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Global hydrological reanalyses are modelled datasets providing information on river discharge evolution everywhere in the world. With multi‐decadal daily timeseries, they provide long‐term context to identify extreme hydrological events such as floods and droughts. By covering the majority of the world's land masses, they can fill the many gaps in river discharge in‐situ observational data, especially in the global South. These gaps impede knowledge of both hydrological status and future evolution and hamper the development of reliable early warning systems for hydrological‐related disaster reduction. River discharge is a natural integrator of the water cycle over land. Global hydrological reanalysis datasets offer an understanding of its spatio‐temporal variability and are therefore critical for addressing the water–energy–food–environment nexus. This paper describes how global hydrological reanalyses can fill the lack of ground measurements by using earth system or hydrological models to provide river discharge time series. Following an inventory of alternative sources of river discharge datasets, reviewing their advantages and limitations, the paper introduces the Copernicus Emergency Management Service (CEMS) Global Flood Awareness System (GloFAS) modelling chain and its reanalysis dataset as an example of a global hydrological reanalysis dataset. It then reviews examples of downstream applications for global hydrological reanalyses, including monitoring of land water resources and ocean dynamics, understanding large‐scale hydrological extreme fluctuations, early warning systems, earth system model diagnostics and the calibration and training of models, with examples from three Copernicus Services (Emergency Management, Marine and Climate Change). [ABSTRACT FROM AUTHOR]

ABSTRACT Heavy rain events or rainstorms of various scales often occur in Hong Kong from April to September. In extremes cases, they lead to serious landslides and flash floods resulting in loss of life, and damage to property and infrastructure. With climate change, extreme rain events are projected to be more frequent and more intense in this region. A system to gauge and label the severity of rainstorms would be useful for identifying and communicating extreme conditions in warning and disaster prevention operations. In parallel, a better understanding of the characteristics of rainstorms would also be important for impact assessments and engineering design purposes. This paper formulates a practical framework to index the magnitude and severity of rainstorms in Hong Kong. An index termed as the Severity Index combining the magnitude of different rainstorm attributes is devised for quantifying the overall severity of rainstorms. This index is flexible to allow tuning for specific applications. [ABSTRACT FROM AUTHOR]

Relationships between rainfall and river discharge are important for governing flood characteristics and predicting flood impacts. Previous studies have examined these relationships, but they lacked the high-resolution precipitation data necessary to analyse rainfall--streamflow correlations for individual flood episodes. The present study addresses this limitation by examining rainfall--streamflow relationships in two topographically and climatically different river basins: the Wabash River basin in Indiana and the Willamette River basin in Oregon, using high-resolution, sub-basin precipitation and discharge data. Results show that flood rainfall--streamflow relationships are highly spatially variable on a sub-basin scale. In the Wabash basin, strong positive correlations exist between rainfall and streamflow near urban areas and slight terrain gradients during flash floods, while weaker correlations between rainfall and streamflow are observed in other areas of the basin and for slow-rise floods. In the Willamette basin, strong positive slow-rise flood rainfall--streamflow relationships occur in referenced gauges in the eastern, mountainous part of the basin, while strong negative correlations occur in non-referenced gauges near reservoirs along the main rivers. Results suggest that in addition to high-resolution rainfall variability, the influence of urbanization, topography and water management on flood rainfall--streamflow relationships needs to be considered in order to forecast local flood impacts better. [ABSTRACT FROM AUTHOR]

Anomalous conditions in the oceans and atmosphere have the potential to be used to enhance the predictability of flood events, enabling earlier warnings to reduce risk. In the Amazon basin, extreme flooding is consistently attributed to warmer or cooler conditions in the tropical Pacific and Atlantic oceans, with some evidence linking floods to other hydroclimatic drivers such as the Madden–Julian Oscillation (MJO). This review evaluates the impact of several hydroclimatic drivers on rainfall and river discharge regimes independently, aggregating all the information of previous studies to provide an up‐to‐date depiction of what we currently know and do not know about how variations in climate impact flooding in the Amazon. Additionally, 34 major flood events that have occurred since 1950 in the Amazon and their attribution to climate anomalies are documented and evaluated. This review finds that despite common agreement within the literature describing the relationship between phases of climate indices and hydrometeorological variables, results linking climate anomalies and flood hazard are often limited to correlation rather than to causation, while the understanding of their usefulness for flood forecasting is weak. There is a need to understand better the ocean–atmosphere response mechanisms that led to previous flood events. In particular, examining the oceanic and atmospheric conditions preceding individual hydrological extremes, as opposed to composite analysis, could provide insightful information into the magnitude and spatial distribution of anomalous sea surface temperatures required to produce extreme floods. Importantly, such an analysis could provide meaningful thresholds on which to base seasonal flood forecasts.This review provides an up‐to‐date depiction of what we currently know and do not know about how climate variability influences Amazon hydrology. Evidence showing the usefulness of hydroclimatic drivers for flood forecasting is weak. Further efforts are required to understand the atmospheric–oceanic processes that have led to previous individual extreme floods. Importantly, such an analysis could provide thresholds of sea surface temperatures in the Pacific and Atlantic oceans on which to base seasonal forecasts to reduce risk. [ABSTRACT FROM AUTHOR]

