# asia_russ129w - Ceminsky pass (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/4373
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# Description/Documentation lines begin with #
# Data lines have no #
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# Archive: Tree Rings
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# Contribution_Date
#	Date: 2016-01-07
#--------------------
# Title
#	Study_Name: asia_russ129w - Ceminsky pass (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: Ceminsky pass (Altai)
#	Location:
#	Country: Russia
#	Northernmost_Latitude: 51.0
#	Southernmost_Latitude: 51.0
#	Easternmost_Longitude: 85.63
#	Westernmost_Longitude: 85.63
#	Elevation: 1450 m
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# Data_Collection
#	Collection_Name: asia_russ129wB
#	Earliest_Year: 1673
#	Most_Recent_Year: 1994
#	Time_Unit: y_ad
#	Core_Length:
#	Notes: {"database":{"database1":"LMR","database2":"Breits"}} {"climateInterpretation":{"basis":"", "climateVariable":"T", "climateVariableDetail":"air", "interpDirection":"positive", "seasonality":"[6, 7, 8]"}}{"VSLite_parameters":{"T1":"5.60101747044","T2":"18.9559146419","M1":"0.0222499745689","M2":"0.311829483088"}}
#--------------------
# Species
#	Species_Name: Siberian larch
#	Species_Code: LASI
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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
#
#--------------------
# Data:
# Data lines follow (have no #)
# Data line format - tab-delimited text, variable short name as header
# Missing Values: nan
#
age	trsgi
1673	0.891
1674	0.987
1675	0.907
1676	1.025
1677	0.855
1678	0.92
1679	0.872
1680	0.842
1681	0.973
1682	0.862
1683	0.799
1684	1.006
1685	0.828
1686	1.024
1687	0.865
1688	0.864
1689	1.008
1690	1.005
1691	0.889
1692	0.812
1693	1.213
1694	0.977
1695	1.138
1696	0.983
1697	1.035
1698	0.823
1699	0.834
1700	0.938
1701	0.892
1702	0.978
1703	1.148
1704	1.004
1705	0.867
1706	0.702
1707	0.913
1708	1.081
1709	1.222
1710	0.892
1711	1.098
1712	0.588
1713	0.338
1714	0.783
1715	0.957
1716	1.186
1717	1.064
1718	0.876
1719	1.092
1720	1.166
1721	1.177
1722	1.211
1723	0.992
1724	0.893
1725	0.913
1726	0.949
1727	0.922
1728	0.967
1729	1.021
1730	0.972
1731	1.043
1732	0.907
1733	1.013
1734	1.129
1735	0.779
1736	0.788
1737	0.964
1738	0.922
1739	1.041
1740	1.088
1741	0.84
1742	1.026
1743	0.898
1744	0.853
1745	0.717
1746	0.76
1747	1.023
1748	1.111
1749	1.3
1750	0.974
1751	1.049
1752	0.895
1753	1.014
1754	0.983
1755	0.818
1756	0.974
1757	1.223
1758	0.924
1759	1.209
1760	1.027
1761	1.239
1762	1.104
1763	1.308
1764	1.162
1765	0.972
1766	0.901
1767	1.045
1768	0.921
1769	0.97
1770	1.146
1771	1.24
1772	1.294
1773	1.263
1774	1.004
1775	1.065
1776	1.102
1777	1.274
1778	0.847
1779	0.856
1780	0.942
1781	1.376
1782	1.376
1783	1.072
1784	1.169
1785	1.235
1786	1.283
1787	1.472
1788	0.978
1789	1.066
1790	1.254
1791	1.273
1792	1.151
1793	1.216
1794	1.071
1795	0.808
1796	0.854
1797	0.862
1798	1.028
1799	0.906
1800	1.048
1801	0.887
1802	0.883
1803	1.076
1804	1.099
1805	1.098
1806	1.177
1807	1.214
1808	1.183
1809	1.275
1810	1.173
1811	1.191
1812	0.946
1813	0.988
1814	0.788
1815	0.844
1816	0.882
1817	0.922
1818	0.842
1819	0.763
1820	0.742
1821	0.855
1822	0.921
1823	0.853
1824	0.842
1825	1.026
1826	0.818
1827	0.787
1828	0.732
1829	0.981
1830	1.24
1831	1.286
1832	1.234
1833	1.122
1834	1.048
1835	0.651
1836	0.781
1837	0.862
1838	1.048
1839	0.883
1840	0.835
1841	0.998
1842	0.76
1843	0.69
1844	0.682
1845	0.699
1846	1.135
1847	0.968
1848	1.085
1849	0.75
1850	0.418
1851	0.749
1852	0.611
1853	0.915
1854	0.489
1855	0.589
1856	0.927
1857	1.01
1858	0.85
1859	0.904
1860	1.007
1861	1.039
1862	1.241
1863	1.133
1864	0.975
1865	0.814
1866	0.846
1867	0.965
1868	0.97
1869	0.783
1870	0.785
1871	0.663
1872	0.768
1873	0.621
1874	0.616
1875	0.675
1876	0.891
1877	0.895
1878	0.953
1879	0.99
1880	1.017
1881	0.856
1882	0.983
1883	0.998
1884	0.91
1885	0.955
1886	1.2
1887	1.111
1888	1.142
1889	1.11
1890	0.83
1891	0.824
1892	0.868
1893	0.959
1894	1.015
1895	1.012
1896	1.116
1897	1.155
1898	0.938
1899	1.119
1900	1.095
1901	1.256
1902	1.223
1903	1.098
1904	1.072
1905	1.311
1906	1.189
1907	1.221
1908	1.578
1909	1.582
1910	1.207
1911	1.086
1912	1.135
1913	1.109
1914	1.136
1915	1.072
1916	1.227
1917	0.887
1918	1.028
1919	1.015
1920	1.087
1921	1.269
1922	1.299
1923	1.417
1924	1.422
1925	1.376
1926	1.142
1927	1.143
1928	1.373
1929	1.285
1930	1.052
1931	0.909
1932	1.118
1933	1.077
1934	0.949
1935	1.009
1936	1.154
1937	1.235
1938	1.02
1939	1.178
1940	0.871
1941	1.078
1942	1.142
1943	0.783
1944	1.008
1945	0.976
1946	0.992
1947	0.844
1948	1.156
1949	1.074
1950	1.106
1951	1.035
1952	1.275
1953	1.338
1954	1.397
1955	1.218
1956	1.004
1957	1.124
1958	0.814
1959	0.884
1960	0.877
1961	0.728
1962	1.027
1963	1.208
1964	1.219
1965	1.145
1966	1.047
1967	0.939
1968	0.734
1969	0.838
1970	0.859
1971	0.887
1972	0.799
1973	0.624
1974	0.766
1975	0.812
1976	1.152
1977	1.05
1978	1.067
1979	1.06
1980	0.957
1981	0.755
1982	0.733
1983	0.804
1984	0.73
1985	0.321
1986	0.355
1987	0.589
1988	0.564
1989	0.886
1990	0.898
1991	0.874
1992	0.613
1993	0.421
1994	0.572