Comments on “Flash Flood Verification: Pondering Precipitation Proxies”

2021 ◽  
Vol 22 (3) ◽  
pp. 739-747
Author(s):  
Jonathan J. Gourley ◽  
Humberto Vergara
Keyword(s):  
Flash Flood ◽  
End Users ◽  
Next Generation ◽  
Dual Polarization ◽  
Flash Flooding ◽  
Radar Network ◽  
Operational Forecasting ◽  
Precipitation Estimates ◽  
Quantitative Precipitation Estimates ◽  
Flood Warnings

AbstractNew operational tools for monitoring flash flooding based on radar quantitative precipitation estimates (QPEs) have become available to U.S. National Weather Service forecasters. Herman and Schumacher examined QPE exceedance thresholds for several tools and compared them to each other, to flash flood reports (FFRs), and to flash flood warnings. The Next Generation Radar network has been updated with dual-polarization capabilities since the publication of Herman and Schumacher, which has changed the characteristics of the derived QPEs. Updated thresholds on Multi-Radar Multi-Sensor version 12 products that are associated to FFRs are provided and thus can be used as guidance by the operational forecasting community and other end-users of the products.

scholarly journals Utilization of Weather Radar Data for the Flash Flood Indicator Application in the Czech Republic

2021 ◽  
Vol 13 (16) ◽  
pp. 3184
Author(s):  
Petr Novák ◽  
Hana Kyznarová ◽  
Martin Pecha ◽  
Petr Šercl ◽  
Vojtěch Svoboda ◽  
...  
Keyword(s):  
Czech Republic ◽  
Flash Flood ◽  
Weather Radar ◽  
Radar Data ◽  
Rain Gauge ◽  
Adjustment Coefficient ◽  
The Czech Republic ◽  
Radar Network ◽  
Precipitation Estimates ◽  
Quantitative Precipitation Estimates

In the past few years, demands on flash flood forecasting have grown. The Flash Flood Indicator (FFI) is a system used at the Czech Hydrometeorological Institute for the evaluation of the risk of possible occurrence of flash floods over the whole Czech Republic. The FFI calculation is based on the current soil saturation, the physical-geographical characteristics of every considered area, and radar-based quantitative precipitation estimates (QPEs) and forecasts (QPFs). For higher reliability of the flash flood risk assessment, calculations of QPEs and QPFs are crucial, particularly when very high intensities of rainfall are reached or expected. QPEs and QPFs entering the FFI computations are the products of the Czech Weather Radar Network. The QPF is based on the COTREC extrapolation method. The radar-rain gauge-combining method MERGE2 is used to improve radar-only QPEs and QPFs. It generates a combined radar-rain gauge QPE based on the kriging with an external drift algorithm, and, also, an adjustment coefficient applicable to radar-only QPEs and QPFs. The adjustment coefficient is applied in situations when corresponding rain gauge measurements are not yet available. A new adjustment coefficient scheme was developed and tested to improve the performance of adjusted radar QPEs and QPFs in the FFI.

scholarly journals Organization of Flash-Flood-Producing Precipitation in the Northeast United States

2012 ◽  
Vol 27 (2) ◽  
pp. 345-361 ◽  
Author(s):  
Stephen M. Jessup ◽  
Stephen J. Colucci
Keyword(s):  
United States ◽  
Flash Flood ◽  
Warm Season ◽  
Heavy Precipitation ◽  
Flash Flooding ◽  
Radar Signature ◽  
Long Duration ◽  
Central United States ◽  
Linear Types ◽  
Precipitation Estimates

Abstract Heavy precipitation and flash flooding have been extensively studied in the central United States, but less so in the Northeast. This study examines 187 warm-season flash flood events identified in Storm Data to better understand the structure of the precipitation systems that cause flash flooding in the Northeast. Based on the organization and movement of these systems on radar, the events are classified into one of four categories—back-building, linear, multiple, and other/size—and then further classified into subtypes for each category. Eight of these subtypes were not previously recognized in the literature. The back-building events were the most common, followed by the multiple, other/size, and linear types. The linear event types appear to produce flash flooding less commonly in the Northeast than in other regions. In general, the subtypes producing the highest precipitation estimates are those whose structures are most conducive to a long duration of sustained moderate to heavy rainfall. The event types were found to differ from those in the central United States in that the events were more often found to be more disorganized in the Northeast. One event type in particular, back-building with merging features, while not more disorganized than the previously recognized event types, offers promise for improved forecasting because its radar signature makes the duration of sustained heavy precipitation potentially easier to predict.

