The meteorological observational period in Turkey,
which starts ca. 1930 CE, is too short for understanding long-term climatic
variability. Tree rings have been used intensively as proxy records to
understand summer precipitation history of the region, primarily because they
have a dominant precipitation signal. Yet, the historical context of
temperature variability is unclear. Here, we used higher-order principle
components of a network of 23 tree-ring chronologies to provide a
high-resolution spring (March–April) temperature reconstruction over Turkey
during the period 1800–2002. The reconstruction model accounted for 67 %
(Adj.
Long-term meteorological observations in the Mediterranean region allow access to 100 years of instrumental recordings of temperature, precipitation and pressure in most of the region. Moreover, natural archives as well as documentary information provide resources with which to make sensitive climate reconstructions (Luterbacher et al., 2012). An extensive body of literature details climate changes in the Mediterranean region over the last two millennia (Luterbacher et al., 2012). Paleolimnological studies provide evidence that the Medieval Climatic Anomaly (MCA; 900–1300 CE) characterized warm and dry conditions over the Iberian Peninsula, while the Little Ice Age (LIA; 1300–1850 CE) brought opposite climate conditions, forced by interactions between the East Atlantic and North Atlantic Oscillation (NAO; Sanchez-Lopez et al., 2016). In addition, Roberts et al. (2012) highlighted an intriguing spatial dipole NAO pattern between the western and eastern Mediterranean region, which brought antiphased warm (cool) and wet (dry) conditions during the MCA and LIA. The hydro-climate patterns revealed by previous investigations appear to have been forced not only by NAO but other climate modes with nonstationary teleconnections across the region (Roberts et al., 2012).
Tree-ring chronology sites in Turkey used to reconstruct temperature. Circles represent the new sampling efforts from this study and the triangles represent previously published chronologies (YAU, SIA and SIU in Mutlu et al., 2011. TIR in Akkemik et al., 2008. TAN in Köse et al., 2013. KIZ, ESK, TEF, BON, KEL, USA, FIR and TUR in Köse et al., 2011. CAT and INC in Köse et al., 2005). The box (dashed line) represents the area for which the temperature reconstruction was performed.
The climate of Turkey is mainly characterized by a Mediterranean macroclimate (Türkeş, 1996a). Contrary to most countries in the Mediterranean region, Turkey has relatively short meteorological records, which start in the 1930s, for understanding long-term climatic variability. On the other hand, proxy records such as speleothems (Fleitmann et al., 2009; Jex et al., 2010; Göktürk et al., 2010), lake sediments (Wick et al., 2003; Jones et al., 2006; Roberts et al., 2008, 2012; Kuzucuoğlu et al., 2011; Woodbridge and Roberts, 2011; Ülgen et al., 2012; Dean et al., 2013) and tree rings, have been used to reconstruct long-term hydroclimate conditions over Turkey. Tree rings in particular have shown to provide useful information about the past climate of Turkey and were used intensively during the last decade to reconstruct precipitation in the Aegean (Griggs et al., 2007), Black Sea (Akkemik et al., 2005, 2008; Martin-Benitto et al., 2016), Mediterranean regions (Touchan et al., 2005a), as well as the Sivas (D'Arrigo and Cullen, 2001), southwestern (Touchan et al., 2003, 2007; Köse et al., 2013), south-central (Akkemik and Aras, 2005) and western Anatolian (Köse et al., 2011) regions of Turkey. These studies used tree rings to reconstruct precipitation because available moisture is often found to be the most important limiting factor that influences radial growth of many tree species in Turkey. These studies revealed past spring–summer precipitation, and described past dry and wet events and their duration. Recently, Cook et al. (2015) presented Old World Drought Atlas (OWDA), which is a set of year-by-year maps of reconstructed Palmer Drought Severity Index from tree-ring chronologies over the Europe and Mediterranean Basin.
Besides detailed information on precipitation history represented by these
paleoscientific studies, we still have very limited knowledge on past
temperature variability of Turkey. For example, significant decreases in
spring diurnal temperature ranges (DTRs) occurred throughout Turkey from 1929
to 1999 (Turkes and Sumer, 2004). This decrease in spring DTRs was
characterized by daytime temperatures that remained relatively constant while
a significant increase in nighttime temperatures were recorded over western
Turkey and were concentrated around urbanized and rapidly urbanizing cities.
The historical context of this gradual warming trend in spring temperatures
is unclear. Heinrich et al. (2013) provided a winter-to-spring temperature
proxy for Turkey from carbon isotopes within the growth rings of
Site information for the new chronologies developed by this study in Turkey.
Summary statistics for the new chronologies developed by this study in Turkey.
