# asia_russ117w - Krasnovishersk - 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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# Original_Source_URL:
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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
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# Title
#	Study_Name: asia_russ117w - Krasnovishersk - Breitenmoser Tree Ring Chronology Data
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# Investigators
#	Investigators:  Breitenmoser, P.; Bronnimann, S.; Frank, D.
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# 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 Vaganov–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 4–6 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 model’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.
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# Funding_Agency
#	Funding_Agency_Name: Swiss National Science Foundation
#	Grant:
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# Site_Information
#	Site_Name: Krasnovishersk
#	Location:
#	Country: Russia
#	Northernmost_Latitude: 60.38
#	Southernmost_Latitude: 60.38
#	Easternmost_Longitude: 57.12
#	Westernmost_Longitude: 57.12
#	Elevation: 140 m
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# Data_Collection
#	Collection_Name: asia_russ117wB
#	Earliest_Year: 1790
#	Most_Recent_Year: 1991
#	Time_Unit: y_ad
#	Core_Length:
#	Notes: {"sensitivity":"temperature"}{"T1":"7.11587828747"}{"T2":"15.4156817692"}{"M1":"0.0225613008748"}{"M2":"0.202938522583"}
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# Species
#	Species_Name: Siberian larch
#	Species_Code: LASI
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# Chronology:
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# Variables
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# 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)
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##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
1790	1.621
1791	1.248
1792	2.136
1793	2.362
1794	2.021
1795	2.066
1796	1.867
1797	1.579
1798	1.094
1799	0.956
1800	0.747
1801	0.85
1802	0.552
1803	0.805
1804	1.139
1805	1.297
1806	1.327
1807	0.667
1808	0.66
1809	0.694
1810	0.712
1811	0.678
1812	0.781
1813	0.962
1814	0.98
1815	0.928
1816	1.096
1817	1.153
1818	1.278
1819	1.328
1820	1.233
1821	1.405
1822	1.303
1823	1.186
1824	1.13
1825	1.064
1826	1.029
1827	1.078
1828	1.227
1829	1.166
1830	1.177
1831	0.965
1832	0.99
1833	0.984
1834	0.998
1835	0.909
1836	0.79
1837	0.97
1838	1.143
1839	1.081
1840	1.214
1841	0.93
1842	0.813
1843	0.68
1844	0.92
1845	0.864
1846	0.874
1847	0.885
1848	0.76
1849	0.459
1850	0.606
1851	0.375
1852	0.545
1853	0.553
1854	0.828
1855	0.854
1856	1.244
1857	0.802
1858	1.111
1859	1.237
1860	1.286
1861	1.163
1862	0.835
1863	1.067
1864	1.463
1865	1.403
1866	1.174
1867	1.141
1868	1.223
1869	1.17
1870	0.977
1871	0.831
1872	0.962
1873	0.934
1874	0.855
1875	0.898
1876	0.877
1877	0.857
1878	1.198
1879	0.967
1880	1.236
1881	0.727
1882	0.847
1883	0.842
1884	0.955
1885	0.859
1886	1.015
1887	0.933
1888	1.279
1889	0.63
1890	0.904
1891	0.623
1892	0.772
1893	1.065
1894	1.262
1895	1.079
1896	0.789
1897	1.104
1898	1.223
1899	0.952
1900	1.184
1901	1.088
1902	1.143
1903	0.896
1904	0.948
1905	0.797
1906	1.147
1907	1.022
1908	0.734
1909	1.064
1910	0.785
1911	0.909
1912	0.742
1913	0.875
1914	0.251
1915	0.693
1916	0.554
1917	0.485
1918	0.731
1919	0.779
1920	0.979
1921	1.159
1922	1.136
1923	0.845
1924	0.563
1925	0.502
1926	0.604
1927	0.734
1928	0.755
1929	0.873
1930	0.893
1931	0.85
1932	0.653
1933	0.68
1934	0.641
1935	0.494
1936	0.927
1937	1.369
1938	1.907
1939	2.238
1940	1.456
1941	1.331
1942	1.93
1943	2.06
1944	1.983
1945	1.932
1946	1.259
1947	1.167
1948	1.75
1949	1.199
1950	1.666
1951	1.344
1952	1.408
1953	1.379
1954	1.168
1955	0.92
1956	1.374
1957	1.255
1958	1.087
1959	0.985
1960	0.898
1961	0.632
1962	0.844
1963	0.733
1964	0.809
1965	0.624
1966	0.63
1967	0.772
1968	1.173
1969	0.621
1970	0.66
1971	0.816
1972	0.769
1973	0.587
1974	0.732
1975	0.491
1976	0.759
1977	0.801
1978	0.643
1979	0.794
1980	0.679
1981	0.582
1982	0.478
1983	0.414
1984	0.757
1985	0.601
1986	0.669
1987	0.867
1988	0.744
1989	0.758
1990	0.822
1991	0.912