Interactive comment on “ Characteristics of cold-warm variation in the Hetao region and its surrounding areas in China during the past 5000 yr ”

In "Characteristics of cold-warm variation in the Hetao region and its surrounding areas in China during the past 5000 yr", the authors introduce a integrate temperature proxy in past 5000 yr derived from different pollens and lake sediment. Although the method seems to have performed ok, I am not sure that it has been exercised enough to be published in CP. Here are a few basic comments that could guide the authors to submit a more detailed manuscript. 1. For the temperature reconstruction, it is very important that the proxy can represent the temperature changes, but the variations of the total organic carbon in loess section, magnetic susceptibility and carbonate content in lake sediment are not only affected by temperature, but also by precipitation. So the authors should give the evidences to support the changes of these proxies due to temperature.


Introduction
The reconstruction of temperature series for various historical periods provides important background for understanding the patterns of natural climate variability and improves our ability to assess the anthropogenic role in observed modern climate change.A number of previous studies have thus focused on climate change of past few centuries to millennium by means of modeling experiments that employ estimated climate forcing and empirical reconstructions based on climate proxy data (Mann et al., 2003).
Correspondence to: Q.-S.Ge (geqs@igsnrr.ac.cn)Several recent studies emphasized spatial reconstruction of climate based on techniques for reconstruction of multivariate climate fields (Mann et al., 1998(Mann et al., , 1999(Mann et al., , 2003(Mann et al., , 2008;;Luterbacher et al., 2002;Evans et al., 2003;Moberg et al., 2005).These spatial reconstructions have focused on the climate changes of the past few centuries to two millennia on a global scale.In China, some scholars have reconstructed temperature series using an integrated method (Wang et al., 1998(Wang et al., , 2007;;Yang et al., 2002;Ge et al., 2006).The uncertainty of reconstructing climatic changes can be reduced by using the method.
the Hetao region and its surrounding areas lie in the transition zone between agriculture and animal husbandry in northern China and include areas of the Mu Us, Hobq, and Ulaan-Buh deserts.The Hetao region has an acutely vulnerable ecological environment and is sensitive to climate change.Thus, it is an ideal area for studying both east-Asian monsoon changes and global climate changes; to do so, it is important to reconstruct the past climatic variations of this region.
During the past few years, a lot of long-term, highresolution climate proxy reconstructions with reliable millennial-scale variability have been produced for this region, which provide us proxy data to reconstruct climate change by using the integrated method.In our study, the characteristics of cold-warm variation in Hetao region and its surrounding area for the past 5000 yr are analyzed by using six long-term reconstructed temperature proxy series (Fig. 1).are the six long-term temperature proxy series (Table 1) selected from recent publications used in our study: -The average July-temperature series in the Daihai Lake (DH) reconstructed quantitatively by using model based on pollens (Xu et al., 2003).
-The oxygen isotope series of a salt lake in Yikezhaomeng, Inner Mongolia (YK) (Qian et al., 2002), which indicates temperature changes with lower than 100 yr temporal resolution.
-The annual average temperature series, which was reconstructed by using model based on pollens in Diaojiaohaizi Lake, Inner Mongolia (DJ) (Shi et al., 2003).
-The total organic-carbon content (TOC) series in Jingbian County (JB) (Xiao et al., 2002).TOC and Md from Jingbian Section are reliable paleo-temperature proxies, in that Jingbian Section contains a higher TOC and a lower Md value during warm/wet period and vice versa (Xiao et al., 2002).
-The magnetic susceptibility series in Huangqihai Lake (HQH) (Shen et al., 2006), which reflects climate changes between the warm-wet and cold-arid periods; therefore the magnetic susceptibility can be as a paleotemperature proxy.
-The carbonate-content series in Zhuyeze Lake (ZYZ) (Long et al., 2007) also reflects climate changes between the warm-wet and cold-arid periods.
Locations for these six series are shown in Fig. 1.The timescales of the six series are more than 5000 yr and are well-dated.Among the six series, DH and DJ showed temperature changes; the others depict proxy temperature changes with different proxy records.6 reconstructions from different proxy archives represent temperature changes.According to instrumental temperature records, the temperature changes of each region which 6 selected series locate can explain between 83% and 94% of annual temperature variability of the study area in 1951-2007.But the six series have different temporal resolution, and there are difference about climate change revealed by the six series in terms of type of natural archive and their correlation with temperature.
For the sake of transferring and comparing data, we used the annual surface-temperature grid-point (1 latitude ×1 longitude) data set in 1951-2007 in China (http://cdc.cma.gov.cn/) for analysis.This data set was obtained using the Spatial Kriging Interpolation Method based on average monthly temperature and DEM (digital elevation model) materials of 731 stations throughout China.

