Tan & Liu, 2003 html text available at: http://onlinelibrary.wiley.com/doi/10.1029/2003GL017352/full
The pdf version is in articoli.html (private directory), but the table with data is in the html version of the paper. ===>>> WTR=warm season temperature reconstruction (MJJA) <<<====== ===>>> BTR=Briffa temperature reconstruction (MJJA) <<<======
BTR Data

From Abbot & Marohasy, 2017, pag.37:
There is an extensive literature examining the occurrence of periodic cycles within proxy temperature reconstructions, through application of spectral analysis [32,78,88] . Many of these stud- ies also discuss possible relationships between these cyclic pat- terns in temperature profiles and natural phenomena that may affect causation, particularly those associated with solar cycles [14,27,40,56,74,81,82,97] . For example, in the southern hemisphere, Nordemann et al. [74] undertook spectral analysis using tree ring data from Brazil and Chile, providing evidence for associations with solar cycles, particularly the Suess ( ∼200 year), Gleissberg ( ∼90 years), Hale ( ∼ 22 years) and Schwabe (11 years) cycles.
Rigozoa et al. [79] examined tree ring widths in Chile, and found an association with solar activity with 11 and 80 year periodicities.
In the northern hemisphere, Raspopov et al. [78] performed spectral analysis of long-term dendrochronological data from Cen- tral Asia and demonstrated an approximate 200-year climatic pe- riodicity, showing a high correlation with solar periodicity for the de Vries period ( ∼210 years). Ogurtsov et al. [75] reported spectral analysis of tree periodicity and discussed the association with the modulation of regional climate in Northern Fennoscandia by the Gleissberg solar cycle ( ∼90 years).
Moffa-Sanchez et al. [68] examined marine sediments for isotopic signals in the shells of the planktonic foraminifera over the past 1000 years. Spectral analysis showed a 200-year periodicity, identified with de Vries solar cycle ( ∼210 years).
Galloway et al.[32] generated a late Holocene temperature record based on diatoms from a sediment obtained from British Columbia, Canada. Spectral analysis shows significant periodicities at 42–60, 70–89, 241–243, and 380 years, and inferred relationships to sunspot number variation.
Tan and Liu [89] produced a 2650-year temperature reconstruction from annual layers of a stalagmite from China, with spectral analysis indicating significant periodicities at 206 and 325 years.
Cyclic variations have also been associated with large-scale internal climate oscillatory modes [15] , that may themselves in turn be influenced by solar activity [49,65,91,93,100,102] .
For example, Wilson et al. [97] examined tree ring widths to enable a reconstruction over 1300 years for the Gulf of Alaska: identifying oscillatory modes at 90, 38, 24, 50.4 and 18.7 years related to changes in sea surface

ABSTRACT of Tan & Liu, 2003:
[1] A 2650-year (BC665-AD1985) warm season (MJJA: May, June, July, August) temperature reconstruction is derived from a correlation between thickness variations in annual layers of a stalagmite from Shihua Cave, Beijing, China and instrumental meteorological records. Observations of soil CO2 and drip water suggest that the temperature signal is amplified by the soil-organism-CO2 system and recorded by the annual layer series. Our reconstruction reveals that centennial-scale rapid warming occurred repeatedly following multicentenial cooling trends during the last millennia. These results correlate with different records from the Northern Hemisphere, indicating that the periodic alternation between cool and warm periods on a sub-millennial scale had a sub-hemispherical influence.

[4] According to observations near Shihua Cave [Tang and Zhou, 1999], the relationship between soil CO2 (C) and atmospheric temperature (T) can be expressed as ln (C) = 0.0657T + 6.4941 (r = 0.85, p < 0.001). This means that a little change in atmospheric temperature can lead to a significant change in soil CO2, which controls the quantity of dissolved and subsequently deposited carbonate. Further calculation indicates that the weighted content of HCO3− in groundwater in July was about 246 times higher than in June (1998) due to higher soil CO2 content, 5000 ppmv versus 3500 ppmv, respectively.
[6] The chronology of stalagmite TS9501 from Shihua Cave has been studied in detail [Tan et al., 2002]. Since it was actively growing when collected in November 1995, its topmost layer is known to have formed in that year.
[8] Comparison of the LTC ( layer thickness chronology) with the standardized instrumental records of Beijing (1951-1985) indicates that about 48% of the variation in layer thickness can be explained by MJJA temperature, and about another 10% by April precipitation according to separate regressions. Since observed temperature data for Beijing have multi-year gaps prior to 1930, the observed data between 1930 to 1985 (lack of 1938) provide calibration for the LTC (Figure 2a, r = 0.55, p < 0.001).

Look at fig.3.
Comparison between the observed temperature and the LTC (see text). (a), Comparison of observed Beijing MJJA temperature (purple) and the LTC (red) from 1930 to 1985. Timescale is the same as that in (c). (b), Comparison of observed Beijing MJJA temperature (purple) and observed NH annual mean temperature (blue) from 1930 to 2000. (c), Comparison of the LTC (red) and observed NH mean annual temperature (blue) from 1856 to 1985 [Observed data for Beijing from website: giss-nasa (lack of 1938). NH data from website: cru-uea.

Received links to the data from Rob Wilson on 3.10.2017 with the mail:
Hi Franco
2007 recon data is available here: Paleo
NB. The detrending of the data will make it difficult to find a strong cenenntial signal I think.

There is an updated version -detrending in a different way (Wiles et al. 2014)- which was used in this large scale comspoite compilation. Coded GOA. Also Paleo
hope this helps

Received data from Paola Moffa-Sanchez with this mail:
Dear Franco Zavatti,
Thank you for your email. What you say sounds very interesting. It is very possible that the Hale solar cycle has an imprint on the North Atlantic hydrography. However, we were very cautious at interpreting any of these cycles since our data has a time resolution is of 6 years (in a few occasions this increases to 12years when we have data points missing because we didn't have sufficient material to get a measurement). I think to further investigate this idea it would be interesting to analyse some of the annual resolved proxies for this (ie. long-lived bivalves) or maybe we would need higher resolved sediment cores.
I have attached the raw data for the paper.
Hope this helps.
Paola Moffa
fz 28.9.17.       Last update: 5 October 2017