Medium- to long-range precipitation forecasts are a crucial component in mitigating the impacts of fluvial flood events. Although precipitation is difficult to predict at these lead times, the forecast skill of atmospheric circulation tends to be greater. The study explores using weather patterns (WPs) as a preliminary step in producing forecasts of upper-tail precipitation threshold exceedance probabilities for the UK. The WPs are predefined, discrete states representing daily mean sea-level pressure (MSLP) over a European--North Atlantic domain. The WPs most likely to be associated with flooding are highlighted by calculating upper-tail exceedance probabilities derived from the conditional distributions of regional precipitation given each WP. WPs associated with higher probabilities of extreme precipitation are shown to have occurred during two well-known flood events: the 2014 Somerset Levels floods in southwest England; and Storm Desmond over the northern UK in December 2015. To illustrate the potential of this WP-based prediction framework, a forecast guidance tool called Fluvial Decider is introduced. It is intended for use by hydro-meteorologists in the England and Wales Flood Forecasting Centre (FFC). Forecasts of the MSLP from ensemble prediction systems (EPSs) are assigned to the closest-matching WP, providing daily probabilistic forecasts of WPs out to the chosen lead time. Combining these probabilities with observed precipitation threshold exceedance probabilities provides a parsimonious tool for highlighting potential periods with increased risk of flooding. Model forecasts using the European Centre forMedium-range Weather Forecasts (ECMWF) EPS highlighted both flood events as being at a higher than average risk of heavy extreme precipitation at lead times of over five days. [ABSTRACT FROM AUTHOR]

ABSTRACT Identification of homogeneous regions is a key task in regional frequency analysis to obtain accurate estimates of a given event. Homogeneity testing based on multivariate L-moments has recently been proposed and all studies dealing with application of the methodology using real-world data still focus on the bivariate case. The practical aspects of the trivariate homogeneity tests for maximum annual 1, 3 and 7 day precipitation totals measured at stations in the Czech Republic are investigated. A trivariate model of the precipitation amounts for simulating synthetic homogeneous regions in parametric testing was determined by goodness-of-fit tests based on the Cramér-von Mises and Vuong statistics and Akaike and Bayesian information criteria while considering selected trivariate exchangeable Archimedean, fully nested Archimedean and mixed C-vine copulas in the copula model test space. Each of the regions into which the area of the Czech Republic is divided meets the homogeneity condition when using both the parametric and non-parametric L-moment homogeneity tests and considering three mixed C-vine copula models given by the bivariate Gumbel copula for two unconditional pair-copulas and normal, Frank or Plackett copula families for the conditional pair-copula for simulating synthetic homogeneous regions. [ABSTRACT FROM AUTHOR]

ABSTRACT A brief case study is provided of a striking example of vertical and horizontal jet coupling associated with the upper jet level as well as upper- and lower-level jet coupling; these jet interactions also supported the development of elevated convection and led to flash flooding. The case constitutes a faithful, real-world verification of what has been suggested in idealized conceptual models by several investigators for similar situations of elevated convection with excessive precipitation. [ABSTRACT FROM AUTHOR]