Methods
Two ways to reconstruct regional paleo-temperature series under the constraint of insufficient data were commonly used in previously published articles: computing the average of all available proxy series in a study area (Jones et al., 1999;Crowley and Lowery, 2000) using a data set that is relatively small and heterogeneous; merging proxy records of several sub-regions by a specific area weighting (Wang et al., 2000;Yang et al., 2002).The latter method has recently been widely used for regional, hemispheric, and global climate reconstructions (Bradley et al., 1993;Jones et al., 1998;Mann et al., 1998Mann et al., , 1999Mann et al., , 2003;;Moberg et al., 2005).This method emphasizes a synthesis of different types of proxies derived from various local regions having differing temporal resolutions.The integrated results show some important climate features not derived from one type of proxy records or from proxies with identical temporal resolutions.To some extent, the multi-proxy analysis method can thus reduce uncertainties in proxy-based climate reconstructions.
Taking the actual background of the study area into consideration, we developed an improved method to reconstruct the regional temperature series of the small Hetao region.
First we calculated the series of annual temperatures for the whole region (WT) of Hetao and neighboring areas according to the surface annual-temperature grid data during 1951-2007 for China (Eq.1).We next calculated the correlation between WT and the annual temperature series in each grid area; this correlation is considered as a contribution to the entire region.The total value (TV) is the sum of the grid contributions provided by each of the series (Eq.2); the weighted value is the ratio of the contribution value of one series to the TV (Eq.3).Finally, based on the weighted values of the grids, the following weighted-average equation was adopted to combine the six series into the whole regional temperature series (Eq.4).The equations are as follows: Where WT is the series of annual temperatures for the whole region according to the surface annual-temperature grid data during 1951-2007 for China; T i is the temperature of each grid and n is the numbers of grid.
Where TV is the sum of r and r i is the correlation between WT and T i .
Where S i is the area's weighted value.
Where T w is the whole regional temperature, T i is the temperature of each sub-region and m is the numbers of subregion.
Before averaging, each series is standardized; this gives the relative amplitude of temperature change, as shown in Fig. 2. The three steps of the method for standardizing are as follows: (1) Selecting samples-According to the correlative papers, the reconstructed data of all but the DH series were obtained by digitizing.All of the abrupt climate change points in each series were taken as random samples to reconstruct the whole region series.
(2) Calibrating the 14 C ages into calendar ages-using the calib5.0program (Stuiver et al., 1998), the six series were all converted to calendar chronological series.
(3) Making the series dimensionless-each series was standardized to a dimensionless series that reflected the climate variation amplitude.
With respect to the time resolution, three of the six series we selected are higher than 100 yr, two are about 100 yr, and one is lower than 100 yr (Table 1).Accordingly, the past 5000 yr was divided into 100-yr intervals.For every series we selected, we calculated the average of all data within each 100-yr period if the series resolution was not lower than 100 yr and by linear interpolation between existing data if the series resolution was lower than 100 yr.Finally, a series that indicates temperature variation (weighted average, WA) was acquired according to the methods previously described (as depicted in Fig. 3).

Results and discussion
Figure 3 shows that the change trend of CA (arithmetic average) is very consistent with that of WA, with the only differences being the values of original data.In the past 5000 yr and on the millennial scale, variations in temperature were warm in 5000∼2600 cal yr BP and were colder after 2600 cal yr BP.Within these two periods, the temperature fluctuated, and there existed numerous short, multi-century sub-stages.We divided the 5000 yr into following seven periods according to cold-warm variations.With respect to the time resolution, three of the six series we selected are higher than 100 yr, two re about 100 yr, and one is lower than 100 yr (Table 1).Accordingly, the past 5000 yr was divided to 100-yr intervals.For every series we selected, we calculated the average of all data within each 00-yr period if the series resolution was not lower than 100 yr and by linear interpolation between xisting data if the series resolution was lower than 100 yr.Finally, a series that indicates temperature ariation (weighted average, WA) was acquired according to the methods previously described (as epicted in Fig. 3).

