Moisture and Temperature Covariability Over the Southeastern Tibetan Plateau During the Past Nine Centuries
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1AUGUST 2020 W A N G E T A L . 6583 Moisture and Temperature Covariability over the Southeastern Tibetan Plateau during the Past Nine Centuries JIANGLIN WANG Key Laboratory of Desert and Desertification, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou, China BAO YANG Key Laboratory of Desert and Desertification, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou, and CAS Center for Excellence in Tibetan Plateau Earth Sciences, Chinese Academy of Sciences, Beijing, China FREDRIK CHARPENTIER LJUNGQVIST Department of History, Stockholm University, and Bolin Centre for Climate Research, Stockholm University, Stockholm, and Swedish Collegium for Advanced Study, Uppsala, Sweden (Manuscript received 20 May 2019, in final form 28 April 2020) ABSTRACT Accurate projections of moisture variability across the Tibetan Plateau (TP) are crucial for managing re- gional water resources, ecosystems, and agriculture in densely populated downstream regions. Our under- standing of how moisture conditions respond to increasing temperatures over the TP is still limited, due to the short length of instrumental data and the limited spatial coverage of high-resolution paleoclimate proxy records in this region. This study presents a new, early-summer (May–June) self-calibrating Palmer drought severity index (scPDSI) reconstruction for the southeastern TP (SETP) covering 1135–2010 CE using 14 tree- ring records based on 1669 individual width sample series. The new reconstruction reveals that the SETP experienced the longest period of pluvial conditions in 1154–75 CE, and the longest droughts during the periods 1262–80 and 1958–76 CE. The scPDSI reconstruction shows stable and significant in-phase rela- tionships with temperature at both high and low frequencies throughout the past 900 years. This supports the hypothesis that climatic warming may increase moisture by enhancing moisture recycling and convective precipitation over the SETP; it is also consistent with climate model projections of wetter conditions by the late twenty-first century in response to global warming. 1. Introduction influence on water resources, agriculture, and ecosys- tems not only on the TP itself but also in countries The Tibetan Plateau (TP), frequently referred to as downstream, thereby affecting the well-being of billions the ‘‘water tower of Asia’’ (Xu et al. 2008; Immerzeel of people (Gao et al. 2019). Accurate projections of et al. 2010), is the source region of many large rivers in future moisture changes under global warming are im- Asia, including the Yellow River, Yangtze River, Nu portant for the TP, but such predictions are largely de- Jiang River, Mekong River, and Indus River. Moisture pendent on a well-constrained temperature–moisture variability on the TP therefore has a considerable relationship in climate model simulations (Ljungqvist et al. 2016). However, state-of-the-art climate models Supplemental information related to this paper is available at show large uncertainties in the coupling between the Journals Online website: https://doi.org/10.1175/JCLI-D-19- changes in temperature and moisture, especially at re- 0363.s1. gional scales (Stephens et al. 2010; Christensen et al. 2013; Orlowsky and Seneviratne 2013; Nasrollahi et al. Corresponding author: Jianglin Wang, wangjianglin2011@lzb. 2015). Uncertainties in how moisture variability will ac.cn respond to global warming are particularly large for the DOI: 10.1175/JCLI-D-19-0363.1 Ó 2020 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses). Unauthenticated | Downloaded 09/27/21 06:10 PM UTC 6584 JOURNAL OF CLIMATE VOLUME 33 TP and adjacent regions of East Asia (Osborn reconstruction covering the past millennium (1000–2005 et al. 2015). CE; hereinafter all years are in the common era). The Instrumental observations show that the TP has majority of the tree-ring-based moisture reconstructions experienced a rapid warming during the past six de- have been developed from moisture-limited sites, around cades, with a higher rate of temperature increase than the lower tree-line areas (Fan et al. 2008; Fang et al. 2009; the global average (Pepin et al. 2015; You et al. 2017). Li et al. 2017; Shi et al. 2018), although some have also Although changes in precipitation over the TP, unlike been derived from the upper tree-line areas (Liu et al. the well-recognized warming, show large spatial and 2011; He et al. 2013; Yang et al. 2014). Zhang et al. (2015) seasonal variability, an overall wetting trend is observed found substantial differences between changes in the in instrumental data (Yao et al. 2012; W. Zhang et al. moisture-sensitive tree-ring chronologies of the southern 2017). The increased precipitation over the TP has been and northern ETP (with the regime division at ;338N), suggested to be related to intensified local moisture re- attributing this