The impacts of climatological adjustment of quantitative precipitation estimates on the accuracy of flash flood detection

2016 ◽  
Vol 541 ◽  
pp. 387-400 ◽  
Author(s):  
Yu Zhang ◽  
Sean Reed ◽  
Jonathan J. Gourley ◽  
Brian Cosgrove ◽  
David Kitzmiller ◽  
...  
Keyword(s):  
Flash Flood ◽  
Precipitation Estimates ◽  
Flood Detection ◽  
Quantitative Precipitation Estimates

Improving QPE and Very Short Term QPF: An Initiative for a Community-Wide Integrated Approach

2007 ◽  
Vol 88 (12) ◽  
pp. 1899-1911 ◽  
Author(s):  
Steven V. Vasiloff ◽  
Dong-Jun Seo ◽  
Kenneth W. Howard ◽  
Jian Zhang ◽  
David H. Kitzmiller ◽  
...  
Keyword(s):  
Flash Flood ◽  
Wide Spectrum ◽  
Integrated Approach ◽  
Test Bed ◽  
Short Term ◽  
Public And Private ◽  
Quarter Century ◽  
Wide Range ◽  
Precipitation Estimates ◽  
Quantitative Precipitation Estimates

Accurate quantitative precipitation estimates (QPE) and very short term quantitative precipitation forecasts (VSTQPF) are critical to accurate monitoring and prediction of water-related hazards and water resources. While tremendous progress has been made in the last quarter-century in many areas of QPE and VSTQPF, significant gaps continue to exist in both knowledge and capabilities that are necessary to produce accurate high-resolution precipitation estimates at the national scale for a wide spectrum of users. Toward this goal, a national next-generation QPE and VSTQPF (Q2) workshop was held in Norman, Oklahoma, on 28–30 June 2005. Scientists, operational forecasters, water managers, and stakeholders from public and private sectors, including academia, presented and discussed a broad range of precipitation and forecasting topics and issues, and developed a list of science focus areas. To meet the nation's needs for the precipitation information effectively, the authors herein propose a community-wide integrated approach for precipitation information that fully capitalizes on recent advances in science and technology, and leverages the wide range of expertise and experience that exists in the research and operational communities. The concepts and recommendations from the workshop form the Q2 science plan and a suggested path to operations. Implementation of these concepts is expected to improve river forecasts and flood and flash flood watches and warnings, and to enhance various hydrologic and hydrometeorological services for a wide range of users and customers. In support of this initiative, the National Mosaic and Q2 (NMQ) system is being developed at the National Severe Storms Laboratory to serve as a community test bed for QPE and VSTQPF research and to facilitate the transition to operations of research applications. The NMQ system provides a real-time, around-the-clock data infusion and applications development and evaluation environment, and thus offers a community-wide platform for development and testing of advances in the focus areas.

scholarly journals Double Impact: When Both Tornadoes and Flash Floods Threaten the Same Place at the Same Time

2015 ◽  
Vol 30 (6) ◽  
pp. 1673-1693 ◽  
Author(s):  
Erik R. Nielsen ◽  
Gregory R. Herman ◽  
Robert C. Tournay ◽  
John M. Peters ◽  
Russ S. Schumacher
Keyword(s):  
Mississippi River ◽  
Flash Flood ◽  
Flash Floods ◽  
Public Communication ◽  
Synoptic Scale ◽  
Flash Flooding ◽  
Synoptic Conditions ◽  
Lower Mississippi River ◽  
Double Impact ◽  
Flood Warnings

