Climatic ChangeDOI 10.1007/s10584-010-9966-7

Reconstruction of annual winter rainfall since A.D.1579in central-eastern Spain based on calcite laminatedsediment from Lake La Cruz

Lidia Romero-Viana · Ramon Julià · Martin Schimmel ·Antonio Camacho · Eduardo Vicente · M. Rosa Miracle

Received: 23 July 2009 / Accepted: 5 October 2010© Springer Science+Business Media B.V. 2010

Abstract We present the first winter (December to March) rainfall reconstructionbased in a novel proxy, the thickness of annual calcite laminations preserved in LakeLa Cruz (central–eastern Spain). A previous calibration analysis between laminaethickness and the instrumental data series (1950 to present) indicated a highlysignificant correlation with winter rainfall. Therefore this study attempts the winterrainfall reconstruction since the onset of laminations (1579 a.d.) by means of thecalibration function previously developed. The verification analysis between inferredannual values and earlier instrumental data (1859–1949) confirms the suitability ofthis novel proxy and the reliability of the series reconstructed. The reconstructedseries show the fluctuating character of winter rainfall in the western Mediterraneanarea; interdecadal dry periods alternated with wetter periods following, in a boardsense, the pattern recorded by documentary sources in other regions of the IberianPeninsula. At present times regional winter rainfall anomalies are highly correlatedwith the phase of the North Atlantic Oscillation (NAO). However the time seriesanalysis showed the dominance of nonstationary components at high frequencies ofthe climate signal over the last four centuries suggesting that the connection between

L. Romero-Viana · A. Camacho · E. Vicente · M. R. MiracleDepartment of Microbiology and Ecology and Cavanilles Institute of Biodiversityand Evolutionary Biology, University of Valencia, 46100 Burjassot,Valencia, Spain

R. Julià · M. SchimmelInstitute of Earth Sciences “Jaume Almera”. CSIC, C/Lluis Solé i Sabarís,s/n 08028, Barcelona, Spain

Present Address:L. Romero-Viana (B)Institut für Erd- und Umweltwissenschaften, Universität Potsdam,Karl-Liebknecht-Strasse 24, Haus 27 14476,Potsdam, Germanye-mail: Lidia.Romero@geo.uni-potsdam.de

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winter rainfall and the NAO has not been stable over time and also other modes ofvariability, not only NAO, may have conditioned winter rainfall variability.

1 Introduction

A step towards a better understanding of anthropogenic impacts on climate systemwithin the global change debate is the assessment of the characteristics of naturalvariability at high-temporal and spatial resolution to evaluate the general circulationmodels under development. At this point regional and large-scale reconstructionsof changes in precipitation become essential because they complement the surfacetemperature series and improve our understanding of the forcing factors that havecontributed to the climate variability. During the last decades huge efforts havebeen carried on the systematic collection of long-term observations to characteriseprecipitation in the Iberian Peninsula (Martin-Vide and Barriendos 1995; Creus-Novau et al. 1997; Rodrigo et al. 1999; Garcia-Herrera et al. 2003). These timeseries of precipitation are mainly based on tree-ring chronologies and documentarysources. Unfortunately (1) the correlation between tree-ring data series and winterprecipitation is weaker than between these series and the temperature variables and(2) the documentary data tend to bias series to extreme events of droughts andfloods. Nowadays, there is still a relative low number of rainfall proxy informationavailable (Pauling et al. 2005) to constrain climate reconstructions.

Unexplored natural archives could potentially contribute to characterise thenatural climatic variability. Among them, annually laminated lake sediments can bepowerful tools to reconstruct different climate variables; since laminated sedimentsare capable of preserving information at higher resolution, as close as annual andeven subannual and they might record the variability of different climatic factors in-volved directly or indirectly in their formation (Leemann and Niessen 1994; Itkonenand Salonen 1994; Zolitschka 1996; Lamoureux and Gilbert 2004). There are severaltypes of laminations (e.g. detrital, biogenic, evaporitic) in a wide temporal andspatial range and, despite differences all of them are formed by seasonal changes insediment deposition (Brauer 2004). Particularly in carbonate bedrock basins, calcitelaminations are common due to the seasonal autogenic precipitation of calciumcarbonate within the water column (“whiting”) and sedimentation of calcite crystals(Kelts and Hsü 1978). Some approaches have assessed the analysis of climatic signalrecorded in calcite laminated sediments using wavelength analysis on laminationsthickness as exploratory technique (Livingston and Hajdas 2001; Dean et al. 2002;Muñoz et al. 2002; Brauer et al. 2008).

