Observational analysis indicates significant decadal changes in daytime, nighttime, and compound (both daytime and nighttime) heat waves (HWs) over China across the mid-1990s, featuring a rapid increase in frequency, intensity, and spatial extent. The variations of these observed decadal changes are assessed by the comparison between the present day (PD) of 1994–2011 and the early period (EP) of 1964–81. The compound HWs change most remarkably in all three aspects, with frequency averaged over China in the PD tripling that in the EP and intensity and spatial extent nearly doubling. The daytime and nighttime HWs also change significantly in all three aspects. A set of numerical experiments is used to investigate the drivers and physical processes responsible for the decadal changes of the HWs. Results indicate the predominant role of the anthropogenic forcing, including changes in greenhouse gas (GHG) concentrations and anthropogenic aerosol (AA) emissions in the HW decadal changes. The GHG changes have dominant impacts on the three types of HWs, while the AA changes make significant influences on daytime HWs. The GHG changes increase the frequency, intensity, and spatial extent of the three types of HWs over China both directly via the strengthened greenhouse effect and indirectly via land–atmosphere and circulation feedbacks in which GHG-change-induced warming in sea surface temperature plays an important role. The AA changes decrease the frequency and intensity of daytime HWs over Southeastern China through mainly aerosol–radiation interaction, but increase the frequency and intensity of daytime HWs over Northeastern China through AA-change-induced surface–atmosphere feedbacks and dynamical changes related to weakened East Asian summer monsoon.
On 21-25 July 2017 a record-breaking heatwave occurred in Central Eastern China, affecting nearly half of the national population and causing severe impacts on public health, agriculture and infrastructure. Here, we compare attribution results from two UK Met Office Hadley Centre models, HadGEM3-GA6 and weather@home (HadAM3P driving 50 km HadRM3P). Within HadGEM3-GA6 July 2017-like heatwaves were unequaled in the ensemble representing the world without human influences. Such heatwaves became approximately a 1 in 50 year event and increased by a factor of 4.8 (5%-95% range of 3.1 to 8.0) in weather@home as a result of human activity. Considering the risk ratio (RR) for the full range of return periods shows a discrepancy at all return times between the two model results. Within weather@home a range of different counterfactual sea surface temperature (SST) patterns were used, whereas HadGEM3-GA6 used a single estimate. The global mean difference in SST (between factual and counterfactual simulations) is shown to be related to the generalised extreme value (GEV) location parameter and consequently the RR, especially for return periods of less than 50 years. It is suggested that a suitable range of SST patterns are used for future attribution studies to ensure that this source of uncertainty is represented within the simulations and subsequent attribution results. It is shown that the risk change between factual and counterfactual simulations is not purely a simple shift in the distribution (i.e. change in GEV location parameter). For return periods greater than 50 years, the GEV shape parameter is found to strongly influence the RR determined with the GEV scale parameter affecting only the most severe events.
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