Spatiotemporal impact of antecedent drought on hot extremes from the
nonstationary risk perspective: A case study in eastern China
Abstract
Hot extremes may adversely impact human health and agricultural
production. Owing to anthropogenic and climate changes, the close and
dynamic interaction between drought and hot extremes in most areas of
China need to be revisited from the perspective of nonstationarity. This
study therefore proposes a time-varying Copula-based model to describe
the nonstationary dependence structure of extreme temperature (ET) and
antecedent soil moisture condition to quantify the dynamic risk of hot
extremes conditioned on dry/wet condition. This study proposed a new
approach to identify the soil moisture driving law over extreme
temperature from the point view of tail monotonicity and nonstationary
risk assessment. Owing to the LTI-RTD (left tail increasing and right
tail decreasing) tail monotonicity for dependence structure of these two
extremes derived from most areas, the driving laws of soil moisture over
ET follows DDL1-WDL1 laws (DDL1: drier antecedent soil moisture
condition would trigger a higher risk of ET; WDL1: wetter antecedent
soil moisture condition would alleviate the occurrence risk of ET).
Because of the spatiotemporal divergence of sensitivity index derived
from tail monotonicity (SITM), we can conclude that the spatial and
temporal heterogeneity of response degree of ET over the variations of
antecedent dry/wet conditions is evident. Incorporation of
nonstationarity and tail monotonicity helps identify the changes of
driving mechanism (laws) between soil moisture and hot extremes. From
the comparison of different kinds of nonstationary behaviours over the
spatial distribution of conditional probability of ET (CP1), the
dependence nonstationarity can impose greater variations on the spatial
distribution of conditional risk of ET given antecedent dry condition
(CP1).