Fig. 2.
Standardized 5000-yr regional temperature series for Hetao region and its vicinity.
1. 5000∼4500 yr BP: This period was the end of the Holocene Megathermal Maximum Age.The temperature was higher than the mean value of the whole series in Hetao and its neighboring areas.Other domestic studies have validated the existence of this warm sub-stage.The temperature series reconstructed by Chu (1973) showed that it was warm in China during this period, as well as it was warm and humid in the Poyanghu Lake area of Jiangxi Province (Peng et al., 2003), in the Zhengzhou area of Henan Province (Wang et al., 2004), in the Hanihu Lake area of Jilin Province (Cui et al., 2006), and in Dunde ice core in Qinghai Province (Yao et al., 1992).These facts are also corroborated by many worldwide studies.It was proved that the climate during this period was warm in the north of Iceland (Axford et al., 2007) and in the area of the North Atlantic (Bond et al., 2001).
( 1973) showed that in China, during this period, it was warm and humid in the Poyan Lake area of Jiangxi Province (Peng et al., 2003)," to "The temperature series reconstru by Chu (1973) showed that it was warm in China during this period, as well as it was w and humid in the Poyanghu Lake area of Jiangxi Province (Peng et al., 2003)," 3. On page 4: change "Figure 3 6.In line 17 in left column on page 6: add "x " before "is the average of the origin series," 3. 3900∼2600 cal yr BP: The temperature was relatively high compare with the mean value of the whole series (Fig. 3).In addition, the δ 18 O and pollens appearing in peat in Taishizhuang village gave evidence of a very warm event during 4.2∼3.38 cal kyr BP in the northern Huabei area of China (Jin et al., 2002); the Indian summer monsoon was very strong at the same time (Hong et al., 2003); the climate was very warm at about 2.5 kyr BP in Fennoscandia region, Finland (Seppä et al., 2002).
4. 2600∼1450 cal yr BP: The temperature decreased rapidly and was lower than the mean value of the whole series (Fig. 3).Parallel evidence abounds: The lake-sediment record in Jiaming Lake showed that the climate turned cold after 2.2 kyr BP in southern Taiwan (Luo et al., 1997); The climate was also cold during 2550∼1211 yr BP in Ulaan-Buh Desert of China (Jia et al., 2003); The strata in Hunshandake Desert of China show an abundance of Aeolian sand at about 1.8∼1.3cal kyr BP, thus giving evidence of a cold climate (Jin et al., 2004); The Guliya ice core and tree-ring records in China show that the climate was cold at 0 AD (Yao et al., 2001); The winter half-year temperature was relatively low during 1700∼1400 yr BP in eastern China (Ge et al., 2003); The yearly average temperature was low in the Tibet plateau region during the period (Yang et al., 2003); A cold event during 1.8∼1.4kyr BP had been recorded in the southern deep sea off Iceland (Bianchi et al., 1999); An ice-floating event appeared in the North Atlantic Ocean at 1.4 kyr BP (Bond et al., 1997).
5. 1450∼1000 cal yr BP: The climate was relatively warm compare with the temperature of its adjacent periods but less so than the degree of warmth at 5000 cal yr BP.This period corresponded to the Medieval Warm Period.Following are p proofs that give examples: A warming event happened in Daihai Lake in the southern part of the study region during 1.2∼0.9kyr BP (Jin et al., 2002); The Dunde ice core indicated that there was a climate warming phase during the 13th century (Yao et al., 1992); The Guliya ice core recorded a warm event in 1250∼1150 cal yr BP (Yao et al., 1996); At the Chesapeake Dam, the Medieval Warm Period began at 1150 cal yr BP (Cronin TM et al., 2003), which was earlier than the period began in other areas in the world.
6. 1000∼300 cal yr BP: the temperature decreased again.this period includes the Little Ice Age.Temperature of the lake water of Daihai Lake was low during 2010-300 yr BP (Shen et al., 2002).Aeolian sand deposited in Hunshandake Desert during 700-200yr BP produced a record of the cold event, which took place at about 400 yr BP (Jin et al., 2004).
7. 300 cal yr BP to present: The climate has been warming.Shen et al. (2002) found out that the water temperature in Daihai Lake had been rapidly warming since 300 yr BP, increasing from 16.2 • C to 17.5 • C.
In addition, the correlation coefficient of temperature records of Zhangye meteorological station and Hetao region from 1956 to 2009 is 0.936, and the tree-ring width and temperature data from Zhangye meteorological station have a closer relation (Liu et al., 2007).Therefore, the tree-ring width indicated the temperature changes in Qilian Mountain.A comparison of series reconstructed for the Hetao and its surrounding area with the Qilian mountain temperature series (Liu et al., 2007) from tree-ring, and temperature reconstruction for western north China from history documents (Hao et al., 2009) in Fig. 4. The Figure4 shows that the temperature changes of the Hetao and its surrounding area shows good agreement with that of the Qilian Mountain and of eastern part of North West China.But there are differences in some stages, such as about 500 yr BP, it may be induced by the difference between tree ring and other proxy archives, because generally in this region, the width of tree ring is more sensitive to low temperature, but not for the high temperature.

