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Extreme events are widely studied across the world because of their major implications for many aspects of society and especially floods. These events are generally studied in terms of precipitation or temperature extreme indices that are often not adapted for regions affected by floods caused by snowmelt. The rain on snow index has been widely used, but it neglects rain-only events which are expected to be more frequent in the future. In this study, we identified a new winter compound index and assessed how large-scale atmospheric circulation controls the past and future evolution of these events in the Great Lakes region. The future evolution of this index was projected using temperature and precipitation from the Canadian Regional Climate Model large ensemble (CRCM5-LE). These climate data were used as input in Precipitation Runoff Modelling System (PRMS) hydrological model to simulate the future evolution of high flows in three watersheds in southern Ontario. We also used five recurrent large-scale atmospheric circulation patterns in north-eastern North America and identified how they control the past and future variability of the newly created index and high flows. The results show that daily precipitation higher than 10 mm and temperature higher than 5 ∘C were necessary historical conditions to produce high flows in these three watersheds. In the historical period, the occurrences of these heavy rain and warm events as well as high flows were associated with two main patterns characterized by high Z500 anomalies centred on eastern Great Lakes (HP regime) and the Atlantic Ocean (South regime). These hydrometeorological extreme events will still be associated with the same atmospheric patterns in the near future. The future evolution of the index will be modulated by the internal variability of the climate system, as higher Z500 on the east coast will amplify the increase in the number of events, especially the warm events. The relationship between the extreme weather index and high flows will be modified in the future as the snowpack reduces and rain becomes the main component of high-flow generation. This study shows the value of the CRCM5-LE dataset in simulating hydrometeorological extreme events in eastern Canada and better understanding the uncertainties associated with internal variability of climate.
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Global warming is expected to affect both the frequency and severity of extreme weather events, though projections of the response of these events to climate warming remain highly uncertain. The range of changes reported in the climate modelling literature is very large, sometimes leading to contradictory results for a given extreme weather event. Much of this uncertainty stems from the incomplete understanding of the physics of extreme weather processes, the lack of representation of mesoscale processes in coarse-resolution climate models, and the effect of natural climate variability at multi-decadal time scales. However, some of the spread in results originates simply from the variety of scenarios for future climate change used to drive climate model simulations, which hampers the ability to make generalizations about predicted changes in extreme weather events. In this study, we present a meta-analysis of the literature on projected future extreme weather events in order to quantify expected changes in weather extremes as a function of a common metric of global mean temperature increases. We find that many extreme weather events are likely to be significantly affected by global warming. In particular, our analysis indicates that the overall frequency of global tropical cyclones could decrease with global warming but that the intensity of these storms, as well as the frequency of the most intense cyclones could increase, particularly in the northwestern Pacific basin. We also found increases in the intensity of South Asian monsoonal rainfall, the frequency of global heavy precipitation events, the number of North American severe thunderstorm days, North American drought conditions, and European heatwaves, with rising global mean temperatures. In addition, the periodicity of the El Niño–Southern Oscillation may decrease, which could, in itself, influence extreme weather frequency in many areas of the climate system.