Kunhui Ye

Abstract:

More frequent heatwaves in Europe are posing considerable risks to human health, infrastructure, and ecosystems. However, the contributions of external forcing factors such as well-mixed greenhouse gases (GHGs) and aerosols remain to be better quantified. Here, using model outputs from the Large Ensemble Single Forcing Model Intercomparison Project (LESFMIP), a recent atmospheric reanalysis and a machine learning method—self-organising maps (SOMs), we attribute European heatwave trends during 1940–2020 to various external forcings. The Europe-averaged heatwave trend during 1940–2020 (0.87 days per decade) is well captured by the multi-model mean (MMM) response with GHGs dominating the trend. The positive heatwave trend in GHGs and ozone is offset by the effects of aerosols during 1940–1979, leading to weak negative heatwave trends. In contrast, the increase in GHGs has driven about half (53 ± 17%; MMM and model-spread) of the strong heatwave trends in 1980–2020 (2.5 days per decade), amplified by the reduction in aerosols (23 ± 15%). This highlights the increasing risk of more frequent heatwaves in Europe if GHG emissions continue to rise without significant mitigation measures. Analysis of atmospheric circulation by SOMs reveals that four major atmospheric circulation patterns, dominated by a blocking high anomaly, are linked to the most spatially-intense European summer heatwaves. A relatively large increase in the occurrence of blocking-like atmospheric circulation has likely exacerbated heatwave trends in Southern and Eastern Europe in 1980–2020. However, this atmospheric circulation trend is much weaker in the model response, and also seems to be outside the internal variability in most of the models. This may partly explain the underestimated heatwave trends in Southern and Eastern Europe. Constraining and further understanding of the thermodynamic and dynamic response in the LESFMIP models is important for attributing and predicting the multi-annual and decadal variability of climate and weather extremes.

Abstract:

Atlantic multidecadal variability (AMV) is a well-known mode of climate variability with well-understood impacts on several aspects of Northern Hemisphere climate. However, its impact on heatwaves, a type of heat extremes that is increasingly affecting human societies, remains less well understood. The influence of AMV on extratropical summer heatwaves in the Northern Hemisphere is analyzed with a suite of coupled climate model experiments from the Decadal Climate Prediction Project. Our analysis suggests that AMV exerts substantial influence on the heatwave frequency (HWF) and heatwave number (HWN) of heatwaves over subtropics and midlatitudes in the Northern Hemisphere. Compared to the widespread seasonal mean warming response, these heatwave hotspots are less expansive geographically. The warm AMV phase (AMV+) as opposed to the cold phase (AMV−) drives a global stationary wave anomaly that links hotspots of HWF and HWN increases over North America, North Africa, central/western Asia, and parts of East Asia. Such dynamic impacts of AMV on heatwaves are more significant than the thermodynamic impacts of a warmer ocean surface. Hence, mean surface warming alone due to the warming effects of AMV+ versus AMV− does not necessarily equate to more frequent heatwaves. Furthermore, precipitation and surface heat fluxe responses further amplify the HWF increases. By further comparing the tropical and extratropical portions of AMV imposed in model simulations, we emphasize that linear and nonlinear interactions of these features strongly shape the impacts of AMV. We further discuss the mechanisms for and causes of model-observation discrepancies and inter-model uncertainties in the influence of AMV on atmospheric circulation and summer heatwaves, in terms of atmospheric circulation response in North Atlantic-Europe and jet waveguide effects. This highlights some challenges in pinpointing the influence of AMV on heatwaves, and improved understanding of it is necessary for more accurate predictions and projections of heatwaves.

Abstract:

The winter North Atlantic Oscillation (NAO) is the dominant pattern of atmospheric circulation variability over the North Atlantic region. It influences climate and weather such as surface air temperatures downstream over Eurasia through establishing a large-scale teleconnection, but past studies on the NAO’s downstream teleconnection have been largely limited to observational data, and further evidence of downstream impacts and associated mechanisms from comprehensive climate modeling is desirable. This study quantifies and analyzes this teleconnection on an interannual timescale by using both ERA5 reanalysis, and five large ensembles from four climate simulation models. A particular focus is placed on dynamical pathways, as well as variability among ensemble members that modulates the teleconnection strength. Results suggest that NAO signals are propagated downstream by Rossby waves, efficiently transmitted through waveguides along both the polar and subtropical jet streams to Eastern Eurasia; while heat can be advected weakly from upstream, advection plays a rather local effect inducing temperature anomalies from the Pacific Ocean onshore. Multiple linear regression shows that internal climate variability significantly modulates the teleconnection: a more locally dominant NAO pattern, and narrower waveguides could strengthen the teleconnection. These two factors combine to explain up to 70% of variance in the teleconnection strength, with each contributing almost equally. Reanalysis data marginally agree with the regression model (1.9 standardized residuals higher in strength), suggesting potential model biases in jets and the NAO variability. Monitoring these modulating factors would be crucial to understanding downstream climate predictability and improving climate prediction models linked to the NAO.

Abstract:

Sea ice and snow are crucial components of the cryosphere and the climate system. Both sea ice and spring snow in the Northern Hemisphere (NH) have been decreasing at an alarming rate in a changing climate. Changes in NH sea ice and snow have been linked with a variety of climate and weather extremes including cold spells, heatwaves, droughts and wildfires. Understanding of these linkages will benefit the predictions of climate and weather extremes. However, existing work on this has been largely fragmented and is subject to large uncertainties in physical pathways and methodologies. This has prevented further substantial progress in attributing climate and weather extremes to sea ice and snow change, and will potentially risk the loss of a critical window for effective climate change mitigation. In this review, we synthesize the current progress in attributing climate and weather extremes to sea ice and snow change by evaluating the observed linkages, their physical pathways and uncertainties in these pathways, and suggesting ways forward for future research efforts. By adopting the same framework for both sea ice and snow, we highlight their combined influence and the cryospheric feedback to the climate system. We suggest that future research will benefit from improving observational networks, addressing the causality and complexity of the linkages using multiple lines of evidence, adopting large-ensemble approaches and artificial intelligence, achieving synergy between different methodologies/disciplines, widening the context, and coordinated international collaboration.

Abstract:

Arctic amplification (AA), the phenomenon by which Arctic surface temperatures are warming faster than the global average, may have significant unexplored impacts on temperature-related mortality in human populations across Canada. We explore the role of Arctic sea ice loss, a key driver of AA, in changing cold temperature extremes across Canada and their impact on human mortality. We use a multi-model ensemble of climate simulations from the Polar Amplification Model Intercomparison Project and a distributed lag nonlinear mortality model in 27 regions covering Canada to quantify the role of Arctic sea ice loss in changing human mortality in the cold season. We find that despite a robust increase in 5th percentile temperatures across eastern Canada, there is no detectable decrease in mortality associated with the most extreme cold, due to mortality in many regions having low sensitivity to warming of cold extremes. The study attributes the temperature-related mortality impact of a physical process, namely Arctic sea ice loss, and highlights Canada’s robust adaptation to extreme cold.