The study area, which spans 36–42
To investigate past temperature conditions, we used a network of 23
tree-ring site chronologies (Fig. 1). Fifteen chronologies were produced by
previous investigations (Mutlu et al., 2011; Akkemik et al., 2008; Köse et al., 2005, 2011, 2013) that
focused on reconstructing precipitation in the study area. In addition, we
sampled eight new study sites and developed tree-ring time series for these
areas (Table 1). Increment cores were taken from living
Samples were processed using standard dendrochronological techniques (Stokes and Smiley, 1968; Orvis and Grissino-Mayer, 2002; Speer, 2010). Tree-ring widths were measured, then visually cross-dated using the list method (Yamaguchi, 1991). We used the computer program COFECHA, which uses segmented time-series correlation techniques, to statistically confirm our visual cross-dating (Holmes, 1983; Grissino-Mayer, 2001). Cross-dated tree-ring time series were then standardized by fitting a 67 % cubic smoothing spline with a 50 % cutoff frequency to remove non-climatic trends related to the age, size and the effects of stand dynamics using the ARSTAN program (Cook, 1985; Cook et al., 1990a). These detrended series were then pre-whitened with low-order autoregressive models to produce time series with a strong common signal and without biological persistence. These series may be more suitable to understand the effect of climate on tree growth, even if any persistence due to climate might be removed by pre-whitening. For each chronology, the individual series were averaged to a single chronology by computing the biweight robust means to reduce the influences of outliers (Cook et al., 1990b). In this research we used residual chronologies obtained from ARSTAN to reconstruct temperature.
The mean sensitivity, which is a metric representing the year-to-year variation in ring width (Fritts, 1976), was calculated for each chronology and compared. The minimum sample depth for each chronology was determined according to expressed population signal (EPS), which we used as a guide for assessing the likely loss of reconstruction accuracy. Although arbitrary, we required the commonly considered threshold of EPS > 0.85 (Wigley et al., 1984; Briffa and Jones, 1990).
Summary of response function results of 23 chronologies. Red color
represents negative effects of climate variability on tree ring width; blue
color represents positive effects of climate variability on tree ring width;
We extracted high-resolution monthly temperature and precipitation records
from the climate dataset CRU TS 3.23 gridded at 0.5
First, the climate–growth relationships were investigated with response function analysis (RFA; Fritts, 1976) for biological year from the previous October to current October using the DENDROCLIM2002 program (Biondi and Waikul, 2004). This analysis is done to determine the months during which the tree growth is the most responsive to temperature. RFA results showed that precipitation from May to August and temperature in March and April have dominant control on tree-ring formation in the area. Second, we produced correlation maps showing correlation coefficients between tree-ring chronologies and the climate factors most important for tree growth, which are May–August precipitation and March–April temperature, to find the spatial structure of radial growth–climate relationship (St. George, 2014; St. George and Ault, 2014; Hellmann et al., 2016). For each site we used the closest gridded temperature and precipitation values.
Principal components analysis statistics for the Turkey temperature reconstruction model.
The climate reconstruction is performed by regression based on the principal
components (PCs) of the 23 chronologies within the study area. Principle
component analysis (PCA) was done over the entire period in common with the
tree-ring chronologies. The significant PCs were selected by stepwise
regression. We combined forward selection with backward elimination setting
The comparison of May–August total precipitation (black) and the
first principal component of 23 tree-ring chronologies (gray). Correlation
coefficient between two time series is 0.65 (
The quality of the reconstruction is assessed by a number of standard
statistics. The overall quality of fit of reconstruction is evaluated based
on the determination coefficient (
Calibration and verification statistics of the bootstrap method (1000 iterations applied) showing the mean values based on the 95 % confidence interval (CI).
Note that RMSE: root mean squared error,
To identify the extreme March–April cold and warm events in the
reconstruction, standard deviation (SD) values were used. Years 1 and 2 SD
above and below the mean were identified as warm, very warm, cold and very
cold years, respectively. As a way to assess the spatial representation of
our temperature reconstruction, we conducted a spatial field correlation
analysis between reconstructed values and the gridded CRU TS3.23 temperature
field (Jones and Harris, 2008) for a broad region of the Mediterranean over
the entire instrumental period (ca. 1930–2002). Finally, we compared our
temperature reconstruction and also precipitation signal (PC
In addition to 15 chronologies developed by previous studies, we produced
6
Calibration and cross-validation statistics for the Turkey temperature reconstruction model.
