INTENSE: “INTElligent use of climate models for adaptatioN to non-Stationary hydrological Extremes” (2M ERC Consolidators Grant) provides funded core of a community effort into the collection and analysis of sub-daily precipitation data and model outputs.
Perhaps the most important questions in climate change impacts research today focus on understanding how extremes of precipitation are responding to global warming, as these can cause flooding and droughts, result in substantial damages to infrastructure systems and have detrimental effects on ecosystems. There is now strong evidence linking specific extreme rainfall events, or an increase in their numbers, to the human influence on climate.
Despite this, it is still uncertain how hydrological extremes will change with global warming. The problem is two-fold: firstly, we do not fully understand the processes that cause extreme precipitation and how it changes under current climate variability. Secondly, we need to understand and model how the global climate system will respond (and already is responding) to atmospheric warming, and whether there are dangerous or important thresholds in terms of changes to precipitation extremes.
INTENSE will comprehensively analyse the response of precipitation extremes to global warming by constructing a new global sub-daily precipitation dataset, and using this together with other datasets and high-resolution climate modelling to quantify the nature and drivers of global precipitation extremes and their response to natural variability and forcing across multiple timescales. Specifically, the project will examine the influence of local thermodynamics and large-scale circulation modes on observed precipitation extremes using new statistical methods which recognise the non-stationary nature of precipitation, and use these to identify climate model deficiencies in the representation of precipitation extremes. INTENSE will provide a new synergy between data, models and theory to enable the development of innovative downscaling approaches using information from high- and coarse- resolution climate models and process understanding from observations in a new, more intelligent way, to explore how rainfall extremes will respond to a warmer world and the implications for adaptation strategies.