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There is high confidence that precipitation extremes are projected to become more frequent and severe and, to a lesser extent, that their seasonality may change. However, these precipitation characteristics are dealt with separately, without examining whether magnitude and seasonality are jointly projected to change. Here we assess how the seasonality and magnitude of precipitation extremes are jointly projected to change for different climate scenarios. We perform analyses at the global scale using nine global climate models and four different emission scenarios. We identify large areas of the globe where the magnitude of the extremes is expected to increase as the emissions increase; at the same time, large changes in the seasonality of these extremes are projected to impact regions mainly located in the tropical and sub-tropical areas. These changes could impact our response and mitigation efforts and our resilience against such phenomena in response to climate change.

Floods represent a major natural hazard in Africa, causing over 27 000 fatalities during the period 1950–2019. Despite its relevance, little is known about changes in flood hazard across this continent due to the lack of long-term high-quality streamflow records. Here we use a newly assembled discharge dataset of African rivers, and provide a long-term comprehensive view of flood hazard across this continent. We show that the annual maximum peak discharge does not exhibit a monotonic pattern, but overall decreasing trends prior to 1980 and increasing trends afterwards, especially in western and southern Africa. Our results indicate that these differing trends can be ascribed to changes in extreme precipitation around 1980. Moreover, these changes in intense precipitation pre/post 1980 are due to increased thunderstorm activity associated with enhanced convective available potential energy and zonal vertical shear driven by cooling temperature trends over western Africa. The changes in flood hazard in southern Africa can be tied to changes in Namibia low-level jet. Therefore, the observed increase in flooding since 1980 suggests that it would be beneficial to improve the monitoring, modeling and communication of flood hazard to reduce the socio-economic impacts of these events.

The City of Cedar Rapids was significantly affected by the June 2008 flood. However, little is known about the role anthropogenic warming during this event, not only in terms of hydrologic response but also of impacts. Here we use a continuous distributed hydrologic model forced with precipitation with and without external forcing and show that the impacts of this flood were likely magnified because of increased anthropogenic warming; compared to the baseline scenario with the external forcing removed, this event was ∼1.28-fold larger in flood extent, an approximate 3.4-time larger in the number of affected buildings, and an estimated 5.8- and 7.1-time larger in structural and content damage, respectively. While much of the effort up to this point has focused on the attribution of the physical hazard, our results highlight the cascading increase of the contribution of the external forcing (mainly from anthropogenic forcing) moving from hazard to human impacts.

Within the warm conveyor belt of extra-tropical cyclones, atmospheric rivers (ARs) are the key synoptic features which deliver the majority of poleward water vapour transport, and are associated with episodes of heavy and prolonged rainfall. ARs are responsible for many of the largest winter floods in the mid-latitudes resulting in major socioeconomic losses; for example, the loss from United Kingdom (UK) flooding in summer/winter 2012 is estimated to be about $1.6 billion in damages. Given the well-established link between ARs and peak river flows for the present day, assessing how ARs could respond under future climate projections is of importance in gauging future impacts from flooding. We show that North Atlantic ARs are projected to become stronger and more numerous in the future scenarios of multiple simulations from five state-of-the-art global climate models (GCMs) in the fifth Climate Model Intercomparison Project (CMIP5). The increased water vapour transport in projected ARs implies a greater risk of higher rainfall totals and therefore larger winter floods in Britain, with increased AR frequency leading to more flood episodes. In the high emissions scenario (RCP8.5) for 2074–2099 there is an approximate doubling of AR frequency in the five GCMs. Our results suggest that the projected change in ARs is predominantly a thermodynamic response to warming resulting from anthropogenic radiative forcing.

This paper examines the severity and extent of flooding caused by six predecessor rain events (PREs) over the Midwest United States. PREs are areas of heavy rainfall that occur about 1000 km ahead of landfalling tropical cyclones. While recent studies have mostly focused on the synoptic conditions associated with PREs, little is known about the hydrologic impacts of these events. Here, we use discharge data collected by the US Geological Survey to perform flood analyses at the regional scale. We first examine the number of stations at which a PRE caused an annual maximum flood peak. We then compute the flood ratio, defined as the ratio between the flood peak magnitude caused by the PRE and the at-site, expected 10 year flood peak magnitude. These results indicate that PREs are responsible for significant flooding over the Midwest United States, including highly populated areas like Chicago, Illinois and Detroit, Michigan.

In recent years, the United States has been severely affected by numerous tropical cyclones (TCs) which have caused massive damages. While media attention mainly focuses on coastal losses from storm surge, these TCs have inflicted significant devastation inland as well. Yet, little is known about the relationship between TC-related inland flooding and economic losses. Here we introduce a novel methodology that first successfully characterizes the spatial extent of inland flooding, and then quantifies its relationship with flood insurance claims. Hurricane Ivan in 2004 is used as illustration. We empirically demonstrate in a number of ways that our quantified inland flood magnitude produces a very good representation of the number of inland flood insurance claims experienced. These results highlight the new technological capabilities that can lead to a better risk assessment of inland TC flood. This new capacity will be of tremendous value to a number of public and private sector stakeholders dealing with disaster preparedness.