Widespread flooding occurred across northwest Europe during the winter of 2013/14, resulting in large socioeconomic damages. In the historical record, extreme hydrological events have been connected ...with intense water vapour transport. Here we show that water vapour transport has higher medium-range predictability compared with precipitation in the winter 2013/14 forecasts from the European Centre for Medium-Range Weather Forecasts. Applying the concept of potential predictability, the transport is found to extend the forecast horizon by 3 days in some European regions. Our results suggest that the breakdown in precipitation predictability is due to uncertainty in the horizontal mass convergence location, an essential mechanism for precipitation generation. Furthermore, the predictability increases with larger spatial averages. Given the strong association between precipitation and water vapour transport, especially for extreme events, we conclude that the higher transport predictability could be used as a model diagnostic to increase preparedness for extreme hydrological events.
•Potential monetary benefits of early flood warnings are estimated based on the forecasts of the continental-scale European Flood Awareness System (EFAS).•Benefits are of the order of 400 Euro for ...every 1 Euro invested.•A sensitivity analysis is performed in order to test the uncertainty in the method. The largest source so uncertainty are the underlying damage data and the damage reduction percentages.•Clear evidence that there is likely a substantial monetary benefit in this cross-border continental-scale flood early warning system.
Effective disaster risk management relies on science-based solutions to close the gap between prevention and preparedness measures. The consultation on the United Nations post-2015 framework for disaster risk reduction highlights the need for cross-border early warning systems to strengthen the preparedness phases of disaster risk management, in order to save lives and property and reduce the overall impact of severe events. Continental and global scale flood forecasting systems provide vital early flood warning information to national and international civil protection authorities, who can use this information to make decisions on how to prepare for upcoming floods. Here the potential monetary benefits of early flood warnings are estimated based on the forecasts of the continental-scale European Flood Awareness System (EFAS) using existing flood damage cost information and calculations of potential avoided flood damages. The benefits are of the order of 400 Euro for every 1 Euro invested. A sensitivity analysis is performed in order to test the uncertainty in the method and develop an envelope of potential monetary benefits of EFAS warnings. The results provide clear evidence that there is likely a substantial monetary benefit in this cross-border continental-scale flood early warning system. This supports the wider drive to implement early warning systems at the continental or global scale to improve our resilience to natural hazards.
The atmospheric composition analysis and forecast for the European Copernicus Atmosphere Monitoring Services (CAMS) relies on biomass-burning fire emission estimates from the Global Fire Assimilation ...System (GFAS). The GFAS is a global system and converts fire radiative power (FRP) observations from MODIS satellites into smoke constituents. Missing observations are filled in using persistence, whereby observed FRP values from the previous day are progressed in time until a new observation is recorded. One of the consequences of this assumption is an increase of fire duration, which in turn translates into an increase of emissions estimated from fires compared to what is available from observations. In this study persistence is replaced by modelled predictions using the Canadian Fire Weather Index (FWI), which describes how atmospheric conditions affect the vegetation moisture content and ultimately fire duration. The skill in predicting emissions from biomass burning is improved with the new technique, which indicates that using an FWI-based model to infer emissions from FRP is better than persistence when observations are not available.
In winter, heavy precipitation and floods along the west coasts of midlatitude continents are largely caused by intense water vapor transport (integrated vapor transport (IVT)) within the atmospheric ...river of extratropical cyclones. This study builds on previous findings that showed that forecasts of IVT have higher predictability than precipitation, by applying and evaluating the European Centre for Medium‐Range Weather Forecasts Extreme Forecast Index (EFI) for IVT in ensemble forecasts during three winters across Europe. We show that the IVT EFI is more able (than the precipitation EFI) to capture extreme precipitation in forecast week 2 during forecasts initialized in a positive North Atlantic Oscillation (NAO) phase; conversely, the precipitation EFI is better during the negative NAO phase and at shorter leads. An IVT EFI example for storm Desmond in December 2015 highlights its potential to identify upcoming hydrometeorological extremes, which may prove useful to the user and forecasting communities.
Key Points
Evaluate the ECMWF Extreme Forecast Index (EFI) for water vapor transport (IVT) across Europe
IVT EFI is better in capturing extreme rainfall in week 2 forecasts that are initialized in a positive North Atlantic Oscillation (NAO)
Precipitation EFI is better at capturing extreme rainfall in forecasts initialized in a negative NAO and at shorter lead times
The ability to monitor floods with sensors mounted on aircraft and satellites has been known for decades. Early launches of satellites and the availability of aerial photography allowed investigation ...of the potential to support flood monitoring from as far as space. There have been notable studies on integrating data from these instruments with flood modeling since the late 1990s. There is now a consensus among space agencies to strengthen the support that satellites can offer. This trend has stimulated more research in this area, and significant progress has been achieved in recent years in fostering our understanding of the ways in which remote sensing can support or even advance flood modeling. This research goes considerably further than using a wet/dry flood map for model validation as in early studies of this type. Therefore, this paper aims to review recent and current efforts to aid advancing flood inundation modeling from space.
