven months (May 2008–August 2009, exclusive of winter months) of high-density rain gauge network data are used to describe the uncertainty structure of radar rainfall and rain gauge representativeness with respect to five spatial scales (0.5, 1, 2, 4, and 8 km). While both uncertainties of gauge representativeness and radar rainfall show simple scaling behavior, the uncertainty of radar rainfall is characterized by an almost 3 times greater standard error at higher temporal and spatial resolutions (15 min and 0.5 km) than at lower resolutions (1 h and 8 km). These results may have implications for error propagation through distributed hydrologic models that require high-resolution rainfall input. Another interest...

Real-Time Flood Forecasting and Information System for the State of Iowa

AbstractThe Iowa Flood Center (IFC), established following the 2008 record floods, has developed a real-time flood forecasting and information dissemination system for use by all Iowans. The system complements the operational forecasting issued by the National Weather Service, is based on sound scientific principles of flood genesis and spatial organization, and includes many technological advances. At its core is a continuous rainfall–runoff model based on landscape decomposition into hillslopes and channel links. Rainfall conversion to runoff is modeled through soil moisture accounting at hillslopes. Channel routing is based on a nonlinear representation of water velocity that considers the discharge amount as well as the upstream drainage area. Mathematically, the model represents a large system of ordinary differential equations organized to follow river network topology. The IFC also developed an efficient numerical solver suitable for high-performance computing architecture. The solver allows the IF...

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...

Data-Enabled Field Experiment Planning, Management, and Research Using Cyberinfrastructure

AbstractIn the spring of 2013, NASA conducted a field campaign known as Iowa Flood Studies (IFloodS) as part of the Ground Validation (GV) program for the Global Precipitation Measurement (GPM) mission. The purpose of IFloodS was to enhance the understanding of flood-related, space-based observations of precipitation processes in events that transpire worldwide. NASA used a number of scientific instruments such as ground-based weather radars, rain and soil moisture gauges, stream gauges, and disdrometers to monitor rainfall events in Iowa. This article presents the cyberinfrastructure tools and systems that supported the planning, reporting, and management of the field campaign and that allow these data and models to be accessed, evaluated, and shared for research. The authors describe the collaborative informatics tools, which are suitable for the network design, that were used to select the locations in which to place the instruments. How the authors used information technology tools for instrument moni...

Deployment and Performance Analyses of High-Resolution Iowa XPOL Radar System during the NASA IFloodS Campaign

AbstractThis article presents the data collected and analyzed using the University of Iowa’s X-band polarimetric (XPOL) radars that were part of the spring 2013 hydrology-oriented Iowa Flood Studies (IFloodS) field campaign, sponsored by NASA’s Global Precipitation Measurement (GPM) Ground Validation (GV) program. The four mobile radars have full scanning capabilities that provide quantitative estimation of the rainfall at high temporal and spatial resolutions over experimental watersheds. IFloodS was the first extensive test of the XPOL radars, and the XPOL radars demonstrated their field worthiness during this campaign with 46 days of nearly uninterrupted, remotely monitored, and controlled operations. This paper presents detailed postcampaign analyses of the high-resolution, research-quality data that the XPOL radars collected. The XPOL dual-polarimetric products and rainfall are compared with data from other instruments for selected diverse meteorological events at high spatiotemporal resolutions from...

Comparison of Single- and Dual-Polarization–Based Rainfall Estimates Using NEXRAD Data for the NASA Iowa Flood Studies Project

AbstractThis study compares and evaluates single-polarization (SP)- and dual-polarization (DP)-based radar-rainfall (RR) estimates using NEXRAD data acquired during Iowa Flood Studies (IFloodS), a NASA GPM ground validation field campaign carried out in May–June 2013. The objective of this study is to understand the potential benefit of the DP quantitative precipitation estimation, which selects different rain-rate estimators according to radar-identified precipitation types, and to evaluate RR estimates generated by the recent research SP and DP algorithms. The Iowa Flood Center SP (IFC-SP) and Colorado State University DP (CSU-DP) products are analyzed and assessed using two high-density, high-quality rain gauge networks as ground reference. The CSU-DP algorithm shows superior performance to the IFC-SP algorithm, especially for heavy convective rains. We verify that dynamic changes in the proportion of heavy rain during the convective period are associated with the improved performance of CSU-DP rainfal...