Abstract While both tornadoes and flash floods individually present public hazards, when the two threats are both concurrent and collocated (referred to here as TORFF events), unique concerns arise. This study aims to evaluate the climatological and meteorological characteristics associated with TORFF events over the continental United States. Two separate datasets, one based on overlapping tornado and flash flood warnings and the other based on observations, were used to arrive at estimations of the instances when a TORFF event was deemed imminent and verified to have occurred, respectively. These datasets were then used to discern the geographical and meteorological characteristics of recent TORFF events. During 2008–14, TORFF events were found to be publicly communicated via overlapping warnings an average of 400 times per year, with a maximum frequency occurring in the lower Mississippi River valley. Additionally, 68 verified TORFF events between 2008 and 2013 were identified and subsequently classified based on synoptic characteristics and radar observations. In general, synoptic conditions associated with TORFF events were found to exhibit similar characteristics of typical tornadic environments, but the TORFF environment tended to be moister and have stronger synoptic-scale forcing for ascent. These results indicate that TORFF events occur with appreciable frequency and in complex meteorological scenarios. Furthermore, despite these identified differences, TORFF scenarios are not easily distinguishable from tornadic events that fail to produce collocated flash flooding, and present difficult challenges both from the perspective of forecasting and public communication.

scholarly journals Improving Multisensor Precipitation Estimation via Adaptive Conditional Bias–Penalized Merging of Rain Gauge Data and Remotely Sensed Quantitative Precipitation Estimates

2019 ◽  
Vol 20 (12) ◽  
pp. 2347-2365 ◽  
Author(s):  
Ali Jozaghi ◽  
Mohammad Nabatian ◽  
Seongjin Noh ◽  
Dong-Jun Seo ◽  
Lin Tang ◽  
...  
Keyword(s):  
Computational Cost ◽  
Mean Field ◽  
Remotely Sensed ◽  
Rain Gauge ◽  
Rain Gauge Data ◽  
Gauge Data ◽  
Precipitation Estimation ◽  
Precipitation Estimates ◽  
Radar Satellite ◽  
Quantitative Precipitation Estimates

Abstract We describe and evaluate adaptive conditional bias–penalized cokriging (CBPCK) for improved multisensor precipitation estimation using rain gauge data and remotely sensed quantitative precipitation estimates (QPE). The remotely sensed QPEs used are radar-only and radar–satellite-fused estimates. For comparative evaluation, true validation is carried out over the continental United States (CONUS) for 13–30 September 2015 and 7–9 October 2016. The hourly gauge data, radar-only QPE, and satellite QPE used are from the Hydrometeorological Automated Data System, Multi-Radar Multi-Sensor System, and Self-Calibrating Multivariate Precipitation Retrieval (SCaMPR), respectively. For radar–satellite fusion, conditional bias–penalized Fisher estimation is used. The reference merging technique compared is ordinary cokriging (OCK) used in the National Weather Service Multisensor Precipitation Estimator. It is shown that, beyond the reduction due to mean field bias (MFB) correction, both OCK and adaptive CBPCK additionally reduce the unconditional root-mean-square error (RMSE) of radar-only QPE by 9%–16% over the CONUS for the two periods, and that adaptive CBPCK is superior to OCK for estimation of hourly amounts exceeding 1 mm. When fused with the MFB-corrected radar QPE, the MFB-corrected SCaMPR QPE for September 2015 reduces the unconditional RMSE of the MFB-corrected radar by 4% and 6% over the entire and western half of the CONUS, respectively, but is inferior to the MFB-corrected radar for estimation of hourly amounts exceeding 7 mm. Adaptive CBPCK should hence be favored over OCK for estimation of significant amounts of precipitation despite larger computational cost, and the SCaMPR QPE should be used selectively in multisensor QPE.

scholarly journals Detecting Beam Blockage in Radar-Based Precipitation Estimates

2017 ◽  
Vol 34 (7) ◽  
pp. 1407-1422 ◽  
Author(s):  
D. Brent McRoberts ◽  
John W. Nielsen-Gammon
Keyword(s):  
Hydrological Modeling ◽  
Tall Buildings ◽  
Eastern United States ◽  
Spatiotemporal Resolution ◽  
Transmitted Beam ◽  
Geographical Regions ◽  
Precipitation Estimates ◽  
Low Pass ◽  
Prerequisite Knowledge ◽  
Quantitative Precipitation Estimates