Maps showing Pearson's correlation coefficients between the sites
chronologies and
RFA coefficients of May to August precipitation are positively correlated
with most of the tree-ring series (Fig. 2) and among them May and June
coefficients are generally significant. The first principal component of the
23 chronologies, which explains 47 % of the tree-growth variance, is
highly correlated with May–August total precipitation, statistically (
Correlation maps representing influence of May–August precipitation
(Fig. 4a) and March–April temperature (Fig. 4b) also showed that strength of
the summer precipitation signal is higher and significant almost all over
Turkey. Higher precipitation in summer has a positive effect on tree growth,
because of long-lasting dry and warm conditions over Turkey (Türkeş,
1996b; Köse et al., 2012). Spring precipitation signals are generally
positive and significant only for four tree-ring sites. The sites located at
the upper distributions of the species generally showed higher correlations.
The highest correlations obtained for
Actual (instrumental) and reconstructed March–April temperature
(
March–April temperature reconstruction for Turkey for the period
1800–2002 CE. The horizontal, central white line shows the reconstructed
long-term mean and does not include instrumental data; black background
denotes Monte Carlo (
The higher-order PCs of the 23 chronologies are significantly correlated with
the March–April temperature and, by nature, are independent of the
precipitation signal (Table 3). The best selection for fit temperatures are
obtained with the PC
Spatial correlation map for the March–April temperature
reconstruction. Spatial field correlation map showing statistical
relationship between the temperature reconstruction and the gridded
temperature field at 0.5
Spatial correlation maps for the March–April temperature
reconstruction and precipitation signal (PC
Using this method, the calibration and verification statistics indicated a statistically significant reconstruction (Table 4, Fig. 5). For additional verification, we also present split-sample procedure results. Similarly, the bootstrap results, derived calibration and verification tests using this method indicated statistically significant RE and CE values (Table 5).
The regression model accounted for 67 % (Adj.
Our temperature reconstruction on the 1800–2002 period is obtained by bootstrap regression using 1000 iterations (Fig. 6). The confidence intervals are obtained from the range between the 2.5th and the 97.5th percentiles of the 1000 simulations. Low-frequency variability of our spring temperature reconstruction showed larger variability in the 19th century than the 20th century. For the pre-instrumental period (1800–1929), a total of 23 cold (1813, 1818, 1821, 1824, 1837, 1848, 1854, 1858, 1860, 1869, 1877–1878, 1880–1881, 1883, 1897–1898, 1905–1907, 1911–1912, 1923) and 13 warm (1801–1802, 1807, 1845, 1853, 1866, 1872–1873, 1879, 1885, 1890, 1901, 1926) events were determined. After comparing our results with event years obtained from May to June precipitation reconstructions from western Anatolia (Köse et al., 2011), the cold years 1818, 1848 and 1897 appeared to coincide with wet years and 1881 was a very wet year for the entire region. Furthermore, these years can be described as cold (in March–April) and wet (in May–June) for western Anatolia.
Comparison of March–April temperature reconstruction (gray) with
the mean of corresponding grid points from European spring (March to May)
temperature reconstruction (Xoplaki et al., 2005; black) over the study area
(36–42
Among the warm periods in our reconstruction, conditions during the year 1879 were dry, 1895 wet, and 1901 very wet across the broad region of western Anatolia (Köse et al., 2011). Hence, we defined 1879 as a warm (in March–April) and dry year (in May–June), and 1895 and 1901 were warm and wet years. In the years 1895 and 1901 the combination of a warm early spring and a wet, late spring–summer caused enhanced radial growth in Turkey, interpreted as longer growing seasons without drought stress.
Of these event years, 1897 and 1898 were exceptionally cold and 1845, 1872 and 1873 were exceptionally warm. During the last 200 years, our reconstruction suggests that the coldest year was 1898 and the warmest year was 1873. The reconstructed extreme events also coincided with accounts from historical records. Server (2008) recounted the winter of 1898 as characterized by anomalously cold temperatures that persisted late into the spring season. A family that brought their livestock herds up into the plateau region in Kırşehir seeking food and water were suddenly covered in snow on 11 March 1898. This account of a late spring freeze supports the reconstruction record of spring temperatures across Turkey and offers corroboration to the quality of the reconstructed values.
Seyf (1985) reported that extreme summer temperature during the year 1873 resulted in widespread crop failure and famine. Historical documents recorded an infamous drought-derived famine that occurred in Anatolia from 1873 to 1874 (Quataert, 1996; Kuniholm, 1990), which claimed the lives of 250 000 people and a large number of cattle and sheep (Faroqhi, 2009). This drought caused widespread mortality of livestock and depopulation of rural areas through human mortality, and migration of people from rural to urban areas. Further, the German traveler Naumann (1893) reported a very dry and hot summer in Turkey during the year 1873 (Heinrich et al., 2013). Conditions worsened when the international stock exchanges crashed in 1873 (Zürcher, 2004). Our temperature record suggests that dry conditions during the early 1870s were possibly exacerbated by warm spring temperatures that likely carried into summer. A similar pattern of intensified drought by warm temperatures was demonstrated recently by Griffin and Anchukaitis (2014) for the current drought in California, USA.