Hydro-NEXRAD Radar-Rainfall Estimation Algorithm Development, Testing and Evaluation

The Hydro-NEXRAD radar-rainfall estimation algorithms involve three main components: 1) preprocessing, 2) rain rate, and 3) rainfall accumulation. The preprocessing algorithm performs the quality control of reflectivity volume data and generates a hybrid scan. That is, reflectivity values for each azimuth and range bin are assigned from the several lowest elevation angles. It optionally estimates an azimuthdependent vertical reflectivity profile and performs a correction for range effects. The rain rate algorithm converts the corrected reflectivity to rainfall intensity. The user can specify any power-law type empirical relationship between reflectivity and rainfall intensity. The last step of rainfall estimation is to integrate consecutive rate scans for specific time duration ranging from 15 minutes to daily. The algorithm mimics real-time calculations and involves advection correction.

A Spatial–Dynamical Framework for Evaluation of Satellite Rainfall Products for Flood Prediction

AbstractRainfall maps that are derived from satellite observations provide hydrologists with an unprecedented opportunity to forecast floods globally. However, the limitations of using these precipitation estimates with respect to producing reliable flood forecasts at multiple scales are not well understood. To address the scientific and practical question of applicability of space-based rainfall products for global flood forecasting, a data evaluation framework is developed that allows tracking the rainfall effects in space and time across scales in the river network. This provides insights on the effects of rainfall product resolution and uncertainty. Obtaining such insights is not possible when the hydrologic evaluation is based on discharge observations from single gauges. The proposed framework also explores the ability of hydrologic model structure to answer questions pertaining to the utility of space-based rainfall observations for flood forecasting. To illustrate the framework, hydrometeorologica...

Towards Better Utilization of NEXRAD Data in Hydrology: An Overview of Hydro-NEXRAD

Witold F. Krajewski (corresponding author) Anton Kruger Charles Gunyon Radoslaw Goska Bong-Chul Seo Piotr Domaszczynski A. Allen Bradley IIHR-Hydroscience & Engineering, The University of Iowa, Iowa City, IA 52242, USA E-mail: witold-krajewski@uiowa.edu James A. Smith Mary Lynn Baeck Civil and Environmental Engineering, Princeton University, Princeton, NJ 08544, USA Mohan K. Ramamurthy Jeffrey Weber Unidata Program Center, UCAR, Boulder, CO 80307, USA Stephen A. DelGreco National Climatic Data Center, Ashville, NC 28801, USA Ramon Lawrence Computer Science, University of British Columbia, Okanagan, BC V1V 1V7, Canada Matthias Steiner National Center for Atmospheric Research, Boulder, CO 80301, USA With a very modest investment in computer hardware and the open-source local data manager (LDM) software from University Corporation for Atmospheric Research (UCAR) Unidata Program Center, a researcher can receive a variety of NEXRAD Level III rainfall products and the unprocessed Level II data in real-time from most NEXRAD radars in the USA. Alternatively, one can receive such data from the National Climatic Data Center in Ashville, NC. Still, significant obstacles remain in order to unlock the full potential of the data. One set of obstacles is related to effective management of multi-terabyte datasets. A second set of obstacles, for hydrologists and hydrometeorologists in particular, is that the NEXRAD Level III products are not well suited for applications in hydrology. There is a strong need for the generation of high-quality products directly from the Level II data with well-documented steps that include quality control, removal of false echoes, rainfall estimation algorithms, coordinate conversion, georeferencing and integration with GIS. For hydrologists it is imperative that these procedures are basin-centered as opposed to radar-centered. The authors describe the Hydro-NEXRAD system that addresses the above challenges. With support from the National Science Foundation through its ITR program, the authors have developed a basin-centered framework for addressing all these issues in a comprehensive manner, tailored specifically for use of NEXRAD data in hydrology and hydrometeorology.

Four-dimensional reflectivity data comparison between two ground-based radars: methodology and statistical analysis

Abstract A methodology is proposed to compare radar reflectivity data obtained from two partially overlapping ground-based radars in order to explain relative differences in radar-rainfall products and establish sound merging procedures for multi-radar observing networks. To identify radar calibration differences, radar reflectivity is compared for well-matched radar sampling volumes viewing common meteorological targets. Temporal separation and three-dimensional matching of two different sampling volumes were considered based on the original polar coordinates of radar observation. Since the proposed method assumes radar beam propagation under standard atmospheric conditions, anomalous propagation cases were eliminated from the analysis. The reflectivity comparison results show systematic differences over time, but the variability of these differences is surprisingly large due to the sensitive nature of the radar reflectivity measurement. Editor D. Koutsoyiannis/Z.W. Kundzewicz; Guest editor R.J. Moore Citation Seo, B.-C., Krajewski, W.F., and Smith, J.A., 2013. Four-dimensional reflectivity data comparison between two ground-based radars: methodology and statistical analysis. Hydrological Sciences Journal, 59 (7), 1312–1326. http://dx.doi.org/10.1080/02626667.2013.839872