Lake La Cruz (central–eastern Spain) shows an excellent preserved laminatedsediment which is formed by couplets of alternated white and brownish laminations(Julià et al. 1998). The light laminae are composed by calcium carbonate crystalsdeposited after summer whiting and the dark laminae consist mainly of organic-richsilts with a minor part of fine mineral clasts (Rodrigo et al. 1993). In order to explorethe potential use of laminations as quantitative climate indicator, a calibration analy-ses was performed between calcite laminations thickness and rainfall/temperaturevariables during the regional instrumental record, 1950 onwards (Romero-Vianaet al. 2008). The results have shown that accumulated winter rainfall, from De-cember to March, is the best predictor of annual calcite laminations thickness.

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The monitoring study carried out in Lake La Cruz during three consecutiveyears (1996–1998) and the water column data available supported this relation-ship (Miracle et al. 2000; Romero et al. 2006). Although high water temperatureand photosynthetic activity (Camacho et al. 2003) can be trigger factors of themassive calcite precipitation during summer, the total amount of crystals precip-itated in the lake during summer whiting depends on annual dissolved calciumrenewal, which in turn is dependent on the aquifer discharge after winter rainfall(Miracle et al. 2000; Romero-Viana et al. 2008). This study attempts the winterrainfall reconstruction over the last four centuries using calcite laminae thicknessas rainfall proxy based in the previous work developed by Romero-Viana et al.(2008). The results of our study highlight the potential of calcite varved sedimentrecords in paleoclimatic research. Our results further support the use of calcitelaminae thickness as a consistent quantitative proxy of past hydro-climatic variabilitycontributing to the characterisation of winter rainfall variability over the westernarea of the Mediterranean basin.

2 Methods

2.1 Location

Lake La Cruz is a karstic lake located in the Iberian Range (central–eastern Spain,UTM 30SWK95983 27029, Fig. 1) at 1,000 m above sea level. The study area ischaracterised by a continental Mediterranean climate-type with a typical seasonalrhythm of very dry hot summers and cool, rainier winters. A detailed climaticdescription of the site area including seasonal instrumental data series 1950–2003from the nearby town of Cuenca is provided by Romero-Viana et al. (2008). In

Fig. 1 Iberian Peninsula map with the cities locations cited in the text. The white dot indicates thelocation of Lake La Cruz

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summary and for this time period (1950–2003), mean annual rainfall is 525 ± 123 mm.Regional winter precipitation, which contributes at 50% of the total amount, is highlycorrelated with the phase of the North Atlantic Oscillation (NAO) (Romero-Vianaet al. 2008). The annual mean evapotranspiration in the lake area is approximately130 mm/month, with monthly maxima over 200 mm in summer and monthly minimabelow 50 mm in winter. Mean monthly temperatures range from 5–6◦C in thecoldest month (January) to 25◦C in the warmest month (July). Monthly temperaturevariations can be quite extreme and differences between day and night are also veryimportant, especially in summer, indicating the continental character of its climate.

2.2 Sediment cores

Three sediment cores were used to construct the varve chronology (Fig. 2). All ofthem were obtained from the central deepest point of Lake La Cruz at differentdates. The first sediment core (CV-94) was extracted in 1994 with a Wright (1980)corer and the other two (CV-98 and CV-03) using a gravity corer in December1998 and May 2003, respectively. The laminated section of Lake La Cruz extendsapproximately to the uppermost 40 cm. Among the three sedimentary sequencesavailable, only CV-03 recorded the total extension of the laminated section. Due tothe extremely wet nature of recent sediment, the uppermost laminated centimetresof CV-94 were damaged during the transportation (Julià et al. 1998) and CV-98 wastoo short (only 30 cm) to recover the oldest varves.

