Suchergebnisse

Abstract. Aridity indices have been widely used in climate
classification. However, there is
not enough evidence for their ability in identifying the multiple climate
types in areas with
complex topography and landscape, especially in those areas with a
transition climate. This
study compares a traditional meteorological aridity index (AI), defined as the
ratio of precipitation (P) to potential evapotranspiration (PET), with a
hydrological aridity index, the
evaporative stress index (ESI) defined as the ratio of actual
evapotranspiration (AET) to PET
in the Heihe River Basin (HRB) of arid northwestern China. PET was estimated
using the
Penman–Monteith and Hamon methods. The aridity indices were calculated using
the high-resolution climate data simulated with a regional climate model for the
period of 1980–2010.
The climate classified by AI shows a climate type for the upper basin and a
second type for the middle and lower basin, while three different climate
types are found using ESI, each for one
river basin, indicating that only ESI is able to identify a transition climate
zone in the middle
basin. The difference between the two indices is also seen in the
interannual variability and
extreme dry/wet events. The magnitude of variability in the middle basin
is close to that in
the lower basin for AI, but different for ESI. AI had a larger magnitude of the
relative interannual
variability and a greater decreasing rate from 1980 to 2010 than ESI, suggesting the
role of local
hydrological processes in moderating extreme climate events. Thus, the
hydrological aridity
index is better than the meteorological aridity index for climate
classification in the arid Heihe
River Basin.