Extreme cold and warm events were usually 1 year long, and the longest extreme cold and warm events were 2 and 3 years long, respectively. These results were similar with durations of extreme wet and dry events in Turkey (Touchan et al., 2003, 2005a, b, 2007; Akkemik and Aras, 2005; Akkemik et al., 2005, 2008, Köse et al., 2011; Güner et al., 2016). Moreover, seemingly innocuous short-term warm events, such as the 1807 event, were recorded across the Mediterranean and in high elevations of the European regions. Casty et al. (2005) reported the year 1807 as being one of the warmest alpine summers in the European Alps over the last 500 years. As such, a drought record from Nicault et al. (2008) echoes this finding, as a broad region of the Mediterranean Basin experienced drought conditions.
Heinrich et al. (2013) analyzed winter-to-spring (January–May) air
temperature variability in Turkey since 1125 CE as revealed from a robust
tree-ring carbon isotope record from
Spatial correlation analysis revealed that our network-based temperature
reconstruction was representative of conditions across Turkey as well as the
broader Mediterranean region (Fig. 7). During the period 1930–2002,
estimated temperature values were highly significant (
We compared our tree-ring-based temperature reconstruction with existing
gridded temperature reconstructions for Europe (Xoplaki et al., 2005, Fig. 8a;
Luterbacher et al., 2016, Fig. 8b) and the OWDA (Cook et al., 2015, Fig. 8c) for further
validation of the reconstruction. Spatial correlations over the past 200 years were
lower with reconstructed European summer temperature (May to July; Fig. 8b).
Yet, we expected this result because of the paucity of Turkey derived proxies
in the other reconstructions, as well as the differing seasons involved
across the reconstructions. Similarly, our reconstruction showed weak
correlations with summer drought index over Turkey. Besides comparing
different seasons, perhaps this is because less precipitation begets drought
conditions rather than high temperature in the region. The highest and
significant (
We also compared the precipitation signal (PC
In this study, we used a broad network of tree-ring chronologies to provide the first tree-ring-based temperature reconstruction for Turkey and identified extreme cold and warm events during the period 1800–1929 CE. Similar to the precipitation reconstructions against which we compare our air temperature record, extreme cold and warm years were generally short in duration (1 year) and rarely exceeded 2–3 years in duration. The coldest and warmest years over western Anatolia were experienced during the 19th century and the 20th century is marked by a temperature increase.
Reconstructed temperatures for the 19th century suggest that more short-term fluctuations occurred compared to the 20th century. The gradual warming trend shown by our reconstruction calibration period (1930–2002) is coeval with decreases in spring DTRs. Given the results of Turkes and Sumer (2004), the variations in short- and long-term temperature changes between the 19th and 20th centuries might be related to increased urbanization in Turkey.
We highlight that the 20th century warming trend is unprecedented within the context of the past ca. 200 years, especially over the past ca. 15 years. Correlations with gridded climate fields and other climate reconstructions from the region revealed that our network-based temperature reconstruction was representative of conditions across Turkey, as well as the broader Mediterranean region. Expanding the tree-ring network across Turkey, especially to the east, will improve the spatial implications of future temperature reconstructions.
The study revealed the potential for reconstructing temperature in an area previously thought impossible, especially given the strong precipitation signals displayed by most tree species growing in the dry Mediterranean climate that characterizes broad areas of Turkey. Our reconstruction only spans 205 years due to the shortness of the common interval for the chronologies used in this study, but the possibility exists to extend our temperature reconstruction further back in time by increasing the sample depth with more temperature-sensitive trees, especially from northeastern Turkey. Thus, future research will focus on increasing the number of tree-ring sites across Turkey and maximizing chronology length at existing sites that would ultimately extend the reconstruction back in time.
Tree-ring data set is available from the International Tree-Ring Data Bank – ITRDB
(
This research was supported by the Scientific and Technical Research Council of Turkey (TUBITAK), projects ÇAYDAG 107Y267 and YDABAG 102Y063. Nesibe Köse was supported by the Council of Higher Education of Turkey. We are grateful to the Turkish Forest Service personnel and Ali Kaya, Umut Ç. Kahraman and Hüseyin Yurtseven for their invaluable support during our field studies. We thank Ufuk Turuncoğlu for his help on spatial analysis. Joel Guiot was supported by the Labex OT-Med (ANR-11-LABEX-0061), French National Research Agency (ANR). Edited by: J. Luterbacher Reviewed by: F. Charpentier Ljungqvist and three anonymous referees