A probabilistic climate change assessment for Europe

A probabilistic climate change assessment for Europe

Moghim, Sanaz (Sharif University of Technology)
Teuling, Adriaan J. (Wageningen University & Research)
Uijlenhoet, R. (TU Delft Water Resources; TU Delft Water Management; Hydrology and Quantitative Water Management Group; Wageningen University & Research)

Water Management

2022

Globally, the impacts of climate change can vary across different regions. This study uses a probability framework to evaluate recent historical (1976–2016) and near-future projected (until 2049) climate change across Europe using Climate Research Unit and ensemble climate model datasets (under RCPs 2.6 and 8.5). A historical assessment shows that although the east and west of the domain experienced the largest and smallest increase in temperature, changes in precipitation are not as smooth as temperature. Results indicate that the maximum changes between distributions of the variables (temperature and precipitation) mainly occur at extreme percentiles (e.g., 10% and 90%). A group analysis of four subregions of Europe, namely east (G1), north (G2), west/south (G3), and UK/Ireland (G4), shows that G1 and G4 are expected to have the largest increase in temperature and precipitation extremes, respectively. Although maximum increases in temperature in G3 and G4 occur at larger percentiles, G1 and G2 experience maximum increases at both large and small percentiles. The maximum increase of precipitation over the study domain, however, occurs mainly at larger extremes. To quantify changes in the distribution of projection (2020–2049) relative to the historical reference (1976–2005), two measures are defined, namely a change in occurrences (KS statistic) and intensities at different quantiles (Δ). Results confirm that the temperature distribution tends to shift to higher temperatures. Changes in distribution and extremes of precipitation are spatially variable. Furthermore, extremes are expected to be intensified under RCP 8.5. The quantile analysis and defined measures reveal changes in the entire probability distribution, reflecting possible climate changes in the future.

climate change
climate indicators
extreme weather events
impact assessment
probabilistic framework
quantile analysis

http://resolver.tudelft.nl/uuid:2ca709b3-a009-46f4-90ec-f570d37ed357

https://doi.org/10.1002/joc.7604

2022-09-05

0899-8418

International Journal of Climatology, 42 (13), 6699-6715

Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.

Institutional Repository

journal article

© 2022 Sanaz Moghim, Adriaan J. Teuling, R. Uijlenhoet