Projected near-term changes in three types of heat waves over China under RCP4.5
The changes in three aspects of frequency, intensity and duration of the compound, daytime and nighttime heat waves (HWs) over China during extended summer (May–September) in a future period of the mid-21st century (FP; 2045–2055) under RCP4.5 scenario relative to present day (PD; 1994–2011) are investigated by two models, MetUM-GOML1 and MetUM-GOML2, which comprise the atmospheric components of two state-of-the-art climate models coupled to a multi-level mixed-layer ocean model. The results show that in the mid-21st century all three types of HWs in China will occur more frequently with strengthened intensity and elongated duration relative to the PD. The compound HWs will change most dramatically, with the frequency in the FP being 4–5 times that in the PD, and the intensity and duration doubling those in the PD. The changes in daytime and nighttime HWs are also remarkable, with the changes of nighttime HWs larger than those of daytime HWs. The future changes of the three types of HWs in China in two models are similar in terms of spatial patterns and area-averaged quantities, indicating these projected changes of HWs over the China under RCP4.5 scenario are robust. Further analyses suggest that projected future changes in HWs over China are determined mainly by the increase in seasonal mean surface air temperatures with change in temperature variability playing a minor role. The seasonal mean temperature increase is due to the increase in surface downward longwave radiation and surface shortwave radiation. The increase in downward longwave radiation results from the enhanced greenhouse effect and increased water vapour in the atmosphere. The increase in surface shortwave radiation is the result of the decreased aerosol emissions, via direct aerosol–radiation interaction and indirect aerosol–cloud interaction over southeastern and northeastern China, and the reduced cloud cover related to a decrease in relative humidity.
KeywordsHeat wave Heat wave type Future change China Coupled models
This study is supported by the National Natural Science Foundation of China under Grants 41505037 and 41875103, by the Applied Basic Research Foundation of Yunnan Province (2016FB078), and by the UK-China Research & Innovation Partnership Fund through the Met Office Climate Science for Service Partnership (CSSP) China as part of the Newton Fund. QS is supported by the China Scholarship Council. BD is supported by the U.K. National Centre for Atmospheric Science-Climate (NCAS-Climate) at the University of Reading. The authors like to thank three anonymous reviewers for their constructive comments on the earlier version of the paper.
- Chen Y, Chen W, Su Q, Luo F, Sparrow S, Tian F, Dong B, Tett SFB, Lott FC, Wallom D (2019) Anthropogenic warming has substantially increased the likelihood of July 2017-like heat waves over Central-Eastern China [in “Explaining Extremes of 2017 from a Climate Perspective”]. Bull Amer Meteor Soc 100(1):S91–S95. https://doi.org/10.1175/BAMS-D-18-0087.1 CrossRefGoogle Scholar
- Karl TR, Knight RW (1997) The 1995 Chicago heat wave: how likely is a recurrence? Bull Am Meteor Soc 78(6):1107–1120. https://doi.org/10.1175/1520-0477(1997)078%3c1107:tchwhl%3e2.0.co;2 CrossRefGoogle Scholar
- Lamarque J-F, Bond TC, Eyring V, Granier C, Heil A, Klimont Z, Lee D, Liousse C, Mieville A, Owen B (2010) Historical (1850–2000) gridded anthropogenic and biomass burning emissions of reactive gases and aerosols: methodology and application. Atmos Chem Phys 10(15):7017–7039. https://doi.org/10.5194/acp-10-7017-2010 CrossRefGoogle Scholar
- Lamarque J-F, Kyle GP, Meinshausen M, Riahi K, Smith SJ, van Vuuren DP, Conley AJ, Vitt F (2011) Global and regional evolution of short-lived radiatively-active gases and aerosols in the representative concentration pathways. Clim Change 109:191. https://doi.org/10.1007/s10584-011-0155-0 CrossRefGoogle Scholar
- Su Q, Dong B (2019) Recent decadal changes in heat waves over China: drivers and mechanisms. J ClimGoogle Scholar
- Sun Y, Song L, Yin H, Zhou B, Hu T, Zhang X, Stott P (2016) Human influence on the 2015 extreme high temperature events in Western China [in “Explaining Extremes of 2015 from a Climate Perspective”]. Bull Am Meteor Soc 97(12):S102–S106. https://doi.org/10.1175/bams-d-16-0158.1 CrossRefGoogle Scholar
- Twomey S (1977) Influence of pollution on shortwave albedo of clouds. J Atmos Sci 34(7):1149–1152. https://doi.org/10.1175/1520-0469(1977)034%3c1149:tiopot%3e2.0.co;2 CrossRefGoogle Scholar
- Walters D, Best M, Best M, Bushell A, Copsey D, Copsey D, Edwards J, Falloon P, Harris C, Lock A, Manners J, Morcrette C (2011) The Met Office Unified Model global atmosphere 3.0/3.1 and JULES global land 3.0/3.1 configurations. Geosci Model Dev 4(4):919. https://doi.org/10.5194/gmd-4-919-2011 CrossRefGoogle Scholar
- Walters D, Wood N, Vosper S, Milton S (2014) ENDGame: a new dynamical core for seamless atmospheric prediction. Met Office documentation. http://www.metoffice.gov.uk/media/pdf/s/h/ENDGameGOVSciv2.0.pdf
- Walters D, Brooks M, Boutle I, Melvin T, Stratton R, Vosper S, Wells H, Williams K, Wood N, Allen T (2017) The Met Office unified model global atmosphere 6.0/6.1 and JULES global land 6.0/6.1 configurations. Geosci Model Dev 10(4):1487–1520. https://doi.org/10.5194/gmd-10-1487-2017 CrossRefGoogle Scholar
- Zhou TJ, Ma SM, Zou LW (2014b) Understanding a hot summer in Central Eastern China: summer 2013 in context of multimodel trend analysis [in “Explaining Extremes of 2013 from a Climate Perspective”]. Bull Am Meteor Soc 95(9):S54–S57Google Scholar