In the laboratory, the core barrels were cut lengthwise and the sediment was splitin half. Overlapping sediment slabs were sampled using aluminium trays (1 × 2 ×18 cm). Thin sections (30 μm in thickness) of sediment were obtained after freeze-drying followed by saturation with Spurr’s epoxy resin that hardened sedimentslabs (Lamoureux 2001). The thin sections of CV-98 and CV-03 were scanned at1600 dpi resolution and the high resolution images obtained were analysed withthe UTHSCSA Image tool program developed at the University of Texas HealthScience Centre at San Antonio, Texas, and available from the Internet by anonymousFTP ftp://maxrad6.uthscsa.edu. The laminae number and thickness were determinedbetween visually discernible marked horizons. Measurements of lamina thicknesswere resolvable to 15 μm and documented using the measuring tools in the software.We report the mean thickness of three separate measurements within each laminae.The CV-94 core was processed in the laboratory in a similar way after it wasrecovered. The light and brownish laminae of CV-94 thin sections were counted andthe thickness of each lamina was measured in several parts under a petrographicmicroscope with an ocular micrometer.

The annual laminations are interrupted at some depths by events of high detritalinput. These layers occur with no obvious primary textural organization of detritalmaterial and commonly small plant fragments and charcoal particles are present.Both, its occurrence and thickness (the later has not been included in Fig. 2) showsan inter-sequence variability. The three sequences were cross-matched following assedimentological criteria the occurrence of detrital layers and the number of varvesbetween detrital events (Fig. 2). During the cross-matching we noted the absenceof varves, usually less than two annual laminations, and just before some detritallayers. The occurrence of lost varves before the detrital inputs suggests a possibleerosive effect of these on delicate laminations. However the availability of more

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Fig. 2 Schema representingthe three sediment cores(CV03, CV-94 and CV-98) andthe cross-matching of the threestudied laminated sequences.The scale corresponds to thevarve-year unit. The blacklines indicate the presence ofdetrital layers interrupting theannually laminated sequence.The number of annuallaminations is indicated ineach laminations package. Thegray areas indicate lostlaminations. In the right sidethe results of the statisticalcross-correlation analysisbetween series are provided(see text for a detaileddescription of the method)

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than only one sedimentary sequence to build a master series enables the confidenceassessment of a Lake La Cruz annual laminations chronology. After cross-matchingthe sequences, a total of 423 annual laminations have been identified; confirmingthe onset of laminated sediments at 1579 a.d. Annual laminations provide betterchronological data than radioisotopic methods, however lamination chronology hasbeen tested by an independent dating method. The chronological model based on210Pb activity (Romero-Viana et al. 2010) matches with the varve dating.

3 Climate signal processing and statistical analysis

3.1 Construction of master series

Once we confirmed by a correlation analysis the suitability of the cross-matchingperformed between the three available series (Fig. 2), we proceeded to averagethese three series. The method used to express the similarity between series was theproduct moment correlation coefficient, defined as,

r =(∑

xy − NXY)/(√ ((∑

x2)

− (NX2)) ((∑

y2)

− (NY2)))

where X and Y are the means of all x and y values respectively (Baillie and Pilcher1973; Maddy and Brew 1995). A Student’s t-test was then performed to provide ameasurement of the probability of the calculated value of r having arisen by chance.The value of the Student’s t-test is given by

t = (r√

(N − 2)) / (√ (

1 − r2)

where N is the number of samples, which here means the number of overlappingcalcite laminae. Before r was calculated, the data were transformed so that the setsof values (x and y) became bivariate-normal, thus each calcite lamina was convertedto a percentage respect to the mean of the five calcite laminae of which it was thecentral value and ln of these percentages were then calculated. The results of thisanalysis are included in Fig. 2.

Then, each raw calcite laminae thickness series was normalized by the averageseries value and the 50-years moving standard deviation, resulting in three dimen-sionless annual index series. The three index series were averaged year by year toproduce a master series (Fig. 3) increasing the climate signal and partially cancellingthe non-climatic noise. In Fig. 3, the dots without standard deviation indicate onlyone annual calcite lamina thickness measurement available.