Conclusions
The air temperature, on the millennial scale variation, was relatively high compare with the mean value of the whole series during 5000∼2600 cal yr BP and decreased after 2600 cal yr BP.Many temperature fluctuations took place during those two periods.During the periods of 5000∼4500 cal yr BP, 3900∼2600 cal yr BP, 1450∼1000 cal yr BP, and 300 cal yr BP to present, the climate was warm; while during the periods of 4500∼3900 cal yr BP, 2600∼1450 cal yr BP, and 1000∼300 cal yr BP, the temperature decreased.
The cold-warm variation of climate on long-term scale disclosed by the reconstructed series described in this paper took place in phase with that proved in other global research efforts.However, on the century to multi-century scale, the beginning and the ending times varied from region to region, thus implying that climate changes did not occur simultaneously in different regions, because the climate are affected www.clim-past.net/6/475/2010/Clim.Past, 6, 475-481, 2010 M.-Q.Li et al.: Characteristics of cold-warm variation in the Hetao region by regional atmospheric circulation, regional landform, et al.. Taking China as an example, according to modern instrumental data, the domain of China can be divided into 5 climate regions (Ge et al., 2010) and the variations of annual mean temperature were mainly determined by variations winter-half year temperature.Our study area lies in the east of the northwest region.The temperature of winter-half year is affected by the winter monsoon.The winter monsoon has different effect on the 5 regions because of the Qinghai-Tibet plateau, mountains and the distance from Siberian area which is one of the original sources of cold wave, therefore there are differences in temperature change in this 5 regions.
The steps reconstructing series are as follows: Firstly, we standardized the selected 6 series respectively, equation is as follows: Where T i is standard score, x i is the ith value in the origin series, x is the average of the origin series, and σ is standard deviation of the origin series.Secondly, we synthesized a series with the 6 standardized series by using the methods of "arithmetic average" and "weighted average".The equations are follows: Where T a is arithmetic average value, T w is weighted average value and S i is the area's weighted value.

Fig. 1 .
Fig. 1.Distribution map for six locations of proxy climate records.(Stars=the site of proxy climate records; dots=primary cities).

Fig. 2 .
Fig. 2. Standardized 5000-yr regional temperature series for Hetao region and its vicinity " to: 4. In line 6-11 in left column on page 6: change "The winter monsoon has little effect on Qinghai-Tibet Plateau because of its height; hence, there is difference between the T region and other four regions.In addition, because of landform, especially mountains and distance from Siberian area, there are differences in temperature change in other regions." to "The winter monsoon has different effect on the 5 regions because of Qinghai-Tibet plateau, mountains and the distance from Siberian area which is one of original sources of cold wave, therefore there are differences in temperature change in th regions." 5.In line 16 in left column on page 6: delete "x "

Fig. 4 .
Fig. 4. Comparison of three temperature reconstructions for China.Black curve: temperature series reconstructed in the paper; Green dashed line: 10-yr average temperature changes reconstructed by using tree-ring in Qilian Mountain (Liu et al, 2007); Green curve: 100-yr smoothing average temperature records in Qilian Mountain; Red dashed line: 10-yr average temperature record reconstructed by using history record and natural evidence in eastern part of North West China; and Red curve (Hao et al., 2009): 100-yr smoothing average temperature record in eastern part of North West China.

Table 1 .
Information regarding the six series applied.
Notes:(1)T represents temperature;(2)Cal.represents the series chronological control provided by calendar ages; (3)14 C represents the series as chronologically controlled by 14 C ages.