AbstractGridded radar-based quantitative precipitation estimates (QPEs) are potentially ideal inputs for hydrological modeling and monitoring because of their high spatiotemporal resolution. Beam blockage is a common type of bias in radar QPEs related to the blockage of the radar beam by an obstruction, such as topography or tall buildings. This leads to a diminishment in the power of the transmitted beam beyond the range of obstruction and a systematic underestimation of reflectivity return to the radar site. A new spatial analysis technique for objectively identifying regions in which precipitation estimates are contaminated by beam blockage was developed. The methodology requires only a long-term precipitation climatology with no prerequisite knowledge of topography or known obstructions needed. For each radar domain, the QPEs are normalized by climatology and a low-pass Fourier series fit captures the expected precipitation as a function of azimuth angle. Beam blockage signatures are identified as radially coherent regions with normalized values that are systematically lower than the Fourier fit. Precipitation estimates sufficiently affected by beam blockage can be replaced by values estimated using neighboring unblocked estimates. The methodology is applied to the correction of the National Weather Service radar-based QPE dataset, whose estimates originate from the NEXRAD network in the central and eastern United States. The methodology is flexible enough to be useful for most radar installations and geographical regions with at least a few years of data.

Effects of 2017 Early Flash Flooding on Agriculture in Haor Areas of Sunamganj

2021 ◽  
Vol 12 (1-2) ◽  
pp. 117-125
Author(s):  
S Mondal ◽  
L Akter ◽  
HJ Hiya ◽  
MA Farukh
Keyword(s):  
Agricultural Production ◽  
Flash Flood ◽  
Eastern Region ◽  
Fish Production ◽  
Flood Events ◽  
Flash Flooding ◽  
The North ◽  
North Eastern ◽  
Boro Rice

The Sunamganj district is covered by major Haor systems in the north-eastern region of Bangladesh. Flash flood is the most commonly occurring water related disaster in the Haor areas. During the flash flood it is very common that people lost their primary agricultural productions which are the only source of their livelihood. The present study focuses on the effects of 2017 early flash flooding on rice and fish production of Sunamganj Haor areas. The flood caused enormous damage to agriculture such as rice especially Boro rice and fish production on which the Haor dwellers rely upon for their livelihood. The total affected land of Boro rice cultivation in Haors of Sunamganj was 149,224 hectare and the total amount of damaged rice was 393,855 metric ton (MT). The total number of affected farmers was 315,084. The early flash flood also affects the quality of Haor water which caused the death of fishes. The total amount of damaged fish was 49.75 MT and the loss was 158.70 lakh taka. The total number of affected fishermen was 44,445. This findings could be very useful for the environmental scientists to predict the probable future effects on agricultural production due to early flash flood events in Sunamganj Haors areas. Environ. Sci. & Natural Resources, 12(1&2): 117-125, 2019

scholarly journals Flood Forecasting and Warning System Structures: Procedure and Application to a Small Urban Stream in South Korea

Water ◽  
2019 ◽  
Vol 11 (8) ◽  
pp. 1571 ◽  
Author(s):  
Song ◽  
Park ◽  
Lee ◽  
Park ◽  
Song
Keyword(s):  
Decision Making ◽  
Water Level ◽  
Real Time ◽  
Lead Time ◽  
Flash Flood ◽  
Warning System ◽  
Flood Forecasting ◽  
Urban Stream ◽  
Forecasting And Warning ◽  
Flood Warnings

The runoff from heavy rainfall reaches urban streams quickly, causing them to rise rapidly. It is therefore of great importance to provide sufficient lead time for evacuation planning and decision making. An efficient flood forecasting and warning method is crucial for ensuring adequate lead time. With this objective, this paper proposes an analysis method for a flood forecasting and warning system, and establishes the criteria for issuing urban-stream flash flood warnings based on the amount of rainfall to allow sufficient lead time. The proposed methodology is a nonstructural approach to flood prediction and risk reduction. It considers water level fluctuations during a rainfall event and estimates the upstream (alert point) and downstream (confluence) water levels for water level analysis based on the rainfall intensity and duration. We also investigate the rainfall/runoff and flow rate/water level relationships using the Hydrologic Engineering Center’s Hydrologic Modeling System (HEC-HMS) and the HEC’s River Analysis System (HEC-RAS) models, respectively, and estimate the rainfall threshold for issuing flash flood warnings depending on the backwater state based on actual watershed conditions. We present a methodology for issuing flash flood warnings at a critical point by considering the effects of fluctuations in various backwater conditions in real time, which will provide practical support for decision making by disaster protection workers. The results are compared with real-time water level observations of the Dorim Stream. Finally, we verify the validity of the flash flood warning criteria by comparing the predicted values with the observed values and performing validity analysis.

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