Annual winter (DJFM) rainfall values were inferred using the calibration functiondescribed in Romero-Viana et al. (2008) after adding new data corresponding to theseries CV-98 (1950–1988);

yt = 55xt + 156,

where y is the estimated rainfall value (mm) and x the corresponding calcite indexvalue (t = year in both cases). The uncertainty ranges were calculated according toBriffa et al. (2002). The calibration error ranges are based upon the uncertainty inthe regression coefficients (the intercept, a, and the gradient, b) and the residual

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Fig. 3 Calcite index master series (dimensionless). The black dots represent the average calciteindex values and the grey bar the standard deviation. The dots without standard deviation indicateonly one annual calcite lamina thickness measurement available. The solid black line and the dottedblack lines indicate the mean and the standard deviation, respectively, for the data series

variance (Sxy). In this case, the standard error of the regression coefficients were,SEa = 17 and SEb = 19, and the residual rainfall variance Sxy = 75.

3.2 Verification process

The skill of rainfall reconstruction was verified by comparing the reconstructedvalues for the period 1859 to 1949 with the available instrumental data series fromCuenca and Madrid (Fig. 1). The instrumental dataset for Cuenca station covers from1909 to nowadays. Unfortunately gaps in the instrumental dataset appear especiallyfor the first half of the twentieth century, more frequently during 1915–1917, 1919–1921, 1925–1926, and 1936–1941, the latter caused by the Spanish Civil War. A highstatistical correlation was found between the instrumental rainfall series of Cuencaand Madrid (r2 = 0.7; p < 0.001; n = 76). The instrumental climatic data fromMadrid, (1859 onwards), were used to infer Cuenca winter (DJFM) rainfall from1859 to 1909 and to fill the remaining gaps in the Cuenca’s dataset by means of alineal function. The skill of reconstruction has been estimated using the reductionerror (RE) measure and the coefficient of efficiency (CE) (Cook et al. 1994). Theyare defined as,

RE = 1 −[(∑(

yi − yi)2

)/(∑(yi − yc

)2)]

,

CE = 1 −[(∑(

yi − yi)2

)/ (∑ (yi − yv

)2)]

,

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where yi and yi are the observed and the reconstructed values, respectively, overthe verification period and where yc is the mean of the actual data during thecalibration period and the yv is the mean of the observed values over the verificationtime period. RE and the CE values ranges from +1.0 to −∞. Although there isno way of testing RE and CE for statistical significance, positive values indicateuseful information in the climatic reconstruction. Moreover the product-momentcorrelation coefficient between estimated and instrumental data series has beencalculated and the significance of the calculated coefficient was tested using a t-test. See Cook et al. (1994) for a detailed description of verification test of climaticreconstructions.

Furthermore we have included for comparisons two rainfall reconstruction se-ries from other regions in the Iberian Peninsula obtained from different sources; themean winter plus spring rainfall index in Andalucía (mainly based on documentarysources from Sevilla, Málaga and Granada cities, southern Spain, Fig. 1) and thedrought events during winter and spring in Toledo (central Spain, Fig. 1). Andalucíaseasonal rainfall index (limits scale −2 to 2, from dry to wet) is available at http://www.ucm.es/info/reclido/es/basesdatos/Rainfallindex.txt and more information rela-tive to the data sources and processing could be obtained in Rodrigo et al. (1999,2000). On the other hand, Barriendos and Domínguez-Castro personally providedToledo’s data series (Domínguez-Castro et al. 2008). Comparisons with three differ-ent NAO index reconstructions have been also included (Glueck and Stockton 2001;Cook et al. 2002; Luterbacher et al. 2002). The NAO index series are available atthe NOAA web site (ftp://ftp.ncdc.noaa.gov/pub/data/paleo/treering/reconstructions/glueck2001_nao.txt; ftp://ftp.ncdc.noaa.gov/pub/data/paleo/treering/reconstructions/nao_cook2002.txt and ftp://ftp.ncdc.noaa.gov/pub/data/paleo/historical/north_atlantic/nao_sea.txt)

3.3 Time-series analysis

Climatic time series have generally non-stationary properties since the statisticalproperties of the underlying processes are changing with time. As a consequence thefrequency contents of the time-series are expected to change with time. A normalFourier spectrum does not reflect this time-dependence and we therefore analysealso the time–frequency spectra of our time series. There exist many approachesto study the time–frequency evolution of signals. The short time Fourier transform(STFT) based on Gabor (1946) and the continuous wavelet transform (CWT) (e.g.Daubechies 1990) are among the most common methods. The STFT determines thelocal spectra by applying the Fourier transform on overlapping data segments ofconstant width while the CWT permits a frequency-dependent time resolution byusing a scaled replica of a mother wavelet for data segmentation. The STFT hasa poor time-resolution at high frequencies and a poor frequency resolution at lowfrequencies due to its constant width windows which are too large or too small withrespect to the analysed periods. The variable time–frequency resolution of the CWTis therefore an advantage over the STFT.

