INTENSE
INTElligent use of climate models for adaptatioN to non-Stationary hydrological Extremes.
Project leader
Dates
Project staff
Dr Stephen Blenkinsop
Dr Steven Chan
Dr Xiaofeng Li
Dr Selma Guerreiro
Dr Elizabeth Lewis
Dr Haider Ali
Dr Geert Lenderink, KNMI
Dr Elizabeth Kendon, UKMO,
Dr Renaud Barbero, Irstea
Sponsors
European Research Council (ERC) Consolidators Grant
Partners
The Met Office
Reading University
SMHI
IITGN
Washington University
NCAR
University of Adelaide
University of New South Wales
UCAR
KNMI
Princeton
GEWEX
Description
Perhaps the most important questions in climate change impacts research today focus on understanding how extremes of precipitation are responding to global warming. These extremes:
- can cause flooding and droughts
- can result in substantial damages to infrastructure systems
- 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:
- We do not fully understand the processes that cause extreme precipitation and how it changes under current climate variability.
- 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 is analysing the response of precipitation extremes to global warming by constructing a new, quality controlled global sub-daily rainfall dataset (GSDR). We are using this with other datasets and high-resolution climate modelling to quantify:
- the nature and drivers of global extremes
- their response to natural variability and forcing across multiple timescales
We are examining the influence of local thermodynamics (through temperature scaling) and large-scale circulation modes on observed extremes using new statistical methods. These methods recognise the non-stationary nature of precipitation. We are using these to identify climate model deficiencies in the representation of precipitation extremes, and in particular, in short-duration, intense rainfall.
The project is linking up with the latest developments in the field of high-resolution convection permitting modelling. It is providing a new synergy between data, models and theory to enable the development of innovative downscaling approaches. We are 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.
The key questions for this project are:
- How has sub-daily rainfall changed over the last century, across continents, climate regimes and seasons?
- How does rainfall at different timescales vary with atmospheric temperature and atmospheric moisture as the atmosphere warms?
- How do large-scale atmospheric and oceanic features influence or modulate the observed changes in rainfall extremes, the clustering of extremes and the variability between ‘drought’ and ‘flood’ periods, in different climate regimes and seasons?
- What is the influence of climate model resolution and structure on the simulation of rainfall extremes for different climate regimes and seasons?
- What is the likely response to warming of rainfall and rainfall extremes at different timescales across different climate regimes?
- How can we use information from both high-resolution and coarse-resolution climate models in a more intelligent way to inform climate change adaptation decision making to better manage extreme hydrological events?