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  • Author or Editor: J. J. Gourley x
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Galateia Terti
,
Isabelle Ruin
,
Sandrine Anquetin
, and
Jonathan J. Gourley

Abstract

This paper investigates the circumstances of 1,075 fatalities from flash flooding recorded from 1996 to 2014 across the United States. This study provides insights into the situations of the fatality events as determined by the victims’ profile and activity and the spatiotemporal context of the flooding. A reclassification of the individual fatality circumstance (i.e., location and/or activity) is performed to explore statistically the timing, the duration, and location of the flash flood event and the age and gender of the victims. In agreement with other studies, more than 60% of the reported fatalities were related to vehicles involving mainly males. A geospatial analysis indicated these were most common in southern states. Further, 21% of fatalities occurred outdoors, typically in neighborhoods near streams, where the victims were exhibiting high-risk-taking behavior, such as cleaning out drains and even playing in the floodwaters. Human vulnerability varies dynamically on a subdaily basis and depends on social and natural factors of the flash flood. For example, most campsite-related fatalities were associated with very fast-responding flash flood events (less than 5-h duration), occurred more commonly after midnight, and impacted younger females and males alike. On the other hand, fatalities related to inundation of permanent buildings were most commonly associated with longer-duration events and impacted the elderly. Situational rather than generic examination of vulnerability is required to realistically capture risky cases during short-fuse flood events.

The circumstances in which people perished in flash floods suggest that situational rather than generic examination of vulnerability is required to realistically capture risky cases during short-fuse flood events.

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Bin Yong
,
Die Liu
,
Jonathan J. Gourley
,
Yudong Tian
,
George J. Huffman
,
Liliang Ren
, and
Yang Hong

Abstract

Accurate estimation of high-resolution precipitation on the global scale is extremely challenging. The operational Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis (TMPA) has created over 16 years of high-resolution quantitative precipitation estimation (QPE), and has built the foundation for improved measurements in the upcoming Global Precipitation Measurement (GPM) mission. TMPA is intended to produce the “best effort” estimates of quasi-global precipitation from almost all available satelliteborne precipitation-related sensors by consistently calibrating them with the high-quality measurements from the core instrument platform aboard TRMM. Recently, the TMPA system has been upgraded to version 7 to take advantage of newer and better sources of satellite inputs than version 6, and has attracted a large user base. A key product from TMPA is the near-real-time product (TMPA-RT), as its timeliness is particularly appealing for time-sensitive applications such as flood and landslide monitoring. TMPA-RT’s error characteristics on a global scale have yet to be extensively quantified and understood. In this study, efforts are focused on a systematic evaluation of four sets of mainstream TMPA-RT estimates on the global scale. The analysis herein indicates that the latest version 7 TMPA-RT with the monthly climatological calibration had the lowest daily systematic biases of approximately 9% over land and –11% over ocean (relative to the gauge-adjusted research product). However, there still exist some unresolved issues in mountainous areas (especially the Tibetan Plateau) and high-latitude belts, and for estimating extreme rainfall rates with high variability at small scales. These global error characteristics and their regional and seasonal variations revealed in this paper are expected to serve as the benchmark for the upcoming GPM mission.

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Alan Gerard
,
Steven M. Martinaitis
,
Jonathan J. Gourley
,
Kenneth W. Howard
, and
Jian Zhang

Abstract

The Multi-Radar Multi-Sensor (MRMS) system is an operational, state-of-the-science hydrometeorological data analysis and nowcasting framework that combines data from multiple radar networks, satellites, surface observational systems, and numerical weather prediction models to produce a suite of real-time, decision-support products every 2 min over the contiguous United States and southern Canada. The Flooded Locations and Simulated Hydrograph (FLASH) component of the MRMS system was designed for the monitoring and prediction of flash floods across small time and spatial scales required for urban areas given their rapid hydrologic response to precipitation. Developed at the National Severe Storms Laboratory in collaboration with the Cooperative Institute for Mesoscale Meteorological Studies (CIMMS) and other research entities, the objective for MRMS and FLASH is to be the world’s most advanced system for severe weather and storm-scale hydrometeorology, leveraging the latest science and observation systems to produce the most accurate and reliable hydrometeorological and severe weather analyses. NWS forecasters, the public, and the private sector utilize a variety of products from the MRMS and FLASH systems for hydrometeorological situational awareness and to provide warnings to the public and other users about potential impacts from flash flooding. This article will examine the performance of hydrometeorological products from MRMS and FLASH and provide perspectives on how NWS forecasters use these products in the prediction of flash flood events with an emphasis on the urban environment.