We used the S transform (Stockwell et al. 1996) which can be considered as anextension of the STFT with frequency-dependent resolution. Moving windows arescaled inversely by frequency similar to a mother wavelet in the CWT. This allowsthe detection of high frequency bursts and permits a good frequency resolution at

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the lower frequencies. The S-transform takes over most of the well-known Fourierproperties and is therefore an easy understandable tool which permits to move freelybetween the time, frequency and time–frequency domain. This invites for furtherdata adaptive processing (e.g. Schimmel and Gallart 2007 for further details andreferences). The relation between the S transform and the CWT is presented inVentosa et al. (2008). In our analysis, we use Gaussian-shaped windows since theyare the most compact in time and frequency. The width of the Gaussian window (e.g.,measures using the full duration at half maximum or in analogy to probability densityfunctions by the standard derivation) is chosen as a constant factor of each period tobe analysed. This factor permits to control the time–frequency resolution. We use afactor one which means that the standard deviation equals each considered period.A larger factor would decrease the time resolution and improve the frequencyresolution.

4 Results and discussion

4.1 Winter rainfall reconstruction

Given the relationship between calcite laminae thickness and regional winter rainfall(from December to March, DJFM), the calibration linear function developed wasapplied to infer annual rainfall values until the onset of annual laminations in LakeLa Cruz sediment (Fig. 4). Outstanding features of the reconstruction show: (1) theannual and decadal rainfall variability and that (2) the difference observed betweenthe mean winter rainfall over the reconstruction period and the calibration period

Fig. 4 Inferred winter (DJFM) rainfall values (mm) (gray line), and 5-years smoothed series (blackline). The grey areas correspond to the uncertainty range. The solid black line and the dotted blacklines indicate the mean value and the standard deviation, respectively, for the overall winter rainfallreconstruction

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(154 and 204 mm, respectively). Likewise the standard deviation value (55 mm)was significantly lower for the inferred values than the value corresponding tothe calibration period (92 mm) which is a common effect to almost all regressiontechniques.

The rainfall series show the alternation of difference length time periods ofnegative and positive anomalies in the region over the last four centuries (Fig. 4).The last years of the sixteenth century and the first quarter of the seventeenth theinferred values were mainly under the mean value, the minima occurring around 1580and 1625, whereas the maxima were observed around 1590 and 1615. However theserainfall values between 1578–1614 were inferred based on only one calcite thicknessseries (CV03, Fig. 2), then conclusions should be taken with caution. One of themost intense negative anomalies was observed between 1630 and 1640 but then apositive trend started in 1660 reaching the highest positive values in the series at1685. The eighteenth century was also relatively wet but low values were observedaround 1720, 1740 and 1760. The end of the eighteenth century was relatively wetbut at the beginning of the nineteenth century a persistent negative anomaly wasobserved from 1800 to 1820, occurring during a minimum solar activity period knownas Dalton Minimum (1790–1820). By contrast around the half and at the end of thenineteenth century the inferred rainfall values showed high positive values (1840–1850 and 1890). Finally the beginning of the twentieth century was relatively drierrespect to the 1940–1950 decades and the second half of the twentieth century whenthe mean value, as commented before, was around 204 mm. Rodrigo and Barriendos(2008) concluded that dry anomalies in the Iberian Peninsula based on documentarysources were more intense in the past whereas wet anomalies were more intense inthe twentieth century. They speculated that these results might be biased due to thenature of documentary data, more focused on the appearance of droughts that affectagriculture, or alternatively they may reflect the increasing trends of heavy rainfallsdetected in the twentieth century (Groisman et al. 1999).

The interannual variability was significantly higher over the second half of theseventeenth century (1645–1665 and around 1690), during the eighteenth century(1710–1735 and 1750–1800), and significantly decreased through the first half ofthe nineteenth century, though increasing for short periods around 1855, 1870 and1880–1900. The second half of the eighteenth century stands out showing highinterannual variability with extreme values. Noteworthy this period 1760–1800 (theMalda anomaly), was characterised by major climatic fluctuations, with a rapidsuccession of droughts and floods (Barriendos and Llasat 2003). Meanwhile, thetotal annual precipitation during this period was not so different from what could beconsidered average values. This anomaly affected also other Mediterranean regionssuch as Italy (Camuffo et al. 2000) and the Balkans (Xoplaki et al. 2001).

