# europe_finl003 - Ilomantsi Kintturinne - Breitenmoser Tree Ring Chronology Data
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#		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: europe_finl003 - Ilomantsi Kintturinne - 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 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: Ilomantsi Kintturinne
#	Location:
#	Country: Finland
#	Northernmost_Latitude: 62.98
#	Southernmost_Latitude: 62.98
#	Easternmost_Longitude: 31.3
#	Westernmost_Longitude: 31.3
#	Elevation: 207 m
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# Data_Collection
#	Collection_Name: europe_finl003B
#	Earliest_Year: 1833
#	Most_Recent_Year: 1984
#	Time_Unit: y_ad
#	Core_Length:
#	Notes: {"sensitivity":"temperature"}{"T1":"5.09228946589"}{"T2":"17.4696103002"}{"M1":"0.0226863454415"}{"M2":"0.261501306099"}
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# Species
#	Species_Name: Scots pine
#	Species_Code: PISY
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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
1833	0.858
1834	1.053
1835	0.838
1836	0.728
1837	0.812
1838	1.02
1839	1.118
1840	0.863
1841	0.848
1842	1.057
1843	0.901
1844	0.993
1845	0.9
1846	1.013
1847	0.982
1848	1.116
1849	1.068
1850	1.093
1851	1.21
1852	0.991
1853	0.971
1854	1.168
1855	1.118
1856	1.102
1857	1.017
1858	1.025
1859	0.892
1860	1.192
1861	1.193
1862	0.928
1863	1.024
1864	1.066
1865	1.142
1866	0.988
1867	0.693
1868	0.933
1869	0.915
1870	1.092
1871	0.958
1872	0.837
1873	0.881
1874	0.868
1875	0.914
1876	0.82
1877	1.031
1878	0.941
1879	0.854
1880	0.904
1881	0.827
1882	1.15
1883	0.985
1884	1.016
1885	1.182
1886	1.01
1887	1.152
1888	1.061
1889	1.023
1890	1.142
1891	1.157
1892	1.03
1893	1.008
1894	0.914
1895	0.869
1896	1.057
1897	0.843
1898	0.801
1899	0.677
1900	0.812
1901	0.717
1902	0.691
1903	0.709
1904	0.779
1905	0.729
1906	0.847
1907	0.993
1908	1.068
1909	0.895
1910	0.782
1911	0.84
1912	1.046
1913	1.0
1914	1.265
1915	1.498
1916	1.204
1917	1.127
1918	0.957
1919	0.998
1920	1.057
1921	1.177
1922	1.338
1923	1.48
1924	1.374
1925	0.943
1926	0.622
1927	1.012
1928	0.75
1929	0.937
1930	0.986
1931	0.673
1932	0.921
1933	0.873
1934	1.14
1935	0.818
1936	0.799
1937	0.86
1938	0.856
1939	0.89
1940	0.978
1941	0.989
1942	0.836
1943	0.909
1944	0.866
1945	1.199
1946	1.195
1947	1.43
1948	1.348
1949	1.04
1950	1.015
1951	1.129
1952	1.028
1953	1.137
1954	1.285
1955	0.987
1956	1.048
1957	1.081
1958	0.835
1959	0.995
1960	0.886
1961	0.76
1962	0.857
1963	0.697
1964	0.891
1965	0.65
1966	0.833
1967	1.159
1968	1.011
1969	0.904
1970	0.896
1971	0.8
1972	1.032
1973	1.244
1974	1.184
1975	1.143
1976	0.906
1977	1.12
1978	1.067
1979	1.341
1980	0.966
1981	1.015
1982	1.144
1983	1.173
1984	1.135