12 research outputs found
Recommended from our members
Providing openly-available seasonal forecasts of flood and drought hazard for rivers worldwide
Dr Rebecca Emerton of the National Centre for Atmospheric Science worked alongside scientists at the University of Reading and the European Centre for Medium-Range Weather Forecasts (ECMWF) to develop the worldâs first open global-scale seasonal hydro-meteorological forecasting system. This work was undertaken as part of Dr Emertonâs PhD research with the Universityâs Water@Reading research group, completed in February 2019
Recommended from our members
What is the most useful approach for forecasting hydrological extremes during El Niño?
In the past, efforts to prepare for the impacts of El Niño-driven flood and drought hazards have often relied on seasonal precipitation forecasts as a proxy for hydrological extremes, due to a lack of hydrologically relevant information. However, precipitation forecasts are not the best indicator of hydrological extremes. Now, two different global scale hydro-meteorological approaches for predicting river flow extremes are available to support flood and drought preparedness. These approaches are statistical forecasts based on large-scale climate variability and teleconnections, and resource-intensive dynamical forecasts using coupled ocean-atmosphere general circulation models. Both have the potential to provide early warning information, and both are used to prepare for El Niño impacts, but which approach provides the most useful forecasts?
This study uses river flow observations to assess and compare the ability of two recently-developed forecasts to predict high and low river flow during El Niño: statistical historical probabilities of ENSO-driven hydrological extremes, and the dynamical seasonal river flow outlook of the Global Flood Awareness System (GloFAS-Seasonal). Our findings highlight regions of the globe where each forecast is (or is not) skilful compared to a forecast of climatology, and the advantages and disadvantages of each forecasting approach. We conclude that in regions where extreme river flow is predominantly driven by El Niño, or in regions where GloFAS-Seasonal currently lacks skill, the historical probabilities generally provide a more useful forecast. In areas where other teleconnections also impact river flow, with the effect of strengthening, mitigating or even reversing the influence of El Niño, GloFAS-Seasonal forecasts are typically more useful
Recommended from our members
Can seasonal hydrological forecasts inform local decisions and actions? A decision-making activity
While this paper has a hydrological focus (a glossaryâ is included) the concept of our decision-making activity will be of wider interest and applicable to those involved in all aspects of geoscience communication.
Seasonal hydrological forecasts (SHF) provide insight into the river and groundwater levels that might be expected over the coming months. This is valuable for informing future flood or drought risk and water availability, yet studies investigating how SHF are used for decision-making are limited. Our activity was designed to capture how different water sector users, broadly flood and drought forecasters, water resource managers and groundwater hydrologists, interpret and act on SHF to inform decisions in the West Thames, UK. Using a combination of operational and hypothetical forecasts, participants were provided with 3 sets of progressively confident and locally tailored SHF for a flood event in 3 monthsâ time. Participants played with their âday-jobâ hat on and were not informed whether the SHF represented a flood, drought or business-as-usual scenario. Participants increased their decision/action choice in response to more confident and locally tailored forecasts. Forecasters and groundwater hydrologists were most likely to request further information about the situation, inform other organisations and implement actions for preparedness. Water resource managers more consistently adopted a âwatch and waitâ approach. Local knowledge, risk appetite and experience of previous flood events were important for informing decisions. Discussions highlighted that forecast uncertainty does not necessarily pose a barrier to use, but SHF need to be presented at a finer spatial resolution to aid local decision-making. SHF information that is visualised using combinations of maps, text, hydrographs and tables is beneficial for interpretation and better communication of SHF that are tailored to different user groups is needed. Decision-making activities are a great way of creating realistic scenarios that participants can identify with, whilst allowing the activity creators to observe different thought-processes. In this case, participants stated that the activity complemented their everyday work, introduced them to ongoing scientific developments and enhanced their understanding of how different organisations are engaging with and using SHF to aid decision-making across the West Thames
Recommended from our members
Developing a global operational seasonal hydro-meteorological forecasting system: GloFAS-Seasonal v1.0
Global overviews of upcoming flood and drought events are key for many applications, including disaster risk reduction initiatives. Seasonal forecasts are designed to provide early indications of such events weeks, or even months, in advance, but seasonal forecasts for hydrological variables at large or global scales are few and far between. Here, we present the first operational global scale seasonal hydro-meteorological forecasting system: GloFAS-Seasonal. Developed as an extension of the Global Flood Awareness System (GloFAS), GloFAS-Seasonal couples seasonal meteorological forecasts from ECMWF with a hydrological model, to provide openly available probabilistic forecasts of river flow out to 4 months ahead for the global river network. This system has potential benefits not only for disaster risk reduction through early awareness of floods and droughts, but also for water-related sectors such as agriculture and water resources management, in particular for regions where no other forecasting system exists. We describe the key hydro-meteorological components and computational framework of GloFAS-Seasonal, alongside the forecast products available, before discussing initial evaluation results and next steps
