# asia_russ064w - Shchely Bozh - Breitenmoser Tree Ring Chronology Data
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#		World Data Center for Paleoclimatology, Boulder
#				and
#		NOAA Paleoclimatology Program
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# 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/4637
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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_russ064w - Shchely Bozh - 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: Shchely Bozh
#	Location:
#	Country: Russia
#	Northernmost_Latitude: 66.22
#	Southernmost_Latitude: 66.22
#	Easternmost_Longitude: 56.33
#	Westernmost_Longitude: 56.33
#	Elevation: 65 m
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# Data_Collection
#	Collection_Name: asia_russ064wB
#	Earliest_Year: 1671
#	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":"6.58663076226","T2":"18.4824456271","M1":"0.0224557976366","M2":"0.270245411785"}}
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# 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
#
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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
1671	1.539
1672	1.862
1673	1.282
1674	0.924
1675	1.065
1676	0.948
1677	0.838
1678	1.336
1679	0.683
1680	1.211
1681	1.215
1682	1.418
1683	1.198
1684	0.779
1685	1.61
1686	1.273
1687	1.331
1688	1.288
1689	1.011
1690	1.117
1691	0.869
1692	0.77
1693	0.684
1694	0.117
1695	0.878
1696	0.699
1697	0.297
1698	0.079
1699	0.474
1700	0.327
1701	0.389
1702	0.521
1703	0.747
1704	1.051
1705	1.297
1706	1.298
1707	1.533
1708	1.404
1709	1.017
1710	1.09
1711	0.537
1712	0.382
1713	0.412
1714	0.401
1715	0.661
1716	0.627
1717	0.617
1718	0.769
1719	0.873
1720	0.775
1721	0.892
1722	0.467
1723	0.84
1724	1.328
1725	0.895
1726	0.55
1727	0.562
1728	0.664
1729	0.436
1730	0.19
1731	0.554
1732	0.113
1733	0.539
1734	0.422
1735	0.351
1736	0.499
1737	0.573
1738	0.458
1739	0.802
1740	0.484
1741	1.127
1742	1.116
1743	0.793
1744	1.092
1745	0.794
1746	0.757
1747	0.768
1748	0.341
1749	0.903
1750	0.71
1751	1.22
1752	0.612
1753	0.838
1754	1.347
1755	1.39
1756	1.14
1757	0.485
1758	1.38
1759	0.841
1760	1.187
1761	1.466
1762	1.854
1763	1.109
1764	2.527
1765	1.889
1766	1.039
1767	2.007
1768	2.02
1769	1.557
1770	1.116
1771	1.332
1772	0.493
1773	0.315
1774	1.174
1775	0.969
1776	0.672
1777	0.564
1778	0.965
1779	1.521
1780	1.055
1781	1.14
1782	1.753
1783	0.941
1784	0.85
1785	1.264
1786	1.0
1787	1.538
1788	1.998
1789	1.511
1790	1.99
1791	2.097
1792	1.851
1793	1.751
1794	1.675
1795	1.558
1796	1.859
1797	1.337
1798	1.346
1799	1.048
1800	1.035
1801	0.706
1802	1.116
1803	1.194
1804	0.948
1805	1.062
1806	0.873
1807	1.186
1808	1.253
1809	0.843
1810	0.561
1811	0.779
1812	1.004
1813	0.827
1814	0.551
1815	0.525
1816	0.503
1817	0.41
1818	0.445
1819	0.639
1820	0.546
1821	0.833
1822	1.064
1823	1.597
1824	1.324
1825	1.026
1826	0.922
1827	1.304
1828	1.196
1829	1.412
1830	1.75
1831	0.969
1832	1.155
1833	0.992
1834	0.38
1835	0.586
1836	0.415
1837	0.581
1838	0.102
1839	0.478
1840	0.77
1841	0.573
1842	0.83
1843	0.582
1844	0.875
1845	0.762
1846	1.132
1847	1.301
1848	1.283
1849	1.111
1850	0.932
1851	0.982
1852	0.762
1853	0.657
1854	0.914
1855	0.738
1856	1.148
1857	0.428
1858	0.317
1859	0.678
1860	0.553
1861	0.636
1862	0.574
1863	0.07
1864	0.775
1865	0.655
1866	0.755
1867	0.738
1868	0.529
1869	1.184
1870	1.818
1871	0.532
1872	0.617
1873	1.154
1874	0.605
1875	0.961
1876	0.941
1877	1.212
1878	1.557
1879	1.255
1880	1.764
1881	1.489
1882	0.604
1883	0.756
1884	0.64
1885	0.249
1886	0.375
1887	0.754
1888	0.793
1889	0.387
1890	1.424
1891	0.662
1892	0.776
1893	0.747
1894	0.887
1895	0.991
1896	0.938
1897	1.308
1898	1.594
1899	0.905
1900	1.079
1901	1.235
1902	0.9
1903	0.349
1904	0.43
1905	0.272
1906	0.676
1907	0.609
1908	0.66
1909	0.741
1910	0.52
1911	1.175
1912	0.658
1913	0.83
1914	0.684
1915	1.191
1916	1.321
1917	0.844
1918	1.133
1919	0.909
1920	1.115
1921	1.357
1922	1.91
1923	1.828
1924	0.513
1925	1.293
1926	1.283
1927	0.935
1928	1.204
1929	1.265
1930	0.968
1931	1.312
1932	1.165
1933	1.235
1934	1.447
1935	1.612
1936	1.683
1937	1.455
1938	1.419
1939	1.807
1940	1.553
1941	1.505
1942	1.604
1943	1.194
1944	1.085
1945	1.201
1946	0.892
1947	0.922
1948	1.33
1949	1.129
1950	0.779
1951	0.702
1952	1.529
1953	1.676
1954	1.262
1955	0.844
1956	1.062
1957	0.791
1958	0.836
1959	0.96
1960	0.961
1961	1.14
1962	1.072
1963	1.3
1964	1.52
1965	1.365
1966	1.156
1967	0.696
1968	1.042
1969	0.895
1970	0.482
1971	0.798
1972	0.851
1973	0.712
1974	1.066
1975	0.62
1976	0.967
1977	1.159
1978	1.085
1979	0.8
1980	0.87
1981	1.143
1982	0.671
1983	1.376
1984	1.203
1985	1.006
1986	0.801
1987	0.805
1988	1.048
1989	1.104
1990	1.011