The verification process has been achieved using the instrumental data registeredin Cuenca and Madrid since a.d. 1909 and 1859, respectively (Fig. 5). The winterrainfall values corresponding to 1877–1879 and 1943–1949 have been excluded fromthe verification analysis because they were inferred based in only one calcite laminathickness annual data (empty dots in Fig. 3). The three different verification testsapplied, the product-moment correlation coefficient, Coefficient of Efficiency (CE)and the Reduction Error (RE), have confirmed the skill of the reconstruction (r =0.28 n = 81 p < 0.01; and RE = 0.2). In spite of the similarity between both RE and

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Fig. 5 Verification analysis. Instrumental (gray thin line) and reconstructed (black line) winterrainfall values (mm). The empty dots indicate annual values inferred based only in one data seriesand excluded from the verification analysis. The thicker gray line represents the smoothed annualinstrumental data by the previous year

CE, the difference in the results is related with the difference between the calibrationand verification winter rainfall mean values which have changed significantly. Duringthe calibration time period (1950–1988) the mean winter rainfall was 204 mm,whereas this value drops to 177 mm during the verification period (1859–1949).Noteworthy the calculations of RE and CE using the smoothed instrumental dataaveraged by the previous year, instead of the annual value (Fig. 5) show higherpositive values (CE = 0.6 and RE = 0.6). Moreover these results have confirmedthe buffer effect of the karstic system suggested in the previous calibration study(Romero-Viana et al. 2008). The extreme precipitation events may have lowerincidence in aquifer because of its lost by runoff, thus does not influence waterdischarge to the lake when the aquifer retention capacity is overpassed. Moreoverduring the extremely dry periods the lake has a background calcium concentrationwhich still allows calcite crystals formation and subsequent summer whiting. Thisresult does not preclude the value of the interannual variability inference but limitsthe climate signal of the highest values.

Additionally our winter rainfall reconstruction has been compared in Fig. 6 withtwo other rainfall series reconstructions from other sites of the Iberian Peninsulabased on documentary sources (Rodrigo et al. 1999, 2000; Domínguez-Castro et al.2008). Unfortunately comparisons with another natural proxy such as dendroclimaticreconstructions were not possible for the moment. Although there are many tree-chronologies around the Iberian Peninsula, in general correlations with the precip-itation variables are weaker than with the temperature variables (Manrique andFernandez-Cancio 2000). In particular the calibration studies suggest a tree-ringresponse to spring-summer precipitation and temperature but there is not a clear

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Fig. 6 Comparison between regional winter rainfall reconstruction (5-years smoothed series; blackline) and Andalucía winter–spring rainfall index (from -2 (dry) to 2 (wet); dark gray bars) and Toledonumber of drought events during winter and spring (light gray bars), in both cases 5-years smoothedseries

response to winter precipitation in the area of the Iberian Ranges (Fernandez-Cancioet al. 1993), where the lake is located.

The two rainfall series selected for comparison correspond to central south-western Iberian Peninsula locations. Both Spanish locations are in present timesunder the strong influence of NAO which mainly controls the winter rainfall variabil-ity as in our study site (Rodriguez-Puebla et al. 1998). Taking into account that theToledo series only represent drought events (Fig. 6), the three rainfall series showoverlapping periods with similar variability pattern such as, 1580–1600, 1630–1680,1770–1800 and 1890–1940. This simple and preliminary comparison shows that theCuenca rainfall reconstruction is consistent in a board sense with these two otherseries based on documentary sources. However some unconformities stand out: (1)periods with an opposite pattern as, 1610–1620, 1685–1690, 1800–1820 and 1860–1880and (2) a significant non-synchrony between the three series during the periods 1690–1720 and 1745–1760.

