Spatial and temporal variability of drought in the arid region of China and its relationships to teleconnection indices

• Drought pattern of SCPSDI was obtained by REOF and wavelet analysis.
• Relationships between RPCs and climate indices were analyzed.
• Four moisture-related spatial patterns were objectively defined.
• The PDSI increased in Xinjiang, while decreased in the eastern Hexi Corridor.
• The drought evolution of this arid region may affected by VPA, AO, and NAO.

SummaryWe studied the drought patterns in the arid region of northwestern China between 1960 and 2010 using the Palmer Drought Severity Index (PDSI). The general evolution of drought was obtained by empirical orthogonal function (EOF), rotated empirical orthogonal function (REOF), the Mann–Kendall test, and the continuous wavelet transform method. Additionally, relationships between rotated principal component time series (RPCs) and seven selected climate indices were analyzed. The results showed that: (1) Four moisture-related spatial patterns (North Xinjiang, western South Xinjiang, Central Xinjiang, and the Hexi Corridor) were objectively defined by REOF analysis. These patterns are related to distinct geographical areas and are associated with distinct temporal variations. (2) The PDSI increased significantly in most regions of Xinjiang, while decreased in the eastern Hexi Corridor. The significant 4–8 year band is the major period band for the annual and seasonal PDSI derived. (3) The seasonal REOFs (RPCs) and EOFs (PCs) have consistent spatial distribution patterns with the annual REOF. The seasonal trends of PDSI are also the same as the annual PDSI trends, indicating space–time consistency between annual PDSI and seasonal PDSI. (4) The drought evolution in this region is affected by the area of northern hemisphere polar vortex, the Arctic Oscillation, and the North Atlantic Oscillation. In addition, the changes of drought in South Xinjiang and the Hexi Corridor may also be associated with the Tibetan Plateau High. Changes in drought pattern are expected to have a strong impact on the economic livelihood of the region, especially for agricultural production.