| 1. |
- Dance, Sarah L., et al.
(författare)
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Improvements in Forecasting Intense Rainfall : Results from the FRANC (Forecasting Rainfall Exploiting New Data Assimilation Techniques and Novel Observations of Convection) Project
- 2019
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Ingår i: Atmosphere. - : MDPI. - 2073-4433 .- 2073-4433. ; 10:3
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Forskningsöversikt (refereegranskat)abstract
- The FRANC project (Forecasting Rainfall exploiting new data Assimilation techniques and Novel observations of Convection) has researched improvements in numerical weather prediction of convective rainfall via the reduction of initial condition uncertainty. This article provides an overview of the project's achievements. We highlight new radar techniques: correcting for attenuation of the radar return; correction for beams that are over 90% blocked by trees or towers close to the radar; and direct assimilation of radar reflectivity and refractivity. We discuss the treatment of uncertainty in data assimilation: new methods for estimation of observation uncertainties with novel applications to Doppler radar winds, Atmospheric Motion Vectors, and satellite radiances; a new algorithm for implementation of spatially-correlated observation error statistics in operational data assimilation; and innovative treatment of moist processes in the background error covariance model. We present results indicating a link between the spatial predictability of convection and convective regimes, with potential to allow improved forecast interpretation. The research was carried out as a partnership between University researchers and the Met Office (UK). We discuss the benefits of this approach and the impact of our research, which has helped to improve operational forecasts for convective rainfall events.
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| 2. |
- Mason, David C., et al.
(författare)
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Robust algorithm for detecting floodwater in urban areas using synthetic aperture radar images
- 2018
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Ingår i: Journal of Applied Remote Sensing. - : SPIE-SOC PHOTO-OPTICAL INSTRUMENTATION ENGINEERS. - 1931-3195. ; 12:4
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Tidskriftsartikel (refereegranskat)abstract
- Flooding is a major hazard in both rural and urban areas worldwide, but it is in urban areas that the impacts are most severe. High-resolution synthetic aperture radar (SAR) sensors are able to detect flood extents in urban areas during both day- and night-time. If obtained in near real time, these flood extents can be used for emergency flood relief management or as observations for assimilation into flood forecasting models. A method for detecting flooding in urban areas using near real-time SAR data is developed and extensively tested under a variety of scenarios involving different flood events and different images. The method uses an SAR simulator in conjunction with LiDAR data of the urban area to predict areas of radar shadow and layover in the image caused by buildings and taller vegetation. Of the urban water pixels visible to the SAR, the flood detection accuracy averaged over the test examples is 83%, with a false alarm rate of 9%. The results indicate that flooding can be detected in the urban area to reasonable accuracy but that this accuracy is limited partly by the SAR's poor visibility of the urban ground surface due to shadow and layover. (C) The Authors. Published by SPIE under a Creative Commons Attribution 3.0 Unported License.
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| 3. |
- Arnal, Louise, et al.
(författare)
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Skilful seasonal forecasts of streamflow over Europe?
- 2018
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Ingår i: Hydrology and Earth System Sciences. - : Copernicus GmbH. - 1027-5606 .- 1607-7938. ; 22:4, s. 2057-2072
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Tidskriftsartikel (refereegranskat)abstract
- This paper considers whether there is any added value in using seasonal climate forecasts instead of historical meteorological observations for forecasting streamflow on seasonal timescales over Europe. A Europe-wide analysis of the skill of the newly operational EFAS (European Flood Awareness System) seasonal streamflow forecasts (produced by forcing the Lisflood model with the ECMWF System 4 seasonal climate forecasts), benchmarked against the ensemble streamflow prediction (ESP) forecasting approach (produced by forcing the Lisflood model with historical meteorological observations), is undertaken. The results suggest that, on average, the System 4 seasonal climate forecasts improve the streamflow predictability over historical meteorological observations for the first month of lead time only (in terms of hindcast accuracy, sharpness and overall performance). However, the predictability varies in space and time and is greater in winter and autumn. Parts of Europe additionally exhibit a longer predictability, up to 7 months of lead time, for certain months within a season. In terms of hindcast reliability, the EFAS seasonal streamflow hindcasts are on average less skilful than the ESP for all lead times. The results also highlight the potential usefulness of the EFAS seasonal streamflow forecasts for decision-making (measured in terms of the hindcast discrimination for the lower and upper terciles of the simulated streamflow). Although the ESP is the most potentially useful forecasting approach in Europe, the EFAS seasonal streamflow forecasts appear more potentially useful than the ESP in some regions and for certain seasons, especially in winter for almost 40 % of Europe. Patterns in the EFAS seasonal streamflow hindcast skill are however not mirrored in the System 4 seasonal climate hindcasts, hinting at the need for a better understanding of the link between hydrological and meteorological variables on seasonal timescales, with the aim of improving climate-model-based seasonal streamflow forecasting.