Recently different analysis about the spatial variability of twentieth centurydrought events have suggested that the Iberian Peninsula could be divided indifferent domains or climatologically settings related to drought (Santos et al. 2000;Olcina 2001; Domínguez-Castro et al. 2008), Although Cuenca is under the inlanddomain as Toledo and Andalucía, its more eastern location relative to the othersimplies a stronger influence from the coastal Mediterranean region and even fromthe North-east region (Vicente-Serrano 2006) explaining some of the divergencesbetween these series. In this regard the extreme dry period 1630–1640 observed inCuenca has been also detected in pro-pluvia rogation series from Zaragoza (north-east Spain, Fig. 1) (Vicente-Serrano and Cuadrat 2007). Additionally the inferredrainfall values in Cuenca suggested a severe drought period during the two firstdecades (1800–1820 coincident with the Dalton Minimum) which is not clear inToledo and Andalucía series, but is however recorded in more eastern localities.The evidences based on documentary sources through the Iberian Peninsula suggestthat this is a complex period. While Murcia (south-east Spain, Fig. 1) spring rainfallseries indicate dry conditions from 1775–1825 (Rodrigo and Barriendos 2008), inBarcelona (north-east Spain, Fig. 1) rainfall series suggest a short delay of the drierperiod there occurring from 1812 to 1825, and in Zaragoza (Fig. 1) the dry conditionswere suggested to occur around 1825 (Vicente-Serrano and Cuadrat 2007).

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Therefore this comparison and references to other rainfall index series is a prelim-inary analysis which denotes the complexity of further analysis due to the spatial non-homogeneities within Iberian Peninsula. Moreover the present inconsistency in theavailable data series from different proxy sources do not preclude a further analysiseven more encourage the efforts to combine them for a robust signal extraction andincrease the spatial and temporal resolution of climate signal against noise in a highlyclimate sensitive area.

5 Analysis of the climate signal

We have performed an amplitude S-spectra analysis to evaluate the periodicitiespresent in the reconstructed winter rainfall time series. While the Fig. 7a shows theFourier amplitude spectra of the index data series (Fig. 3) with an enlarged scaleat the high frequencies (inlet Fig. 7a), in Fig. 7b and c the amplitude S-spectra ofthe data have been plotted. The spectral analysis indicated high frequency peaksaround 0.12, 0.2 and 0.25/year whereas in the lower-frequency band significant peaksoccurred around 0.05, 0.02 and 0.01/year. The amplitudes are normalized to one(maximum amplitudes are visible in blue colours) for the data at low and highfrequencies in separate figures for visual purposes. The good time resolution for highfrequency components is due to the usage of shorter data windows at the higherfrequencies.

At the interannual up to decadal time scale, regional winter rainfall seems to begoverned by non-stationary components, according to previous studies which havereported non-stationarities in the European/North Atlantic climate system (Paulinget al. 2005; Touchan et al. 2005; Casty et al. 2005) and also in Mediterranean climate(Luterbacher et al. 2002). Nevertheless the signal of 0.12 and 0.25/year periodicitiesobserved in this regional rainfall reconstruction (Fig. 7a) which are similar to thoseobserved for NAO index series (Hurrell 1995), confirmed the strong correlationwith this large-scale pattern although these have not been stable over time (Fig. 7c).The North Atlantic Oscillation pattern has been confirmed as the most importantatmospheric phenomenon in the Atlantic area associated with the Iberian winterrainfall (Zorita et al. 1992; Rodo et al. 1997; Rodriguez-Puebla et al. 1998; Esteban-Parra et al. 1998).

Figure 8 shows the running correlation between the smoothed series (11-years moving average) of three different NAO index reconstructions (Glueck andStockton 2001; Cook et al. 2002; Luterbacher et al. 2002) and the regional inferredprecipitation series. The divergences between NAO index reconstructions have beenalready subject of different analysis (Schumtz et al. 2000; Timm et al. 2004). Inthis case we want to point out the decoupling signal between Luterbacher et al.(2002, 2004) reconstruction and the Cuenca regional time series during two longperiods such as 1610–1680 and 1800–1850. Noteworthy these time periods correlatewith observed time periods when the significance of these high frequency peaks isalso reduced (Fig. 7c). Obviously, further and more extend analysis are necessary.According with previous studies, these results indicate that probably other thanNAO atmospheric patterns have conditioned the rainfall variability in the IberianPeninsula. In this regard, Pauling et al. (2005) found highly significant correlationbetween the well-known dipole pattern which resembles the NAO and the recon-struction of winter precipitation variability in southern Spain and Morocco during

