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Mary Lynn Baeck and James A. Smith

Abstract

Storms that produce extreme flooding present a special challenge for the WSR-88D rainfall algorithms. The authors assess the utility of weather radar in the investigation of extreme rain-producing storms through both climatological analyses of long-term radar datasets and case studies of storm events. Climatological analyses are presented for long records of WSR-88D volume scan reflectivity observations, for hourly radar rainfall accumulations products (WSR-88D and WSR-57D), and for radar–rain gauge intercomparisons. These analyses provide a context for interpreting case study assessments of WSR-88D rainfall estimates. Case studies are presented of five storms that produced extreme floods in the United States. Events include 1) the orographically enhanced Rapidan storm in the Blue Ridge region of Virginia, which resulted in more than 600 mm of rain during a 6-h period on 27 June 1995; 2) the southeast Texas storms of 16–17 October 1994 in which approximately 750 mm of rain fell during a 6-h time period; 3) the Dallas, Texas, hailstorm of 5 May 1995, which resulted in 16 flash flood deaths during a period of several hours and property damage exceeding $1 billion; 4) the Chicago, Illinois, storms of 17 July 1996 during which the 24-h rainfall record for Illinois was shattered; and 5) Hurricane Fran, which resulted in unprecedented flooding in North Carolina and Virginia during September of 1996. For each event, analyses revolve around volume scan WSR-88D reflectivity observations. The climatological analysis presented, in conjunction with the case studies analyzed, illustrate the significance of 1) brightband contamination, 2) tilt selection, 3) hail, 4) radar calibration, and 5) ZR relationships for quantitative rainfall estimates by the WSR-88D.

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Brianne K. Smith, James Smith, and Mary Lynn Baeck

Abstract

The structure and evolution of flash flood–producing storms over a small urban watershed in the mid-Atlantic United States with a prototypical flash flood response is examined. Lagrangian storm properties are investigated through analyses of the 32 storms that produced the largest peak discharges in Moores Run between January 2000 and May 2014. The Thunderstorm Identification, Tracking, Analysis, and Nowcasting (TITAN) algorithm is used to track storm characteristics over their life cycle with a focus on storm size, movement, intensity, and location. First, the 13 June 2003 and 1 June 2006 storms, which produced the two largest peak discharges for the study period, are analyzed. Heavy rainfall for the 13 June 2003 and 1 June 2006 storms were caused by a collapsing thunderstorm cell and a slow-moving, low-echo centroid storm. Analyses of the 32 storms show that collapsing storm cells play an important role in peak rainfall rate production and flash flooding. Storm motion is predominantly southwest-to-northeast, and approximately half of the storms exhibited some linear organization. Mean storm total rainfall for the 32 storms displayed an asymmetric distribution around Moores Run, with sharply decreasing gradients southwest of the watershed (upwind and into the city) and increased rainfall to the northeast (downwind and away from the city). Results indicate urban modification of rainfall in flash flood–producing storms. There was no evidence that the storms split around Baltimore. Flood-producing rainfall was highly concentrated in time; on average, approximately 21% of the storm total rainfall fell within 15 min.

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James A. Smith, Gabriele Villarini, and Mary Lynn Baeck

Abstract

Flooding in the eastern United States reflects a mixture of flood-generating mechanisms, with landfalling tropical cyclones and extratropical systems playing central roles. The authors examine the climatology of heavy rainfall and flood magnitudes for the eastern United States through analyses of long-duration records of flood peaks and maximum daily rainfall series. Spatial heterogeneities in flood peak distributions due to orographic precipitation mechanisms in mountainous terrain, coastal circulations near land–ocean boundaries, and urbanization impacts on regional climate are central elements of flood peak distributions. Lagrangian analyses of rainfall distribution and storm evolution are presented for flood events in the eastern United States and used to motivate new directions for stochastic modeling of rainfall. Tropical cyclones are an important element of the upper tail of flood peak distributions throughout the eastern United States, but their relative importance varies widely, and abruptly, in space over the region. Nonstationarities and long-term persistence of flood peak and rainfall distributions are examined from the perspective of the impacts of human-induced climate change on flood-generating mechanisms. Analyses of flood frequency for the eastern United States, which are based on observations from a dense network of U.S. Geological Survey (USGS) stream gauging stations, provide insights into emerging problems in flood science.