Recommended from our members
Ensemble flood forecasting: current status and future opportunities
Ensemble flood forecasting has gained significant momentum over the past decade due to the growth of ensemble numerical weather and climate prediction, expansion in high performance computing, growing interest in shifting from deterministic to risk-based decision-making that accounts for forecast uncertainty, and the efforts of communities such as the international Hydrologic Ensemble Prediction Experiment (HEPEX), which focuses on advancing relevant ensemble forecasting capabilities and fostering its adoption. With this shift, comes the need to understand the current state of ensemble flood forecasting, in order to provide insights into current capabilities and areas for improvement, thus identifying future research opportunities to allow for better allocation of research resources. In this paper, we provide an overview of current research activities in ensemble flood forecasting and discuss knowledge gaps and future research opportunities, based on a review of 70 papers focussing on various aspects of ensemble flood forecasting around the globe. Future research directions include opportunities to improve technical aspects of ensemble flood forecasting, such as data assimilation techniques and methods to account for more sources of uncertainty, and developing ensemble forecasts for more variables, for example flood inundation, by applying techniques such as machine learning. Further to this, we conclude that there is a need to not only improve technical aspects of flood forecasting, but also to bridge the gap between scientific research and hydro-meteorological model development, and real-world flood management using probabilistic ensemble forecasts, especially through effective communication
Recommended from our members
Connecting hydrological modelling and forecasting from global to local scales: perspectives from an international joint virtual workshop
The unprecedented progress in ensemble hydro-meteorological modelling and forecasting on a range of temporal and spatial scales, raises a variety of new challenges which formed the theme of the Joint Virtual Workshop, "Connecting global to local hydrological modelling and forecasting: challenges and scientific advancesâ. Held from 29 June to 1 July 2021, this workshop was co-organized by the European Centre for Medium-Range Weather Forecasts (ECMWF), the Copernicus Emergency Management (CEMS) and Climate Change (C3S) Services, the Hydrological Ensemble Prediction EXperiment (HEPEX), and the Global Flood Partnership (GFP). This paper aims to summarize the state-of-the-art presented at the workshop and provide an early career perspective. Recent advances in hydrological modelling and forecasting, reflections on the use of forecasts for decision-making across scales, and means to minimise new barriers to communication in the virtual format are also discussed. Thematic foci of the workshop included hydrological model development and skill assessment, uncertainty communication, forecasts for early action, co-production of services and incorporation of local knowledge, Earth Observation, and data assimilation. Connecting hydrological services to societal needs and local decision-making through effective communication, capacity-building and co-production was identified as critical. Multidisciplinary collaborations emerged as crucial to effectively bring newly developed tools to practice
Recommended from our members
Building a multimodel flood prediction system with the TIGGE archive
In the last decade operational probabilistic ensemble flood forecasts have become common in supporting decision-making processes leading to risk reduction. Ensemble forecasts can assess uncertainty, but they are limited to the uncertainty in a specific modeling system. Many of the current operational flood prediction systems use a multimodel approach to better represent the uncertainty arising from insufficient model structure. This study presents a multimodel approach to building a global flood prediction system using multiple atmospheric reanalysis datasets for river initial conditions and multiple TIGGE forcing inputs to the ECMWF land surface model. A sensitivity study is carried out to clarify the effect of using archive ensemble meteorological predictions and uncoupled land surface models. The probabilistic discharge forecasts derived from the different atmospheric models are compared with those from the multimodel combination. The potential for further improving forecast skill by bias correction and Bayesian model averaging is examined. The results show that the impact of the different TIGGE input variables in the HTESSEL/Catchment-Based Macroscale Floodplain model (CaMa-Flood) setup is rather limited other than for precipitation. This provides a sufficient basis for evaluation of the multimodel discharge predictions. The results also highlight that the three applied reanalysis datasets have different error characteristics that allow for large potential gains with a multimodel combination. It is shown that large improvements to the forecast performance for all models can be achieved through appropriate statistical postprocessing (bias and spread correction). A simple multimodel combination generally improves the forecasts, while a more advanced combination using Bayesian model averaging provides further benefits