# asia_russ123w - Kozhim - 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.
#
#
# 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/4479
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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_russ123w - Kozhim - 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 VaganovÃÂ¢ÃÂÃÂShashkin 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 4ÃÂ¢ÃÂÃÂ6 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 modelÃÂ¢ÃÂÃÂs 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
#------------------
# Site_Information
#	Site_Name: Kozhim
#	Location:
#	Country: Russia
#	Northernmost_Latitude: 65.45
#	Southernmost_Latitude: 65.45
#	Easternmost_Longitude: 60.58
#	Westernmost_Longitude: 60.58
#	Elevation: 400 m
#--------------------
# Data_Collection
#	Collection_Name: asia_russ123wB
#	Earliest_Year: 1611
#	Most_Recent_Year: 1990
#	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":"4.71006289256","T2":"16.8152962095","M1":"0.0221734640947","M2":"0.420714380837"}}
#--------------------
# Species
#	Species_Name: Siberian larch
#	Species_Code: LASI
#--------------------
# 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
1611	1.378
1612	1.516
1613	0.489
1614	1.105
1615	1.22
1616	1.427
1617	0.854
1618	1.408
1619	1.534
1620	0.963
1621	0.969
1622	1.195
1623	0.858
1624	0.941
1625	0.648
1626	0.446
1627	1.217
1628	1.206
1629	1.033
1630	0.655
1631	0.917
1632	1.011
1633	0.791
1634	0.356
1635	0.655
1636	1.396
1637	1.693
1638	0.907
1639	1.002
1640	0.37
1641	0.403
1642	0.766
1643	0.937
1644	0.703
1645	0.513
1646	0.61
1647	0.853
1648	1.223
1649	0.846
1650	1.087
1651	1.18
1652	0.787
1653	1.312
1654	1.401
1655	0.955
1656	1.531
1657	1.002
1658	1.437
1659	1.252
1660	1.043
1661	0.941
1662	1.078
1663	0.941
1664	0.746
1665	0.911
1666	0.609
1667	0.597
1668	0.778
1669	1.296
1670	1.064
1671	1.508
1672	1.624
1673	1.336
1674	1.423
1675	1.311
1676	0.9
1677	0.445
1678	1.0
1679	0.534
1680	0.958
1681	1.171
1682	1.074
1683	0.891
1684	0.731
1685	0.869
1686	0.663
1687	0.818
1688	1.108
1689	1.154
1690	1.249
1691	1.374
1692	1.484
1693	0.995
1694	0.214
1695	1.167
1696	1.379
1697	0.797
1698	0.905
1699	1.092
1700	0.929
1701	0.99
1702	1.008
1703	1.286
1704	1.561
1705	1.53
1706	1.126
1707	1.458
1708	1.506
1709	0.931
1710	1.321
1711	0.792
1712	0.752
1713	0.609
1714	0.795
1715	1.21
1716	1.25
1717	0.877
1718	0.745
1719	1.131
1720	0.905
1721	1.051
1722	0.568
1723	0.812
1724	1.247
1725	1.242
1726	1.238
1727	1.256
1728	1.338
1729	1.128
1730	0.307
1731	1.024
1732	0.562
1733	0.934
1734	0.681
1735	0.725
1736	0.71
1737	1.13
1738	1.047
1739	1.215
1740	1.024
1741	0.959
1742	0.847
1743	0.396
1744	1.098
1745	0.801
1746	0.964
1747	1.044
1748	0.565
1749	0.954
1750	0.538
1751	1.051
1752	0.41
1753	0.641
1754	1.208
1755	0.74
1756	0.413
1757	0.811
1758	1.335
1759	0.928
1760	1.135
1761	1.055
1762	1.305
1763	0.628
1764	1.132
1765	0.949
1766	0.501
1767	1.11
1768	0.895
1769	1.176
1770	0.711
1771	0.96
1772	0.216
1773	0.32
1774	1.05
1775	0.763
1776	0.718
1777	0.843
1778	1.148
1779	1.099
1780	0.602
1781	0.988
1782	1.148
1783	0.622
1784	0.467
1785	1.261
1786	0.642
1787	1.131
1788	1.205
1789	1.219
1790	1.256
1791	1.489
1792	1.38
1793	1.317
1794	1.01
1795	1.235
1796	1.647
1797	0.984
1798	0.885
1799	0.762
1800	0.881
1801	0.773
1802	0.652
1803	0.713
1804	0.834
1805	1.189
1806	0.82
1807	1.261
1808	1.393
1809	1.027
1810	0.555
1811	0.769
1812	0.951
1813	0.933
1814	0.663
1815	0.461
1816	0.271
1817	0.648
1818	0.276
1819	0.877
1820	0.804
1821	0.635
1822	0.839
1823	1.008
1824	0.884
1825	0.385
1826	0.79
1827	1.364
1828	1.337
1829	2.046
1830	1.742
1831	0.925
1832	1.295
1833	1.099
1834	0.456
1835	1.057
1836	0.523
1837	1.233
1838	0.43
1839	1.158
1840	1.113
1841	1.15
1842	1.49
1843	1.118
1844	2.0
1845	1.88
1846	1.814
1847	1.876
1848	1.894
1849	1.756
1850	2.057
1851	2.047
1852	1.469
1853	1.231
1854	1.148
1855	0.789
1856	1.549
1857	0.465
1858	0.701
1859	0.901
1860	0.946
1861	0.717
1862	0.748
1863	0.185
1864	0.972
1865	0.633
1866	0.815
1867	0.823
1868	0.816
1869	1.239
1870	1.182
1871	0.398
1872	0.754
1873	0.751
1874	0.444
1875	0.392
1876	0.416
1877	0.926
1878	0.893
1879	0.685
1880	0.739
1881	0.604
1882	0.371
1883	0.465
1884	0.937
1885	0.604
1886	0.707
1887	1.188
1888	1.052
1889	0.555
1890	1.776
1891	0.572
1892	1.104
1893	0.875
1894	0.866
1895	1.143
1896	0.612
1897	1.395
1898	1.202
1899	0.706
1900	0.88
1901	0.852
1902	0.971
1903	0.538
1904	1.01
1905	0.678
1906	0.878
1907	0.737
1908	0.475
1909	0.726
1910	0.294
1911	1.039
1912	0.516
1913	1.076
1914	0.653
1915	1.158
1916	1.041
1917	0.771
1918	1.303
1919	0.961
1920	1.073
1921	1.335
1922	1.896
1923	1.713
1924	0.366
1925	1.391
1926	1.277
1927	1.191
1928	1.195
1929	0.956
1930	0.232
1931	0.559
1932	0.215
1933	0.646
1934	0.62
1935	0.711
1936	1.015
1937	1.034
1938	1.079
1939	1.41
1940	0.837
1941	1.102
1942	1.605
1943	0.765
1944	1.015
1945	1.074
1946	0.89
1947	0.638
1948	1.091
1949	0.908
1950	0.844
1951	0.537
1952	1.748
1953	1.557
1954	1.673
1955	1.535
1956	1.806
1957	1.304
1958	1.429
1959	1.302
1960	1.136
1961	1.233
1962	0.826
1963	1.827
1964	1.617
1965	1.312
1966	1.1
1967	0.525
1968	1.352
1969	1.13
1970	0.543
1971	0.85
1972	0.477
1973	1.06
1974	1.162
1975	0.665
1976	0.91
1977	1.129
1978	1.069
1979	0.873
1980	1.147
1981	1.337
1982	1.026
1983	1.538
1984	1.435
1985	1.371
1986	0.791
1987	0.636
1988	0.94
1989	1.506
1990	1.341