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Elizabeth M. Argyle
,
Jonathan J. Gourley
,
Zachary L. Flamig
,
Tracy Hansen
, and
Kevin Manross

ABSTRACT

Hazard Services is a software toolkit that integrates information management, hazard alerting, and communication functions into a single user interface. When complete, National Weather Service forecasters across the United States will use Hazard Services for operational issuance of weather and hydrologic alerts, making the system an instrumental part of the threat management process. As a new decision-support tool, incorporating an understanding of user requirements and behavior is an important part of building a system that is usable, allowing users to perform work-related tasks efficiently and effectively. This paper discusses the Hazard Services system and findings from a usability evaluation with a sample of end users. Usability evaluations are frequently used to support software and website development and can provide feedback on a system’s efficiency of use, effectiveness, and learnability. In the present study, a user-testing evaluation assessed task performance in terms of error rates, error types, response time, and subjective feedback from a questionnaire. A series of design recommendations was developed based on the evaluation’s findings. The recommendations not only further the design of Hazard Services, but they may also inform the designs of other decision-support tools used in weather and hydrologic forecasting.

Incorporating usability evaluation into the iterative design of decision-support tools, such as Hazard Services, can improve system efficiency, effectiveness, and user experience.

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Zhijun Huang
,
Huan Wu
,
Robert F. Adler
,
Guy Schumann
,
Jonathan J. Gourley
,
Albert Kettner
, and
Nergui Nanding

Abstract

A reliable flood event inventory that reflects the occurrence and evolution of past floods is important for studies of flood hazards and risks, hydroclimatic extremes, and future flood projections. However, currently available flood inventories are based on single-sourced data and often neglect underreported or less impactful flood events. Furthermore, traditional archives store flood events only at sparse geographic points, which significantly limits their further applicability. Also, few publicly available archives contain all-inclusive records of potential natural flooded area over time. To tackle these challenges, we construct two types of multisourced flood event inventories (MFI) for all river basins across the contiguous United States covering the period 1998–2013 on daily and subcatchment scales, which is publicly available at http://flood.umd.edu/download/CONUS/. These archives integrate flood information from in situ observations, remote sensing observations, hydrological model simulations, and five high-quality precipitation products. The first inventory (MFI-Actual) includes all actual floods that occurred in the presence of flood protection infrastructures, while the second, “natural (undefended)” inventory (MFI-Natural) reconstructs the possible “historical” floods without flood protection, which could be more directly influenced by climate variation. In the proposed two inventories, 2,755 and 4,661 flood events were estimated, respectively. MFI-Natural reconstructed 1,597 floods in ungauged basins, and recovered 608 extreme streamflow events in gauged subcatchments where floods would have happened if there were no flood protection. There is an average of four upstream dams located in these flood-recovered subcatchments, which indicates that modern flood defenses efficiently prevent significant flooding from extreme precipitation in many catchments over the country.

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I. Ruin
,
C. Lutoff
,
L. Creton-Cazanave
,
S. Anquetin
,
M. Borga
,
S. Chardonnel
,
J.-D. Creutin
,
J. Gourley
,
E. Gruntfest
,
S. Nobert
, and
J. Thielen
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O. Bousquet
,
A. Berne
,
J. Delanoe
,
Y. Dufournet
,
J. J. Gourley
,
J. Van-Baelen
,
C. Augros
,
L. Besson
,
B. Boudevillain
,
O. Caumont
,
E. Defer
,
J. Grazioli
,
D. J. Jorgensen
,
P.-E. Kirstetter
,
J.-F. Ribaud
,
J. Beck
,
G. Delrieu
,
V. Ducrocq
,
D. Scipion
,
A. Schwarzenboeck
, and
J. Zwiebel

Abstract

The radar network deployed in southern France during the first special observing period (SOP 1) of the Hydrological Cycle in the Mediterranean Experiment (HyMeX) was designed to precisely document the 3D structure of moist upstream flow impinging on complex terrain as a function of time, height, and along-barrier distance, and surface rainfall patterns associated with orographic precipitation events. This deployment represents one of the most ambitious field experiments yet, endeavoring to collect high-quality observations of thunderstorms and precipitation systems developing over and in the vicinity of a major mountain chain.

Radar observations collected during HyMeX represent a valuable, and potentially unique, dataset that will be used to improve our knowledge of physical processes at play within coastal orographic heavy precipitating systems and to develop, and evaluate, novel radar-based products for research and operational activities. This article provides a concise description of this radar network and discusses innovative research ideas based upon preliminary analyses of radar observations collected during this field project with emphasis on the synergetic use of dual-polarimetric radar measurements collected at multiple frequencies.

