A probabilistic climate change assessment for Europe. (21st March 2022)

• Record Type: Journal Article
• Authors: Moghim, Sanaz; Teuling, Adriaan J.; Uijlenhoet, Remko
• Is Part Of: International journal of climatology. Volume 42:Number 13(2022)
• Page Start: 6699
• Page End: 6715
• Publication Date: 2022-03-21
• Subjects: climate change -- climate indicators -- extreme weather events -- impact assessment -- probabilistic framework -- quantile analysis; Climatology -- Periodicals; Climat -- Périodiques; Climatologie -- Périodiques; 551.605
• DOI: 10.1002/joc.7604
• Languages: English
• ISSNs: 0899-8418

Abstract

Abstract: 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 To quantify changes in the distribution of projection (2020–2049) relative to the historical reference (1976–2005), two measures are defined, namely a change in occurrences (KS statistic) and intensities at different quantiles (Δ).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. Abstract : Maximum differences (Max Δ) between projection (2020–2049) and historical (1976–2005) period at different percentiles including 10th, 50th, 90th percentiles (median and extremes) for (a) temperature (T) and (b) precipitation (P) under RCP 2.6 in four subregions including G1, G2, G3, and G4 (top‐bottom). Max Δ is shown in the first columns of the panels and different percentiles are shown in the second columns [dark blue (10%), yellow (50%), and dark pink (90%), shown in colour bar at top]. Numbers 1, 2, 3, and 4 refer to four subregions (G1, G2, G3, and G4, respectively).