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| 4. |
- Boelee, Leonore, et al.
(författare)
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Estimation of uncertainty in flood forecasts—A comparison of methods
- 2019
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Ingår i: Journal of Flood Risk Management. - : Wiley. - 1753-318X. ; 12:Supplement: 1
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Tidskriftsartikel (refereegranskat)abstract
- The scientific literature has many methods for estimating uncertainty, however, there is a lack of information about the characteristics, merits, and limitations of the individual methods, particularly for making decisions in practice. This paper provides an overview of the different uncertainty methods for flood forecasting that are reported in literature, concentrating on two established approaches defined as the ensemble and the statistical approach. Owing to the variety of flood forecasting and warning systems in operation, the question "which uncertainty method is most suitable for which application" is difficult to answer readily. The paper aims to assist practitioners in understanding how to match an uncertainty quantification method to their particular application using two flood forecasting system case studies in Belgium and Canada. These two specific applications of uncertainty estimation from the literature are compared, illustrating statistical and ensemble methods, and indicating the information and output that these two types of methods offer. The advantages, disadvantages and application of the two different types of method are identified. Although there is no one "best" uncertainty method to fit all forecasting systems, this review helps to explain the current commonly used methods from the available literature for the non-specialist.
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| 5. |
- Di Napoli, Claudia, et al.
(författare)
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Assessing heat-related health risk in Europe via the Universal Thermal Climate Index (UTCI)
- 2018
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Ingår i: International journal of biometeorology. - : SPRINGER. - 0020-7128 .- 1432-1254. ; 62:7, s. 1155-1165
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Tidskriftsartikel (refereegranskat)abstract
- In this work, the potential of the Universal Thermal Climate Index (UTCI) as a heat-related health risk indicator in Europe is demonstrated. The UTCI is a bioclimate index that uses a multi-node human heat balance model to represent the heat stress induced by meteorological conditions to the human body. Using 38 years of meteorological reanalysis data, UTCI maps were computed to assess the thermal bioclimate of Europe for the summer season. Patterns of heat stress conditions and non-thermal stress regions are identified across Europe. An increase in heat stress up to 1 A degrees C is observed during recent decades. Correlation with mortality data from 17 European countries revealed that the relationship between the UTCI and death counts depends on the bioclimate of the country, and death counts increase in conditions of moderate and strong stress, i.e., when UTCI is above 26 and 32 A degrees C. The UTCI's ability to represent mortality patterns is demonstrated for the 2003 European heatwave. These findings confirm the importance of UTCI as a bioclimatic index that is able to both capture the thermal bioclimatic variability of Europe, and relate such variability with the effects it has on human health.
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| 6. |
- Di Napoli, Claudia, et al.
(författare)
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Verification of Heat Stress Thresholds for a Health-Based Heat-Wave Definition
- 2019
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Ingår i: Journal of Applied Meteorology and Climatology. - : AMER METEOROLOGICAL SOC. - 1558-8424 .- 1558-8432. ; 58:6, s. 1177-1194
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Tidskriftsartikel (refereegranskat)abstract
- Heat waves represent a threat to human health and excess mortality is one of the associated negative effects. A health-based definition for heat waves is therefore relevant, especially for early warning purposes, and it is here investigated via the universal thermal climate index (UTCI). The UTCI is a bioclimate index elaborated via an advanced model of human thermoregulation that estimates the thermal stress induced by air temperature, wind speed, moisture, and radiation on the human physiology. Using France as a test bed, the UTCI was computed from meteorological reanalysis data to assess the thermal stress conditions associated with heat-attributable excess mortality in five cities. UTCI values at different climatological percentiles were defined and evaluated in their ability to identify periods of excess mortality (PEMs) over 24 years. Using verification metrics such as the probability of detection (POD), the false alarm ratio (FAR), and the frequency bias (FB), daily minimum and maximum heat stress levels equal to or above corresponding UTCI 95th percentiles (15 degrees +/- 2 degrees C and 34.5 degrees +/- 1.5 degrees C, respectively) for 3 consecutive days are demonstrated to correlate to PEMs with the highest sensitivity and specificity (0.69 <= POD <= 1, 0.19 <= FAR <= 0.46, 1 <= FB <= 1.48) than minimum, maximum, and mean heat stress level singularly and other bioclimatological percentiles. This finding confirms the detrimental effect of prolonged, unusually high heat stress at day- and nighttime and suggests the UTCI 95th percentile as a health-meaningful threshold for a potential heat-health watch warning system.