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Long Yang, James Smith, Mary Lynn Baeck, and Efrat Morin

Abstract

Flash flooding in the arid/semiarid southwestern United States is frequently associated with convective rainfall during the North American monsoon. In this study, we examine flood-producing storms in central Arizona based on analyses of dense rain gauge observations and stream gauging records as well as North American Regional Reanalysis fields. Our storm catalog consists of 102 storm events during the period of 1988–2014. Synoptic conditions for flood-producing storms are characterized based on principal component analyses. Four dominant synoptic modes are identified, with the first two modes explaining approximately 50% of the variance of the 500-hPa geopotential height. The transitional synoptic pattern from the North American monsoon regime to midlatitude systems is a critical large-scale feature for extreme rainfall and flooding in central Arizona. Contrasting spatial rainfall organizations and storm environment under the four synoptic modes highlights the role of interactions among synoptic conditions, mesoscale processes, and complex terrains in determining space–time variability of convective activities and flash flood hazards in central Arizona. We characterize structure and evolution properties of flood-producing storms based on storm tracking algorithms and 3D radar reflectivity. Fast-moving storm elements can be important ingredients for flash floods in the arid/semiarid southwestern United States. Contrasting storm properties for cloudburst storms highlight the wide spectrum of convective intensities for extreme rain rates in the arid/semiarid southwestern United States and exhibit comparable vertical structures to their counterparts in the eastern United States.

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James A. Smith, Mary Lynn Baeck, Gabriele Villarini, and Witold F. Krajewski

Abstract

Extreme floods in the Delaware River basin are examined through analyses of a sequence of record and near-record floods during September 2004, April 2005, and June 2006. The three flood episodes reflect three principal flood-generating mechanisms in the eastern United States: tropical cyclones (September 2004); late winter–early spring extratropical systems (April 2005); and warm-season convective systems (June 2006). Extreme flooding in the Delaware River basin is the product of heavy rainfall and runoff from high-gradient portions of the watershed. Orographic precipitation mechanisms play a central role in the extreme flood climatology of the Delaware River basin and, more generally, for the eastern United States. Extreme flooding for the 2004–06 events was produced in large measure from forested portions of the watershed. Analyses of flood frequency based on annual flood peak observations from U.S. Geological Survey (USGS) stream gauging stations with “long” records illustrate the striking heterogeneity of flood response over the region, the important role of landfalling tropical cyclones for the upper tail of flood peak distributions, and the prevalence of nonstationarities in flood peak records. Analyses show that changepoints are a more common source of nonstationarity than linear time trends. Regulation by dams and reservoirs plays an important role in determining changepoints, but the downstream effects of reservoirs on flood distributions are limited.

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Luciana K. Cunha, James A. Smith, Mary Lynn Baeck, and Witold F. Krajewski

Abstract

Dual-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, they are not able to completely resolve issues associated with range-dependent sampling. Radar rainfall error is demonstrated to decrease as temporal and spatial scales increase. However, errors in the estimation of total storm accumulations based on polarimetric radars remain significant (up to 25%) for scales of approximately 650 km2.

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Yan Zhang, James A. Smith, Alexandros A. Ntelekos, Mary Lynn Baeck, Witold F. Krajewski, and Fred Moshary

Abstract

Heavy precipitation in the northeastern United States is examined through observational and numerical modeling analyses for a weather system that produced extreme rainfall rates and urban flash flooding over the New York–New Jersey region on 4–5 October 2006. Hydrometeorological analyses combine observations from Weather Surveillance Radar-1988 Doppler (WSR-88D) weather radars, the National Lightning Detection Network, surface observing stations in the northeastern United States, a vertically pointing lidar system, and a Joss–Waldvogel disdrometer with simulations from the Weather Research and Forecasting Model (WRF). Rainfall analyses from the Hydro-Next Generation Weather Radar (NEXRAD) system, based on observations from WSR-88D radars in State College, Pennsylvania, and Fort Dix, New Jersey, and WRF model simulations show that heavy rainfall was organized into long-lived lines of convective precipitation, with associated regions of stratiform precipitation, that develop along a frontal zone.

