# asia_russ131w - Tyn hill (Altai) - Breitenmoser Tree Ring Chronology Data
#-----------------------------------------------------------------------
#		World Data Center for Paleoclimatology, Boulder
#				and
#		NOAA Paleoclimatology Program
#-----------------------------------------------------------------------
# NOTE: Please cite Publication, and Online_Resource and date accessed when using these data.
# If there is no publication information, please cite Investigators, Title, and Online_Resource and date accessed.
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# Online_Resource:
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# Online_Resource: https://www.ncdc.noaa.gov/paleo/study/24611
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# Original_Source_URL:https://www.ncdc.noaa.gov/paleo/study/4701
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# Description/Documentation lines begin with #
# Data lines have no #
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# Archive: Tree Rings
#--------------------
# Contribution_Date
#	Date: 2016-01-07
#--------------------
# Title
#	Study_Name: asia_russ131w - Tyn hill (Altai) - Breitenmoser Tree Ring Chronology Data
#--------------------
# Investigators
#	Investigators:  Breitenmoser, P.; Bronnimann, S.; Frank, D.
#--------------------
# Description_and_Notes
#	Description: Data from Breitenmoser 2014 Journal of past Climate supplementary, see publication for ARSTAN standardization details
#--------------------
# Publication
#	Authors: Breitenmoser, P.; Bronnimann, S.; Frank, D.
#	Published_Date_or_Year: 2014-03-11
#	Published_Title: Forward modelling of tree-ring width and comparison with a global network of tree-ring chronologies
#	Journal_Name: Climate of the Past
#	Volume: 10 
#	Edition:
#	Issue:
#	Pages: 437-449
#	DOI: 10.5194/cp-10-437-2014
#	Online_Resource: www.clim-past.net/10/437/2014/
#	Full_Citation:
#	Abstract: We investigate relationships between climate and tree-ring data on a global scale using the process-based VaganovÃÂ¢ÃÂÃÂShashkin Lite (VSL) forward model of tree-ring width formation. The VSL model requires as inputs only latitude, monthly mean temperature, and monthly accumulated precipitation. Hence, this simple, process-based model enables ring-width simulation at any location where monthly climate records exist. In this study, we analyse the growth response of simulated tree rings to monthly climate conditions obtained from the CRU TS3.1 data set back to 1901. Our key aims are (a) to assess the VSL model performance by examining the relations between simulated and observed growth at 2287 globally distributed sites, (b) indentify optimal growth parameters found during the model calibration, and (c) to evaluate the potential of the VSL model as an observation operator for data-assimilation-based reconstructions of climate from tree-ring width. The assessment of the growth-onset threshold temperature of approximately 4ÃÂ¢ÃÂÃÂ6 C for most sites and species using a Bayesian estimation approach complements other studies on the lower temperature limits where plant growth may be sustained. Our results suggest that the VSL model skilfully simulates site level treering series in response to climate forcing for a wide range of environmental conditions and species. Spatial aggregation of the tree-ring chronologies to reduce non-climatic noise at the site level yielded notable improvements in the coherence between modelled and actual growth. The resulting distinct and coherent patterns of significant relationships between the aggregated and simulated series further demonstrate the VSL modelÃÂ¢ÃÂÃÂs ability to skilfully capture the climatic signal contained in tree-ring series. Finally, we propose that the VSL model can be used as an observation operator in data assimilation approaches to reconstruct past climate.
#--------------------
#	Authors: Anderson, D.M., Tardif, R., Horlick, K., Erb, M.P., Hakim, G.J., Noone, D., Perkins, W.A., and E. Steig
#	Published_Date_or_Year: 2018
#	Published_Title: Additions to the last millennium reanalysis multi-proxy database
#	Journal_Name: Data Science Journal
#	Volume:
#	Edition:
#	Issue:
#	Pages:
#	Report_Number:
#	DOI:
#	Online_Resource:
#	Full_Citation: Anderson, D.M., Tardif, R., Horlick, K., Erb, M.P., Hakim, G., J., Noone, D., Perkins, W.A., and E. Steig, submitted. Additions to the last millennium reanalysis multi-proxy database. Data Science Journal.