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| 7. |
- Emerton, Rebecca, et al.
(författare)
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Developing a global operational seasonal hydro-meteorological forecasting system : G1oFAS-Seasonal v1.0
- 2018
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Ingår i: Geoscientific Model Development. - : COPERNICUS GESELLSCHAFT MBH. - 1991-959X .- 1991-9603. ; 11:8, s. 3327-3346
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Tidskriftsartikel (refereegranskat)abstract
- 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 hydrometeorological forecasting system: G1oFAS-Seasonal. Developed as an extension of the Global Flood Awareness System (G1oFAS), G1oFAS-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 hydrometeorological components and computational framework of G1oFAS-Seasonal, alongside the forecast products available, before discussing initial evaluation results and next steps.
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| 8. |
- Emerton, Rebecca E., et al.
(författare)
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What is the most useful approach for forecasting hydrological extremes during El Niño?
- 2019
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Ingår i: Environmental Research Communications (ERC). - : IOP PUBLISHING LTD. - 2515-7620. ; 1:3
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Tidskriftsartikel (refereegranskat)abstract
- In the past, efforts to prepare for the impacts of El Nino-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 Nino 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 Nino: 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 Nino, 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 Nino, GloFAS-seasonal forecasts are typically more useful.
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| 9. |
- Kauffeldt, Anna, et al.
(författare)
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Imbalanced land surface water budgets in a numerical weather prediction system
- 2015
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Ingår i: Geophysical Research Letters. - 0094-8276 .- 1944-8007. ; 42:11, s. 4411-4417
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Tidskriftsartikel (refereegranskat)abstract
- There has been a significant increase in the skill and resolution of numerical weather prediction models (NWPs) in recent decades, extending the time scales of useful weather predictions. The land surface models (LSMs) of NWPs are often employed in hydrological applications, which raises the question of how hydrologically representative LSMs really are. In this paper, precipitation (P), evaporation (E), and runoff (R) from the European Centre for Medium-Range Weather Forecasts global models were evaluated against observational products. The forecasts differ substantially from observed data for key hydrological variables. In addition, imbalanced surface water budgets, mostly caused by data assimilation, were found on both global (P-E) and basin scales (P-E-R), with the latter being more important. Modeled surface fluxes should be used with care in hydrological applications, and further improvement in LSMs in terms of process descriptions, resolution, and estimation of uncertainties is needed to accurately describe the land surface water budgets.
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| 10. |
- Mehring, P., et al.
(författare)
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What is going wrong with community engagement? : How flood communities and flood authorities construct engagement and partnership working
- 2018
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Ingår i: Environmental Science and Policy. - : ELSEVIER SCI LTD. - 1462-9011 .- 1873-6416. ; 89, s. 109-115
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Tidskriftsartikel (refereegranskat)abstract
- In this paper, we discuss the need for flood risk management in England that engages stakeholders with flooding and its management processes, including knowledge gathering, planning and decision-making. By comparing and contrasting how flood communities experience 'community engagement' and 'partnership working', through the medium of an online questionnaire, with the process's and ways of working that the Environment Agency use when 'working with others', we demonstrate that flood risk management is caught up in technocratic ways of working derived from long-standing historical practices of defending agricultural land from water. Despite the desire to move towards more democratised ways of working which enable an integrated approach to managing flood risk, the technocratic framing still pervades contemporary flood risk management. We establish that this can disconnect society from flooding and negatively impacts the implementation of more participatory approaches designed to engage flood communities in partnership working. Through the research in this paper it becomes clear that adopting a stepwise, one-size-fits-all approach to engagement fails to recognise that communities are heterogenous and that good engagement requires gaining an understanding of the social dimensions of a community. Successful engagement takes time, effort and the establishment of trust and utilises social learning and pooling of knowledge to create a better understanding of flooding, and that this can lead to increasing societal connectivity to flooding and its impacts.
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