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Large-Scale Precipitation Variability Over Northwest China Inferred from Tree Rings

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Large-Scale Precipitation Variability Over Northwest China Inferred from Tree Rings 1JULY 2011 F A N G E T A L . 3457 Large-Scale Precipitation Variability over Northwest China Inferred from Tree Rings KEYAN FANG,XIAOHUA GOU, AND FAHU CHEN Key Laboratory of Western China’s Environmental Systems (Ministry of Education), Lanzhou University, Lanzhou, China EDWARD COOK,JINBAO LI,BRENDAN BUCKLEY, AND ROSANNE D’ARRIGO Tree-Ring Lab, Lamont-Doherty Earth Observatory, Columbia University, Palisades, New York (Manuscript received 23 June 2010, in final form 18 January 2011) ABSTRACT A preliminary study of a point-by-point spatial precipitation reconstruction for northwestern (NW) China is explored, based on a tree-ring network of 132 chronologies. Precipitation variations during the past ;200– 400 yr (the common reconstruction period is from 1802 to 1990) are reconstructed for 26 stations in NW China from a nationwide 160-station dataset. The authors introduce a ‘‘search spatial correlation contour’’ method to locate candidate tree-ring predictors for the reconstruction data of a given climate station. Calibration and verification results indicate that most precipitation reconstruction models are acceptable, except for a few reconstructions (stations Hetian, Hami, Jiuquan, and Wuwei) with degraded quality. Additionally, the au- thors compare four spatial precipitation factors in the instrumental records and reconstructions derived from a rotated principal component analysis (RPCA). The northern and southern Xinjiang factors from the in- strumental and reconstructed data agree well with each other. However, differences in spatial patterns be- tween the instrumentation and reconstruction data are also found for the other two factors, which probably result from the relatively poor quality of a few stations. Major drought events documented in previous studies—for example, from the 1920s through the 1930s for the eastern part of NW China—are reconstructed in this study. 1. Introduction areas (China Daily, 17 February 2009), which regret- tably extends to the 1950s for most stations. The brevity At present, water resources are crucial in dry north- of the instrumental record can limit our ability to eval- western (NW) China for both the civic and communal uate current drought severity relative to long-term vari- water supplies, as well as for agriculture activities. The ability inherent in climate systems. We therefore draw severe drought in more than eight provinces in the upon the paleoclimate records available to us to place semihumid-to-arid region of northern China in early the current drought regimes into a longer context of the 2009 is one such case. During that period, 4.6 million natural variability of climate in our study region in NW people were short of drinking water and nearly 30 mil- China (the area north of 358N and west of 1108E). Several lion people suffered from water shortages for agricul- tree-ring based climate reconstructions have been pub- ture activities, forcing the central government to enact lished for a geographic point or small areas of dozens its top-level emergency drought response for the first of square kilometers in this region (e.g., Fang et al. 2009, time. This 2009 drought ranks as the most extreme dur- 2010b; Gou et al. 2008; Li et al. 2006; Liu et al. 2004; Shao ing the period of instrumental monitoring for many et al. 2005; Sheppard et al. 2004; Yuan et al. 2003; Zhang et al. 2003). In this paper, we aim to establish the drought footprint for the entire region and to analyze its broad Corresponding author address: Keyan Fang, Key Laboratory of spatiotemporal features. Western China’s Environmental Systems (Ministry of Education), Lanzhou University, 222 South Tianshui Road, Lanzhou 73000, The wide distribution and annual resolution of tree China. rings make it possible to use quantitative methods to E-mail: [email protected] not only reconstruct local climate variability but also DOI: 10.1175/2011JCLI3911.1 Ó 2011 American Meteorological Society Unauthenticated | Downloaded 10/01/21 02:00 AM UTC 3458 JOURNAL OF CLIMATE VOLUME 24 reconstruct large-scale spatial climate patterns (Cook difference is that we used a modified PPR method for et al. 1999). Previous dendroclimatic studies have used reconstruction based on a ‘‘search spatial correlation a tree-ring network to reconstruct the two leading drought contours’’ (see section 2d for details). fields of central High Asia (Fang et al. 2010a), including Since regional precipitation variability for much of large parts of NW China. This research first delimited the NW China is directly related to monsoon dynamics study region into the western and eastern portions be- (Fang et al. 2010a; Li et al. 2009; Shi et al. 2007), a re- cause of their distinct drought variability and recon- constructed PPR precipitation dataset can be used to structed the first principle component of drought indices investigate long-term precipitation history and its re- for both portions. The