Air temperature has been the most commonly used exposure metric in assessing relationships between thermal stress and mortality. Lack of the high-quality meteorological station data necessary to ...adequately characterize the thermal environment has been one of the main limitations for the use of more complex thermal indices. Global climate reanalyses may provide an ideal platform to overcome this limitation and define complex heat and cold stress conditions anywhere in the world. In this study, we explored the potential of the Universal Thermal Climate Index (UTCI) based on ERA5 – the latest global climate reanalysis from the European Centre for Medium-Range Weather Forecasts (ECMWF) – as a health-related tool. Employing a novel ERA5-based thermal comfort dataset ERA5-HEAT, we investigated the relationships between the UTCI and daily mortality data in 21 cities across 9 European countries. We used distributed lag nonlinear models to assess exposure-response relationships between mortality and thermal conditions in individual cities. We then employed meta-regression models to pool the results for each city into four groups according to climate zone. To evaluate the performance of ERA5-based UTCI, we compared its effects on mortality with those for the station-based UTCI data. In order to assess the additional effect of the UTCI, the performance of ERA5-and station-based air temperature (T) was evaluated. Whilst generally similar heat- and cold-effects were observed for the ERA5-and station-based data in most locations, the important role of wind in the UTCI appeared in the results. The largest difference between any two datasets was found in the Southern European group of cities, where the relative risk of mortality at the 1st percentile of daily mean temperature distribution (1.29 and 1.30 according to the ERA5 vs station data, respectively) considerably exceeded the one for the daily mean UTCI (1.19 vs 1.22). These differences were mainly due to the effect of wind in the cold tail of the UTCI distribution. The comparison of exposure-response relationships between ERA5-and station-based data shows that ERA5-based UTCI may be a useful tool for definition of life-threatening thermal conditions in locations where high-quality station data are not available.
•The suitability of ERA5-based UTCI for health-related studies was demonstrated.•ERA5-based UTCI was evaluated with respect to station-based observations.•ERA5-and station-based air temperature was assessed as a reference thermal metric.•Consistent exposure-response relationships were modelled by ERA5 and station data.•The effect of wind on mortality in cold environments calls for future investigation.
Seasonal streamflow predictions provide a critical management tool for water managers in the American Southwest. In recent decades, persistent prediction errors for spring and summer runoff volumes ...have been observed in a number of watersheds in the American Southwest. While mostly driven by decadal precipitation trends, these errors also relate to the influence of increasing temperature on streamflow in these basins. Here we show that incorporating seasonal temperature forecasts from operational global climate prediction models into streamflow forecasting models adds prediction skill for watersheds in the headwaters of the Colorado and Rio Grande River basins. Current dynamical seasonal temperature forecasts now show sufficient skill to reduce streamflow forecast errors in snowmelt‐driven regions. Such predictions can increase the resilience of streamflow forecasting and water management systems in the face of continuing warming as well as decadal‐scale temperature variability and thus help to mitigate the impacts of climate nonstationarity on streamflow predictability.
Key Points
Seasonal temperature forecasts from climate prediction models are skillful over the headwaters of the Colorado and Rio Grande river basins
Adding temperature information to current operational seasonal streamflow forecasts in snowmelt‐driven basins improves forecast skill
Temperature forecasts help mitigate impacts of nonstationarity on U.S. Southwest streamflow predictability under increasing temperatures
Abstract
Despite the scientific progress in drought detection and forecasting, it remains challenging to accurately predict the corresponding impact of a drought event. This is due to the complex ...relationships between (multiple) drought indicators and adverse impacts across different places/hydroclimatic conditions, sectors, and spatiotemporal scales. In this study, we explored these relationships by analyzing the impacts of the severe 2018–2019 central European drought event in Germany. We first computed the standardized precipitation index (SPI), the standardized precipitation evaporation index (SPEI), the standardized soil moisture index (SSMI) and the standardized streamflow index (SSFI) over various accumulation periods, and then related these indicators to sectorial losses from the European drought impact report inventory (EDII) and media sources. To cope with the uncertainty associated with both drought indicators and impact data, we developed a fuzzy method to categorize them. Lastly, we applied the method at the region level (EU NUTS1) by correlating monthly time series. Our findings revealed strong and significant relationships between drought indicators and impacts over different accumulation periods, albeit in some cases region-specific and time-variant. Furthermore, our analysis established the interconnectedness between various sectors, which displayed systematically co-occurring impacts. As such, our work provides a new framework to explore drought indicators-impacts dependencies across space, time, sectors, and scales. In addition, it emphasizes the need to leverage available impact data to better forecast drought impacts.
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.
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