#	Abstract: Progress in paleoclimatology increasingly occurs via data syntheses. We describe additions to a collection prepared for use in paleoclimate state estimation, specifically the Last Millennium Reanalysis (LMR).  The 2290 additional series include 2152 tree ring chronologies and 138 other series.  They supplement the collection used previously and together form a database titled LMRdb 1.0.0. The additional data draws from lake core, ice core, coral, speleothem, and tree ring archives, using published data primarily from the NOAA Paleoclimatology archive and a set of tree ring width chronologies standardized from raw International Tree Ring Data Bank ring width series. In contrast to many previous paleo compilations, the data were not selected (screened) on the basis of their environmental correlation, multi-century length, or other attributes. The inclusion of proxies sensitive to moisture and other environmental variables expands their use in data assimilation.  A preliminary calibration using linear regression with mean annual temperature reveals characteristics of the proxy series and their relationship to temperature, as well as the noise and error characteristics of the records. The additional records are structured as individual files in the NOAA Paleoclimatology format and archived at NOAA Paleoclimatology (Anderson et al. 2018) and will continue to be improved and expanded as part of the LMR Project.  The additions represent a four-fold increase in the number of records available for assimilation, provide expanded geographic coverage, and add additional proxy variables.  Applications include data assimilation, proxy system model development, and paleoclimate reconstruction using climate field reconstruction and other methods.
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# Funding_Agency
#	Funding_Agency_Name: Swiss National Science Foundation
#	Grant:
#--------------------
#	Funding_Agency_Name: National Science Foundation
#	Grant:AGS-1304263
#	Funding_Agency_Name: National Oceanic and Atmospheric Administration
#	Grant:NA14OAR4310176
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# Site_Information
#	Site_Name: Tyn hill (Altai)
#	Location:
#	Country: Russia
#	Northernmost_Latitude: 54.23
#	Southernmost_Latitude: 54.23
#	Easternmost_Longitude: 89.58
#	Westernmost_Longitude: 89.58
#	Elevation: 650 m
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# Data_Collection
#	Collection_Name: asia_russ131wB
#	Earliest_Year: 1680
#	Most_Recent_Year: 1994
#	Time_Unit: y_ad
#	Core_Length:
#	Notes: {"database":{"database1":"LMR","database2":"Breits"}} {"climateInterpretation":{"basis":"", "climateVariable":"M", "climateVariableDetail":"air", "interpDirection":"positive", "seasonality":"[6, 7, 8]"}}{"VSLite_parameters":{"T1":"2.98157327681","T2":"13.890891288","M1":"0.0229570369282","M2":"0.571141825644"}}
#--------------------
# Species
#	Species_Name: Scots pine
#	Species_Code: PISY
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# Chronology:
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# Variables
#
# Data variables follow that are preceded by ## in columns one and two.
# Data line variables format:  Variables list, one per line, shortname-tab-longname-tab-longname components (9 components: what, material, error, units, seasonality, archive, detail, method, C or N for Character or Numeric data)
#
##age	age, , ,years AD, , , , ,N
##trsgi	tree ring standardized growth index, tree ring, ,percent relative to mean growth, , Tree Rings, , ,N
#
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# Data:
# Data lines follow (have no #)
# Data line format - tab-delimited text, variable short name as header
# Missing Values: nan
#
age	trsgi
1680	0.508
1681	1.066
1682	1.268
1683	0.589
1684	0.82
1685	0.692
1686	0.898
1687	0.923
1688	0.994
1689	0.631
1690	1.099
1691	0.872
1692	0.865
1693	0.855
1694	1.092
1695	1.236
1696	1.234
1697	1.154
1698	1.048
1699	1.364
1700	0.965
1701	1.122
1702	1.251
1703	1.127
1704	1.169
1705	0.865
1706	1.504
1707	1.29
1708	1.374
1709	1.256
1710	1.122
1711	1.229
1712	1.148
1713	1.091
1714	0.972
1715	0.269
1716	0.791
1717	0.787
1718	1.11
1719	1.239
1720	0.959
1721	0.991
1722	1.042
1723	1.202
1724	0.959
1725	1.172
1726	1.254
1727	1.356
1728	0.993
1729	0.875
1730	0.93
1731	0.578
1732	0.488
1733	0.806
1734	0.787
1735	0.585
1736	0.747
1737	0.831
1738	0.466
1739	0.889
1740	1.08
1741	1.321
1742	1.16
1743	0.707
1744	0.718
1745	0.749
1746	0.705
1747	0.852
1748	0.878
1749	0.763
1750	0.348
1751	0.454
1752	1.159
1753	0.797
1754	0.869
1755	0.777
1756	1.3
1757	0.907
1758	1.159
1759	1.039
1760	0.675
1761	1.071
1762	1.338
1763	1.435
1764	1.081
1765	0.811
1766	1.057
1767	0.303
1768	0.871
1769	0.638
1770	0.726
1771	1.109
1772	0.117
1773	1.034
1774	0.889
1775	1.152
1776	0.949
1777	1.313
1778	1.228
1779	1.182
1780	1.378
1781	1.548
1782	0.66
1783	1.542
1784	1.186
1785	1.067
1786	1.306
1787	0.713
1788	0.822
1789	0.58
1790	1.009
1791	1.317
1792	0.477
1793	1.17
1794	1.079
1795	0.996
1796	0.97
1797	0.904
1798	0.794
1799	1.13
1800	1.224
1801	0.935
1802	0.737
1803	0.787
1804	0.721
1805	0.609
1806	0.934
1807	0.616
1808	0.413
1809	1.005
1810	0.857
1811	1.037
1812	0.635
1813	0.783
1814	1.04
1815	1.046
1816	0.834
1817	0.98
1818	1.163
1819	0.986
1820	0.815
1821	1.276
1822	1.547
1823	0.976
1824	1.264
1825	1.284
1826	1.325
1827	1.441
1828	1.486
1829	1.397
1830	1.286
1831	1.049
1832	1.318
1833	1.366
1834	1.6
1835	1.412
1836	1.951
1837	1.218
1838	1.669
1839	0.545
1840	0.44
1841	0.841
1842	1.039
1843	0.801
1844	0.941
1845	1.16
1846	1.212
1847	0.587
1848	0.824
1849	0.392
1850	0.232
1851	0.761
1852	0.882
1853	0.972
1854	1.258
1855	0.83
1856	1.173
1857	1.419
1858	0.836
1859	0.744
1860	1.347
1861	1.241
1862	1.289
1863	0.475
1864	0.989
1865	1.192
1866	1.028
1867	0.638
1868	1.275
1869	1.424
1870	1.181
1871	1.642
1872	1.429
1873	1.476
1874	0.674
1875	0.92
1876	0.644
1877	0.585
1878	0.53
1879	0.68
1880	0.75
1881	0.973
1882	0.506
1883	1.04
1884	0.597
1885	0.743
1886	1.14
1887	1.099
1888	0.977
1889	1.291
1890	1.342
1891	1.09
1892	0.967
1893	0.998
1894	1.06
1895	1.557
1896	0.539
1897	0.769
1898	0.963
1899	1.237
1900	0.748
1901	0.242
1902	0.953
1903	1.094
1904	0.82
1905	0.976
1906	1.054
1907	0.721
1908	0.608
1909	0.457
1910	0.325
1911	0.514
1912	1.006
1913	0.907
1914	0.851
1915	0.705
1916	0.904
1917	0.906
1918	0.515
1919	0.719
1920	0.723
1921	0.621
1922	1.183
1923	1.044
1924	0.796
1925	1.296
1926	1.474
1927	1.935
1928	1.526
1929	1.501
1930	0.859
1931	1.154
1932	1.159
1933	1.28
1934	0.857
1935	1.267
1936	1.417
1937	1.176
1938	1.705
1939	1.378
1940	0.906
1941	1.302
1942	0.869
1943	0.788
1944	1.078
1945	0.249
1946	0.58
1947	0.915
1948	1.068
1949	0.999
1950	1.112
1951	0.698
1952	1.169
1953	1.147
1954	1.346
1955	1.234
1956	1.122
1957	0.841
1958	1.17
1959	1.147
1960	1.059
1961	0.974
1962	1.166
1963	0.842
1964	0.944
1965	0.541
1966	0.707
1967	0.511
1968	0.714
1969	0.781
1970	0.831
1971	0.924
1972	1.095
1973	1.032
1974	0.447
1975	0.533
1976	0.356
1977	0.574
1978	0.582
1979	0.585
1980	0.724
1981	0.699
1982	0.751
1983	1.131
1984	1.04
1985	1.305
1986	1.296
1987	1.07
1988	1.183
1989	1.111
1990	1.306
1991	1.299
1992	0.72
1993	1.339
1994	0.719