| Summary: | Northwestern China (NW China) is characterized by complex regional precipitation pattern, but there are few discussions about the intra-regional precipitation variability (IRPV) in NW China. The purposes of the present study are to quantify the long-term IRPV and to investigate the driving mechanism of IRPV in NW China for the period AD 580-1979. This study focuses on Gansu, Ningxia, Sha’anxi and the eastern part of Qinghai. To improve the climatic significance of the result, the study area is further divided into two sub-regions, namely the arid region (Region A) and the semi-arid region (Region B). Since the transition zone of the Asian Summer Monsoon (ASM) and the Westerlies locates in the study region, the regional precipitation is highly sensitive to the fluctuations of various climatic driving forces and hence, characterized by strong regional precipitation disparity. In the present study, historical documentary records of drought/ flood events are employed to reconstruct the decadal precipitation index (PI) for Region A (PI_A) and Region B (PI_B). The IRPV index is derived from the differences of precipitation index between the two sub-regions. The verification result shows that the IRPV index is able to reflect the long-term spatial hydro-climatic disparity between regions in NW China for the last millennium. Besides, wavelet analysis is employed to reveal the cyclic components of PIA, PIB and IRPV in NW China. The results show that a distinctive ~120-200 year periodicity band exists during the Little Ice Age (LIA, c. AD 1400-1900), which coincides with the period when the IRPV extremes are frequently observed. Various climatic factors are examined for the potential driving relationships with IRPV, including ASM, Arctic Oscillation (AO), Atlantic Multi-decadal Oscillation (AMO), El Niño Southern Oscillation (ENSO), North Atlantic Oscillation (NAO), Pacific Decadal Oscillation (PDO) and China temperature. Results of wavelet coherence analysis show that the influences of AO, AMO, NAO and PDO on IRPV vary ...
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