contrast to a south–north moisture dipole. cycling in response to increasing surface temperature These tree-ring records now serve as a basis for new op- during the past decades (Guo and Wang 2014; Curio portunities to conduct detailed and accurate regional et al. 2015). However, the response of precipitation to moisture reconstructions with which the history of the temperature as indicated by instrumental observations moisture changes can be described. need to be further validated over longer time scales In this study, we use 14 previously published moisture- beyond those of the brief period covered by instru- sensitive tree-ring width records to develop a new mental data. Recent studies suggest time scale- regional-scale early summer (May–June) self-calibrating dependent relationships between temperature and Palmer drought severity index (scPDSI) reconstruction moisture in Europe (Seftigen et al. 2017; Ljungqvist for the southeastern TP (SETP) covering the period et al. 2019b) and East Asia (Rehfeld and Laepple 2016), 1135–2010. We assess the temporal relationships between but these are too short to be fully resolved by instru- moisture and temperature at interannual to centennial mental observations. Moreover, temperature and pre- time scales. Using this new reconstruction in tandem sumably also precipitation (or moisture) have been with a model-simulated scPDSI dataset, we place the increasingly influenced by anthropogenic forcing (e.g., current (twentieth century) moisture variability and fu- greenhouse gas concentration and aerosols) during the ture (twenty-first century) projections within the context instrumental period (Myhre et al. 2013). Taken to- of the past millennium. gether, these issues stress the importance of using pa- leoclimate data to place the current and future climate regimes in a long-term perspective (Cook et al. 2004, 2. Data and methods 2010, 2015; Mann et al. 2009; Büntgen et al. 2011, 2016; a. Instrumental data Esper et al. 2018; Ljungqvist et al. 2012, 2016, 2019a,b; Luterbacher et al. 2016; Wilson et al. 2016; PAGES The gridded Climatic Research Unit (CRU) TS 4.01 Hydro2k Consortium 2017). 0.5830.58 monthly temperature and precipitation Considerable progress has recently been made in de- dataset (Harris et al. 2014) were used to investigate the veloping high-quality tree-ring records covering the relationship between climate and tree growth. We only centuries and millennia over the eastern Tibetan Plateau used CRU data after 1950, because very few meteoro- (ETP) (e.g., Zhang et al. 2003; Bräuning and Mantwill logical stations in this region are available prior to this 2004; Sheppard et al. 2004; Liu et al. 2006; Liang et al. time (Liu and Chen 2000). The regional (i.e., SETP 2008; Zhu et al. 2008; Fang et al. 2009; Fan et al. 2010; scale; 278–338N, 908–1028E) average of monthly CRU Shao et al. 2010; Grießinger et al. 2011; Yang et al. 2014, data was calculated and used to examine the correla- 2019; Gou et al. 2015; Deng et al. 2016; Yin et al. 2016; Li tions between tree-ring records and regional climate et al. 2017; Wernicke et al. 2017). The ETP, with the variables. highest alpine tree line in the world (mostly exceeding The Palmer drought severity index (PDSI), as a 4000 m above mean sea level), is well suited for devel- standardized index, is widely used as an indicator of soil oping temperature-sensitive tree-ring chronologies from moisture variability (Palmer 1965; Dai 2011, 2013). The the upper tree-line area (Liang et al. 2008; Deng et al. zero values of PDSI represent the baseline for average 2014; Duan and Zhang 2014; Wang et al. 2014; Shi et al. conditions and positive (negative) values indicate wet 2016; Li and Li 2017). Wang et al. (2015) found strong (dry) departures from the baseline climatology. The covariance between these temperature-sensitive site self-calibrating PDSI (scPDSI; Wells et al. 2004), a re- chronologies from the ETP, enabling the development vised version of the PDSI, applies a more physically of a regional summer (June–August) temperature realistic Penman–Monteith parameterization for potential Unauthenticated | Downloaded 09/27/21 06:10 PM UTC 1AUGUST 2020 W A N G E T A L . 6585 TABLE 1. Metadata for the 14 moisture-limited tree-ring chronologies over the SETP. Abbreviations are as follows: mean sample length (MSL); ‘‘not a number’’ (i.e., information missing in the original literature) (NaN); expressed population signal (EPS); signal free (SF); linear regression function (LRF), cubic spline function (CSF), and negative exponential function (NEF) are detrending techniques ap- plied to calculate site chronologies by the original authors; r shows the correlation between site tree-ring chronologies and May–June scPDSI over the period 1950–2001; median b refers to the contribution of site chronologies to the reconstruction for the best replicated nest during 1702–2001. No. Site Lat Lon Alt of Detrending MSL Period (EPS r with Median No. Site name (8N) (8E) (m) Species cores method (yr) .