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Sheng Chen
,
Jonathan J. Gourley
,
Yang Hong
,
Qing Cao
,
Nicholas Carr
,
Pierre-Emmanuel Kirstetter
,
Jian Zhang
, and
Zac Flamig

Abstract

In meteorological investigations, the reference variable or “ground truth” typically comes from an instrument. This study uses human observations of surface precipitation types to evaluate the same variables that are estimated from an automated algorithm. The NOAA/National Severe Storms Laboratory’s Multi-Radar Multi-Sensor (MRMS) system relies primarily on observations from the Next Generation Radar (NEXRAD) network and model analyses from the Earth System Research Laboratory’s Rapid Refresh (RAP) system. Each hour, MRMS yields quantitative precipitation estimates and surface precipitation types as rain or snow. To date, the surface precipitation type product has received little attention beyond case studies. This study uses precipitation type reports collected by citizen scientists who have contributed observations to the meteorological Phenomena Identification Near the Ground (mPING) project. Citizen scientist reports of rain and snow during the winter season from 19 December 2012 to 30 April 2013 across the United States are compared to the MRMS precipitation type products. Results show that while the mPING reports have a limited spatial distribution (they are concentrated in urban areas), they yield similar critical success indexes of MRMS precipitation types in different cities. The remaining disagreement is attributed to an MRMS algorithmic deficiency of yielding too much rain, as opposed to biases in the mPING reports. The study also shows reduced detectability of snow compared to rain, which is attributed to lack of sensitivity at S band and the shallow nature of winter storms. Some suggestions are provided for improving the MRMS precipitation type algorithm based on these findings.

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Faye E. Barthold
,
Thomas E. Workoff
,
Brian A. Cosgrove
,
Jonathan J. Gourley
,
David R. Novak
, and
Kelly M. Mahoney

Abstract

Despite advancements in numerical modeling and the increasing prevalence of convection-allowing guidance, flash flood forecasting remains a substantial challenge. Accurate flash flood forecasts depend not only on accurate quantitative precipitation forecasts (QPFs), but also on an understanding of the corresponding hydrologic response. To advance forecast skill, innovative guidance products that blend meteorology and hydrology are needed, as well as a comprehensive verification dataset to identify areas in need of improvement.

To address these challenges, in 2013 the Hydrometeorological Testbed at the Weather Prediction Center (HMT-WPC), partnering with the National Severe Storms Laboratory (NSSL) and the Earth System Research Laboratory (ESRL), developed and hosted the inaugural Flash Flood and Intense Rainfall (FFaIR) Experiment. In its first two years, the experiment has focused on ways to combine meteorological guidance with available hydrologic information. One example of this is the creation of neighborhood flash flood guidance (FFG) exceedance probabilities, which combine QPF information from convection-allowing ensembles with flash flood guidance; these were found to provide valuable information about the flash flood threat across the contiguous United States.

Additionally, WPC has begun to address the challenge of flash flood verification by developing a verification database that incorporates observations from a variety of disparate sources in an attempt to build a comprehensive picture of flash flooding across the nation. While the development of this database represents an important step forward in the verification of flash flood forecasts, many of the other challenges identified during the experiment will require a long-term community effort in order to make notable advancements.

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Kiel L. Ortega
,
Travis M. Smith
,
Kevin L. Manross
,
Kevin A. Scharfenberg
,
Arthur Witt
,
Angelyn G. Kolodziej
, and
Jonathan J. Gourley

During the springs and summers of 2006 through 2008, scientists from the National Severe Storms Laboratory and students from the University of Oklahoma have conducted an enhanced severe-storm verification effort. The primary goal for the Severe Hazards Analysis and Verification Experiment (SHAVE) was the remote collection of high spatial and temporal resolution hail, wind (or wind damage), and flash-flooding reports from severe thunderstorms. This dataset has a much higher temporal and spatial resolution than the traditional storm reports collected by the National Weather Service and published in Storm Data (tens of square kilometers and 1–5 min versus thousands of square kilometers and 30–60 min) and also includes reports of nonsevere storms that are not included in Storm Data. The high resolution of the dataset makes it useful for validating high-resolution, gridded warning guidance applications.

SHAVE is unique not only for the type of data collected and the resolution of that data but also for how the data are collected. The daily operations of the project are largely student led and run. To complete the remote, high-resolution verification, the students use Google Earth to display experimental weather data and geographic information databases, such as digital phonebooks. Using these data, the students then make verification phone calls to residences and businesses, throughout the United States, thought to have been affected by a severe thunderstorm. The present article summarizes the data collection facilities and techniques, discusses applications of these data, and shows comparisons of SHAVE reports to reports currently available from Storm Data.

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