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Fig. 7 a Fourier amplitudespectra (solid black line) of thecalcite lamina index series(Fig. 3). b, c AmplitudeS-spectra of the calcite laminaindex series

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Fig. 8 Running correlation (30-years window) between regional rainfall reconstruction and threedifferent winter NAO index reconstructions (11-years smoothed series); Glueck and Stockton (2001)(dotted line); Cook et al. (2002) (dashed line); Luterbacher et al. (2002) (solid line). Gray areasindicate the decrease in the correlation between Lutherbacher NAO index series reconstruccionand regional winter rainfall reconstruction

the late seventeenth century (1675–1700) as well as during most of the nineteenth(1780–1925) and twentieth centuries (1950–2000) explaining around 50% of winterrainfall variability in these regions. Meanwhile, a second factor, which explainsaround 24% of variability, is featured by one centre of action west of Ireland,and this factor was equally important to the NAO-pattern in terms of explainingwinter precipitation towards the four third of the seventeenth, eighteenth, andnineteenth centuries. Furthermore smaller scale processes also influence regionalrainfall variability. As Xoplaki et al. (2004) noted, land–sea effects and interaction,the influence of sea surface temperature connected with latent and sensible heat flux,orographical features, altogether with thermodynamical aspects interact with eachother on different time scales and are superimposed on the quasi-stationary planetarywaves which control large-scale advection.

On the other hand significant low-frequency peaks have been recorded fordifferent time periods in the laminated sediment. Although no convincing expla-nation can be provided of why such a periodicity appears, significant peaks atsimilar periodicities have been detected in other calcite laminated lake sediments. InSoppensee (Switzerland, Livingstone and Hajdas 2001) and in Lake Elk (Minesotta,USA, Dean et al. 2002), the wavelength analysis on varve thickness data seriesindicate the persistence of similar low-frequency peaks as 50- and 22-year, the laterknown as solar Hale cycle. However it must be taken into consideration that inboth cases the data series correspond to the varve thickness and therefore thecontribution of the calcite lamina should be different and related in each case withdifferent limnological features, Moreover the 88-year peak, the solar Gleissbergcycle is a common peak in climate records which has been recorded in the calcite

Climatic Change

lamina thickness of the Pianico interglacial sediment record (southern Alps). Aspreviously argued by some authors the solar variability could be a forcing factorin the formation of this kind of biogenic varves. In Lake La Cruz productivityhas been analysed thought the laminated time period by means of the analysis ofphotosynthetic pigments (Romero-Viana et al. 2010). The results suggested thatprobably solar variability has been an important factor controlling lake productivity.However, inferred fluctuations of past productivity did not seem to be related to theobserved fluctuations in calcite lamina thickness, more dependent, as we have saidbefore, on the water column calcium content.

6 Conclusion

The direct link between laminated sediment features and climatic variability de-scribed previously (Romero-Viana et al. 2008) has allowed the reconstruction ofregional winter precipitation with annual resolution over the last four centuries,using a novel climate proxy, calcite laminae thickness. The verification process bymeans of a comparative analysis with the overlapping instrumental data (1859–1950)confirmed the reconstruction skill, providing high degree of confidence in the rainfallreconstruction. The regional reconstruction extended back three centuries the earlyinstrumental data in the Iberian Peninsula, before the onset of the Late MaunderMinimum, and contributes as other records to the climate variability characterisa-tion. This work demonstrates the potential of laminated sediments as a powerfultool documenting paleoclimatic signals with annual resolution and highlights thepossibilities of paleoclimatic reconstruction using calcite laminated sediments.

Acknowledgements We are very grateful to M. Barriendos and F. Domínguez-Castro who kindlyprovided Toledo drought events series and the Spanish Meteorological Institute which providedthe instrumental data from Madrid and Cuenca stations. We also thank two anonymous reviewsand the editor Stephen Schneider for their useful and constructive comments. This work has beenfinanced by CICyT REN2002-03272 and CGL2005-04040 from the Spanish Ministry of Educationand Science to M.R. Miracle. L. Romero has been supported by a scholarship from GeneralitatValenciana and M. Schimmel was supported through the Consolider Ingenio 2010 project TOPO-IBERIA (CSD2006-00041).

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