Structure and evolution of convective storm elements that produced extreme rainfall rates over the New York–New Jersey urban corridor were influenced by the complex terrain of the central Appalachians, the diurnal cycle of convection, and the history of convective evolution in the frontal zone. Extreme rainfall rates and flash flooding were produced by a “leading line–trailing stratiform” system that was rapidly dissipating as it passed over the New York–New Jersey region. Radar, disdrometer, and lidar observations are used in combination with model analyses to examine the dynamical and cloud microphysical processes that control the spatial and temporal structure of heavy rainfall. The study illustrates key elements of the spatial and temporal distribution of rainfall that can be used to characterize flash flood hazards in the urban corridor of the northeastern United States.

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Luciana K. Cunha, James A. Smith, Witold F. Krajewski, Mary Lynn Baeck, and Bong-Chul Seo

Abstract

The 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 investigated using a diagnostic framework. The proposed method allows us to quantify QPE uncertainties at hydrologically relevant scales and provides information for the evaluation of hydrological studies forced by these rainfall datasets.

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Bettina Bauer-Messmer, James A. Smith, Mary Lynn Baeck, and Wenjie Zhao

Abstract

Measurement and forecasting of heavy rainfall requires interpretation of the small differences in the storm environment that distinguish a major flood-producing rainfall event from a relatively harmless storm system. This case study will examine some of the small differences in the storm environment that lead to a heavy rainfall event. On 8 July 1994 two storm systems developed in close proximity to each other in central Oklahoma. One of the storms developed into a squall line and produced low storm total precipitation accumulations. The other was a slow-moving multicellular storm that produced storm total precipitation of more than 130 mm and small stream flooding. The storms exhibited contrasting measurement errors in the operational WSR-88D rainfall products, with underestimation for the heavy rain event and overestimation for the squall line. The interactions of synoptic, mesoscale, and storm-scale processes for the 8 July storms are examined through analyses of WSR- 88D reflectivity and Doppler velocity observations, surface and upper-air observations from the GEWEX–GCIP Integrated Systems Test experiment, and GOES observations from visible, IR, and water vapor channels. This case study gives a unique opportunity to analyze the differences and similarities of the prestorm environment that lead to different storm structures and rainfall accumulations. Analyses also illustrate storm-scale and mesoscale processes that play a major role in determining the accuracy of WSR-88D rainfall estimates.

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Julie Rose N. Javier, James A. Smith, Katherine L. Meierdiercks, Mary Lynn Baeck, and Andrew J. Miller

Abstract

The utility of distributed hydrologic models in combination with high-resolution Weather Surveillance Radar-1988 Doppler (WSR-88D) rainfall estimates for flash flood forecasting in urban drainage basins is examined through model simulations of 10 flood events in the 14.3 km2 Dead Run watershed of Baltimore County, Maryland. The hydrologic model consists of a simple infiltration model and a geomorphological instantaneous unit hydrograph–based representation of hillslope and channel response. Analyses are based on high-resolution radar rainfall estimates from the Sterling, Virginia, WSR-88D and observations from a nested network of 6 stream gauges in the Dead Run watershed and a network of 17 rain gauge stations in Dead Run. For the three largest flood peaks in Dead Run, including the record flood on 7 July 2004, hydrologic model forecasts do not capture the pronounced attenuation of flood peaks. Hydraulic controls imposed by valley bottom constrictions associated with bridges and bridge abutments are a dominant element of the extreme flood response of small urban watersheds. Model analyses suggest that a major limitation on the accuracy of flash flood forecasting in urban watersheds is imposed by storm water management infrastructure. Model analyses also suggest that there is potential for improving model forecasts through the utilization of information on initial soil moisture storage. Errors in the rainfall field, especially those linked to bias correction, are the largest source of uncertainty in quantitative flash flood forecasting. Bias correction of radar rainfall estimates is an important element of flash flood forecasting systems.

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