The Flash Flood Guidance System Implementation Worldwide: A Successful Multidecadal Research-To-Operations Effort

At the beginning of the 21st Century a research-to-operations program was initiated to design and develop operational systems to support local forecasters in their challenging task to provide advance warning for flash floods worldwide. Twenty some years later, the Flash Flood Guidance System with global coverage provides real-time assessment and guidance products to more than 60 countries, serving nearly 3 billion people. The implementation domains cover a wide range of hydroclimatological, geomorphological and land-use regimes worldwide. This flexible and evolving system combines meteorology and hydrology data and concepts as well as supports product utility for flash-flood disaster mitigation on very large scales with high spatial and temporal resolution. Through quality control procedures, it integrates remotely-sensed data of land-surface precipitation and of land-surface properties from geostationary and polar orbiter satellite platforms, reflectivity data from a variety of weather radar systems, as well as asynchronous precipitation data from ground-based automated precipitation gauges, in order to produce assessments and short-term forecasts that support forecasters and disaster managers in real time. For each region, it also integrates mesoscale meteorological model forecasts with land-surface model response to produce longer-term guidance products. It contains components and interfaces that allow real-time forecaster adjustments to products based on local last-minute field information and relevant forecaster experience. Assessments of utility for flash flood warning operations by national forecasting agencies worldwide are positive. The article exemplifies the process of realization and evolution of the FFGS from research in interdisciplinary fields to operations in diverse environments, and discusses lessons learned.

Geomorphic Modelling Application for Geospatial Flood Hazards and Flash Flood Thresholds Forecasting

In this chapter, a geomorphic modelling is presented and as a tool for geospatial flood hazard and flash flood thresholds forecasting in drainage basins. The flash flood thresholds have been estimated in terms of flash flood guidance values for the various tributary watersheds of a drainage basin considered. It has been demonstrated using the Limpopo drainage basin in southern Africa. This transboundary basin was chosen because of its importance to water supply for the growing population and water demands in its four riparian states. The basin is also subject to frequent flood and drought hazards. Even though, well established hydrological and flood frequency models do exist for flood forecasting, the purpose of this manuscript is to produce indicative flash flood guidance from a drainage basin of diverse regional development and intensive catchment land-use land cover dynamics by shading light on the geospatial portrayal of flood producing determinants. This will be important in lieu of the need for designing flood forecasting and flood early warning systems for this basin which is subject to frequent flooding hazards. Recommendations on flood forecasting and mitigation of flood hazards is provided considering the technical, human capital and institutional challenges that exist in this part of Africa.

Improving Flash Flood Forecasts: The HMT-WPC Flash Flood and Intense Rainfall Experiment

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.

CONUS-Wide Evaluation of National Weather Service Flash Flood Guidance Products

This study quantifies the skill of the National Weather Service’s (NWS) flash flood guidance (FFG) product. Generated by River Forecast Centers (RFCs) across the United States, local NWS Weather Forecast Offices compare estimated and forecast rainfall to FFG to monitor and assess flash flooding potential. A national flash flood observation database consisting of reports in the NWS publication Storm Data and U.S. Geological Survey (USGS) stream gauge measurements are used to determine the skill of FFG over a 4-yr period. FFG skill is calculated at several different precipitation-to-FFG ratios for both observation datasets. Although a ratio of 1.0 nominally indicates a potential flash flooding event, this study finds that FFG can be more skillful when ratios other than 1.0 are considered. When the entire continental United States is considered, the highest observed critical success index (CSI) with 1-h FFG is 0.20 for the USGS dataset, which should be considered a benchmark for future research that seeks to improve, modify, or replace the current FFG system. Regional benchmarks of FFG skill are also determined on an RFC-by-RFC basis. When evaluated against Storm Data reports, the regional skill of FFG ranges from 0.00 to 0.19. When evaluated against USGS stream gauge measurements, the regional skill of FFG ranges from 0.00 to 0.44.

South African Weather Service operational satellite based precipitation estimation technique: applications and improvements

Extreme weather related to heavy or more frequent precipitation events seem to be a likely possibility for the future of our planet. While precipitation measurements can be done by means of rain gauges, the obvious disadvantages of point measurements are driving meteorologists towards remotely sensed precipitation methods. In South Africa more sophisticated and expensive nowcasting technology such as radar and lightning networks are available, supported by a fairly dense rain gauge network of about 1500 daily gauges. In the rest of southern Africa rainfall measurements are more difficult to obtain. The local version of the Unified Model and the Meteosat Second Generation satellite data are ideal components of precipitation estimation in data sparse regions such as Africa. In South Africa hourly accumulations of the Hydroestimator (originally from NOAA/NESDIS) are currently used as a satellite based precipitation estimator for the South African Flash Flood Guidance system, especially in regions which are not covered by radar. In this study the Hydroestimator and the stratiform rainfall field from the Unified Model are both bias corrected and then combined into a new precipitation field. The new product was tested over a two year period and provides a more accurate and comprehensive input to the Flash Flood Guidance systems in the data sparse southern Africa. Future work will include updating the period over which bias corrections were calculated.