Extreme rain storms are known for triggering devastating flash floods in various regions of Europe and particularly along the Mediterranean coasts. Despite recent notable advances in weather forecasting, most operational early warning systems for extreme rainstorms and flash floods are still based on rainfall measurements from rain gauges and weather radars, rather than on forecasts. As a result, warning lead times are bounded to a few hours and warnings are usually issued when the event is already taking place. This work proposes a novel early warning system for heavy precipitation events in Europe, aimed at identifying forecasts of extreme rainfall accumulations over short durations and within small-size catchments prone to flash flooding. The system is based on the recently developed European Precipitation Index based on simulated Climatology (EPIC), which is calculated using COSMO-LEPS ensemble weather forecasts and subsequently fitted with gamma distributions at each time step of the forecast horizon. Probabilistic exceedence of warning thresholds is calculated and alert points are generated where potentially extreme events are detected. Comparison of daily runs over 22 months with observed rainstorm events and flash floods in Europe denotes a probability of detection up to 90%, corresponding to 45 events correctly predicted, with average lead time of 32 h. Copyright © 2012 Royal Meteorological Society [ABSTRACT FROM AUTHOR]

Empirical conditional probabilities of extreme monthly precipitation averaged over three regions of the southern part of the La Plata basin were calculated as a function of three atmospheric indices: two of them represent low level moisture convergence and the third is related to the mid tropospheric circulation over southern South America. The first region includes southern Paraguay, northeastern Argentina, north of Uruguay and the western sector of southern Brazil, the second region stretches over part of southern Brazil, while the third region, surrounding the Plata Estuary extends over western Uruguay and eastern Argentina between 37 ° S and 32 ° S. Regional monthly precipitation was considered extreme when it exceeded its mean value plus one standard deviation. Conditional empirical probabilities of Months with Extreme Precipitation ( MEP) are more than twice and even four times higher than climatic probabilities when they are calculated under the restriction that the atmospheric indices were beyond certain extreme thresholds empirically defined. Combined conditional probability is even higher when the values of two or the three indices over their respective thresholds take place at the same time, but these cases are less frequent. The index that renders higher conditional probabilities is the one that accounts for the low level moisture convergence in a region that is basically to the west and outside of the three regions. This reflects the fact that most of the mesoconvective systems, which originate to the west of these regions and then move eastwards, produce heavy precipitation that lead to monthly accumulated extremes. Copyright © 2013 Royal Meteorological Society [ABSTRACT FROM AUTHOR]

A methodology of exploratory data analysis investigating the phenomenon of orographic precipitation enhancement is proposed. The precipitation observations obtained from three Swiss Doppler weather radars are analysed for the major precipitation event of August 2005 in the Alps. Image processing techniques are used to detect significant precipitation cells/pixels from radar images while filtering out spurious effects due to ground clutter. The contribution of topography to precipitation patterns is described by an extensive set of topographical descriptors computed from the digital elevation model at multiple spatial scales. Additionally, the motion vector field is derived from subsequent radar images and integrated into a set of topographic features to highlight the slopes exposed to main flows. Following the exploratory data analysis with a recent algorithm of spectral clustering, it is shown that orographic precipitation cells are generated under specific flow and topographic conditions. Repeatability of precipitation patterns in particular spatial locations is found to be linked to specific local terrain shapes, e.g. at the top of hills and on the upwind side of the mountains. This methodology and our empirical findings for the Alpine region provide a basis for building computational data-driven models of orographic enhancement and triggering of precipitation. Copyright © 2011 Royal Meteorological Society [ABSTRACT FROM AUTHOR]

A small but intense convective system affected parts of east Devon during the early hours of 30 October 2008, producing an estimated 200 mm of precipitation, including locally over 20 cm of hail, within a 3 h period. This exceptional storm and its environment are studied here from an observational perspective. Upper air and satellite observations show that the storm developed within an environment characterized by a trend for increasing instability and dynamic forcing for ascent, associated with an approaching upper level cold pool and small positive potential vorticity anomaly. Analysis of surface observations reveals that convective development was strongly focussed by localized, persistent low-level convergence and moisture convergence in the vicinity of a mesoscale surface low pressure area, which rapidly deepened before becoming slow moving over east Devon. Radar, wind profiler and other available observations are used to describe the development and evolution of the convective system, and to identify some additional factors contributing to the exceptional rain- and hail-fall totals. Finally, the role that real-time, simultaneous analysis of these various observation types could play in nowcasting of localized, extreme rainfall events is discussed. © Crown Copyright 2010. Reproduced with the permission of the Controller of HMSO. Published by John Wiley & Sons, Ltd [ABSTRACT FROM AUTHOR]