Challenges to proxy data integration

Integration of paleohydrologic data across sites

Most traditional hydrologic climate-proxy indicators tend to reflect "effective moisture availability", rather than rainfall, with poorly constrained temperature effects on evaporation. Rainfall variation is also spatially more heterogeneous and temporally more pronounced than temperature variation, because the atmospheric circulation patterns ultimately determining rainfall location and intensity depend on ocean currents, pressure contrasts between oceans and adjacent land masses, and local land topography. To draw a coherent picture of latitudinal linkages and the associated climate dynamics for rainfall variability during past millennia thus requires appropriate geographic coverage of well-dated, high-quality hydrologic proxy records. This in turn presents two other challenges: (i) what is the proper spatial scale to integrate paleodata, when the main aim of such integration is to capture and highlight characteristic regional climate patterns for comparison with those of other regions?; (ii) how to compare climate-proxy time series between two or more regions where the selected proxy indicators are influenced to a different degree by temperature and precipitation variations?

High-quality paleodata are often generated from natural climate archives that are common in certain regions but have limited distribution or poor archival quality in other regions. Consequently, meeting the second challenge (if not also the first, cf. Moberg et al. 2005) requires integration of climate-proxy time series across archives that have a different resolution and chronologic control. As with multiproxy studies on a single archive, comparison of proxy records between archives from within the same region can provide unique insight into the seasonal characteristics of past climate change and into how well we understand individual proxies as indicators of climate change. It also provides an independent test of the quality of natural climate archives as recorders of climate change in a manner that any number of proxy indicators from the same archive can not.

Figure 8.1 Western Eurasia and Africa with main study sites and regions discussed in the text: lakes in the Jura, French pre-Alps and Swiss Plateau (1: Magny 2004); Uamh an Tartair Cave, Scotland (2: Proctor etal. 2002); northern Britain peatlands (3: Charman et al. 2006); Great Aletsch Glacier, Switzerland (4: Holzhauser et al. 2005); Bj0rnbreen Glacier, Norway (5: Matthews et al. 2005); fluvial chronology of Spain (6: Thorndycraft and Benito 2006); oak tree-rings, western France (7: Masson-Delmotte et al. 2005); Dongge Cave, China (8: Wang et al. 2005); Qunf Cave, Oman (9: Fleitmann et al. 2003); marine sediments, western Arabian Sea (10: Gupta et al. 2003); Lakes Abhe and Ziway-Shala, Ethiopia (11 and 12: references in Gasse 2000); marine sediments, eastern tropical Atlantic Ocean

(13: de Menocal et al. 2000); Lake Edward, DR Congo/Uganda (14: Russell and Johnson 2005b); agricultural drought index, coastal Angola (15: Miller 1982); Pilkington Bay, Lake Victoria (16: Stager et al. 2005); Lake Naivasha, Kenya (17: Verschuren et al. 2000). Continental-scale syntheses of Holocene and/or historical paleohydrology are available for Europe (A: Yu and Harrison 1995; B: Pauling et al. 2006), the arid-sub-arid belt of North Africa and the Arabian Peninsula (C: Hoelzmann et al. 2004), north and intertropical Africa (D: Street and Grove 1976), the entire African continent (E: Gasse 2000), sub-Saharan Africa (F: Verschuren 2004) and the Indian and East Asian monsoon domains (G: Fleitmann et al. 2007a).

Calibration of paleohydrologicproxy indicators in space and time

Any exercise in paleodata integration across sites and archives necessarily assumes that the relative magnitude of reconstructed proxy climate signals has been calibrated locally. This is accomplished either by time series regression against instrumental climate data (e.g. precipitation) or derived measures of hydrologic change (e.g. effective moisture, Palmer drought index) or through a spatial transfer function relating variation in the proxy indicator to modern geographic variation in the climate variable. Time-series calibration (as is customary in dendroclimatology) is generally considered superior to the spatial approach (customary in palynology or paleoecology of aquatic biota). This is not necessarily the case, however, when instrumental weather data from the immediate vicinity of the proxy record are lacking, or of insufficient length to capture local climate variability at the time-scale of interest and to confirm the stationarity (constancy through time) of indicator response to this variability (Jones et al. 1998). Lack of suitably long precipitation records can sometimes be overcome by a regional climate field reconstruction, i.e. a multi-variate statistical calibration of proxy data against spatial networks of instrumental data (e.g. Zhang et al. 2004). Climate field reconstruction must evidently start from the assumption that relationships between a proxy indicator and synoptic climate patterns have been stationary through time (Jones and Mann 2004). Time-series calibration of nonannually resolved climate-proxy records (e.g. Laird et al. 1996) often optimize the correlation by shifting or tuning the time axis of the record, thus making it difficult to identify possible lags in system response to climate change. This tuning can either be avoided or justified through system modeling of the relationship between a particular proxy indicator, the archive concerned, and climate. Although time-series calibration on nonan-nual proxies is imperfect, such methodologic compromises made for the purpose of climate-proxy calibration are evidently preferable to having no direct test of the exact meaning of climate-proxy signals at that particular site. Unfortunately, in many available high-resolution records of hydrologic change, proxy signals have not been directly calibrated, and the stationarity of signal response is unknown. Reconstruction must be based instead on a plausible mechanistic scenario of system response to climate at the time-scale of interest, inspired sometimes by modern relationships at seasonal time-scales that do not necessarily apply over decadal and centennial scales.

Chronologic issues

A further obstacle to integration of paleohydrologic data and to resolving their association with climate-forcing functions is the limited age control on reconstructed climate anomalies in nonannually resolved records dated with radioisotopes (e.g. 14C, 210Pb, U/Th). Although this issue is not confined to paleohydrologic records, it is of particular importance here because large-scale hydrologic change is thought to have occurred rapidly during certain periods. It also hampers attempts to link presumed low-frequency change (e.g. regional water-table fluctuation) to high-frequency change (e.g. flooding) recorded in different archives. Evidently, more effort should be directed to optimize age control on any record containing significant climate anomalies. Particularly for recent millennia, chronologic precision can sometimes gain significant improvement through wiggle-matching of multiple closely spaced radiocarbon ages to the dendrochronologic radiocarbon calibration curve (Blaauw et al. 2003), an approach used with success for hydro-logic reconstructions extracted from European peat deposits (e.g. Mauquoy et al. 2004). When age control is inadequate, researchers are tempted to draw separate climate events at different sites into one illusory regional-scale event (Baillie 1991, Oldfield 2001). Explicit statistical analysis of the age uncertainties in proxy records can stimulate progress towards more rigorous integration of paleoclimate data (Blaauw et al. 2006).

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