field reconstruction, however, has lations with the Asian monsoon. Spatial precipitation a limited ability to investigate drought history over space reconstruction would be more challenging relative to because it contains a priori spatial patterns of instrumental a PDSI reconstruction, because tree rings in this area are data in its design. For example, temporal variations in the often highly correlated with PDSI (Fang et al. 2009, spatial boundaries of the specified drought modes cannot 2010b; Li et al. 2006). We describe the tree-ring network, be identified with this method. A point-by-point regres- climate data, and regression and other analytical methods sion (PPR) spatial climate reconstruction method can in section 2. Special attention is paid to the regression ameliorate this situation by reconstructing each climate methods because they differ slightly from previous stud- point independently, thereby allowing for ‘‘local control’’ ies. For each station, the regression models are validated over the reconstruction at each point (Cook et al. 1999). by independent data to test for temporal stability. The One of the most notable examples of these methods in the regression models are further examined according to recent literature is the development of the North America their ability to model the temporal variability and recover Drought Atlas (NADA), the methodology of which was the spatial patterns. These results and a discussion are first described by Cook et al. (1999) and later fully pub- presented in section 3, and section 4 summarizes the re- lished in Cook et al. (2004). Spatial reconstruction of all sults of this study. climate points in a region also facilitates an examination of underlying climate forcing via a comparison of the re- construction with results from various general circulation 2. Data and methods models (GCMs). Several subsequent papers utilized this a. Study region set of gridded reconstructions for detailed analyses of the causes of drought over a large portion of North America Located in east-central Asia (Fig. 1), NW China fea- (e.g., Seager 2007). tures a dry continental climate with large temperature The PPR-based spatial reconstructions have been con- gradients between winter and summer. According to the ducted for many areas, such as continental North America precipitation records used herein, it is relatively humid 21 (Cook et al. 1999, 2004; Meko et al. 1993). Recently, Cook (more than ;200 mm yr ) for the northwestern and et al. (2010) published the first ensemble-based PPR re- southeastern portions of NW China, while it is very dry 21 construction for East Asia by calibrating 327 tree-ring (less than 60 mm yr ) in between, such as in southern chronologies with 534 grid points of the Palmer drought Xinjiang, western Gansu, and western Neimenggu (Fig. 2). severity index (PDSI) for monsoonal Asia. We introduce Peak rainfall occurs in June for western NW China herein a precipitation reconstruction using modified PPR (Xinjiang), where the May–July seasonal precipitation methods. Our study region in the arid northwest has accounts for 36% of the annual precipitation. For the perhaps the densest tree-ring network in China, because eastern region (areas other than Xinjiang), peak rainfall of the availability of old-growth and climate-sensitive occurs in August, and July–September precipitation forests, though with far less spatial coverage than the accounts for 64% of the yearly total precipitation. Pre- previously noted studies of Cook et al. (1999, 2004) and vious studies documented differences in climate vari- Meko et al. (1993) over North America. The target data ability between western and eastern NW China (Chen for reconstruction are derived from a nationwide 160- et al. 2008; Li et al. 2009; Qian and Qin 2008; Shi et al. station precipitation dataset (see climate data section) 2007; Zou et al. 2005). For example, in recent decades an that contains 26 stations within NW China. We also se- increase in precipitation has been observed for western lected this climate dataset as predictands because it is a NW China, while the opposite is true for the eastern basic and frequently used dataset for China (e.g., Gemmer portion (Shi et al. 2007). et al. 2004; Lau and Weng 2001). One difference from b. Tree-ring data the study by Cook et al. (2010) is that we aim to re- construct a 26-station precipitation dataset for NW China Tree-ring samples were collected from the old-growth from a tree-ring network of 132 chronologies. Another forests in scattered mountainous ranges distributed Unauthenticated | Downloaded 10/01/21 02:00 AM UTC 1JULY 2011 F A N G E T A L . 3459 FIG. 1. Locations of meteorological stations (circles) in NW China and surrounding tree-ring chronologies (triangles). The search spatial correlation coefficients are also illustrated for the Wulumuqi and Xining stations, which were calculated using precipitation of the station tar- geted for reconstruction and nearby precipitation grids. Tree-ring chronologies located within the area of a specified correlation contour are included as candidate chronologies for re- construction purpose.
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