Concurrent compound dry and hot events(CDHEs)amplified more damange on the ecosystems and human society than individual extremes.Under climate change,compound dry and hot events become more frequent on a global scale....Concurrent compound dry and hot events(CDHEs)amplified more damange on the ecosystems and human society than individual extremes.Under climate change,compound dry and hot events become more frequent on a global scale.This paper proposes a mathematical method to quantitatively attribute changes of CDHEs to changes of precipitation,change in temperature and change in the dependence between precipitation and temperature.The attribution is achieved by formulating the total differential equation of the return period of CDHEs among Meta-gaussian model.A case study of China is devised based on monthly precipitation and temperature data during the period from 1921 to 2020 for 80 major river basins.It is found that temperature is the main driving factor of increases in CDHEs for 49 major river basins in China,except for the upper and middle reaches of the Yangtze River.In West China,precipitation changes drove the increase in CDHEs in 18 river basins(23%),particularly in parts of North Xinjiang,Qinghai and Gansu.On the other hand,dependence between precipitation and temperature dominated changes of CDHEs in 13 river basins(16%)of China with other factors,including parts of South China,East China and Northwestern China.Furthermore,changes in both the mean and spread of precipitation and temperature can also contribute to changes in CDHEs.展开更多
基金This work was supported by the National Key Research and Development Program of China(Grant No.2021YFC3001000)the National Natural Science Foundation of China(Grant No.51979295)the Guangdong Provincial Department of Science and Technology(Grant No.2019ZT08G090).
文摘Concurrent compound dry and hot events(CDHEs)amplified more damange on the ecosystems and human society than individual extremes.Under climate change,compound dry and hot events become more frequent on a global scale.This paper proposes a mathematical method to quantitatively attribute changes of CDHEs to changes of precipitation,change in temperature and change in the dependence between precipitation and temperature.The attribution is achieved by formulating the total differential equation of the return period of CDHEs among Meta-gaussian model.A case study of China is devised based on monthly precipitation and temperature data during the period from 1921 to 2020 for 80 major river basins.It is found that temperature is the main driving factor of increases in CDHEs for 49 major river basins in China,except for the upper and middle reaches of the Yangtze River.In West China,precipitation changes drove the increase in CDHEs in 18 river basins(23%),particularly in parts of North Xinjiang,Qinghai and Gansu.On the other hand,dependence between precipitation and temperature dominated changes of CDHEs in 13 river basins(16%)of China with other factors,including parts of South China,East China and Northwestern China.Furthermore,changes in both the mean and spread of precipitation and temperature can also contribute to changes in CDHEs.
