# europe_spai049 - Urbion Quintenar - 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
#--------------------
# Title
#	Study_Name: europe_spai049 - Urbion Quintenar - 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: Urbion Quintenar
#	Location:
#	Country: Spain
#	Northernmost_Latitude: 42.03
#	Southernmost_Latitude: 42.03
#	Easternmost_Longitude: -3.03
#	Westernmost_Longitude: -3.03
#	Elevation: 1840 m
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# Data_Collection
#	Collection_Name: europe_spai049B
#	Earliest_Year: 1794
#	Most_Recent_Year: 1985
#	Time_Unit: y_ad
#	Core_Length:
#	Notes: {"sensitivity":"temperature"}{"T1":"6.15735598567"}{"T2":"17.1336728095"}{"M1":"0.0222887200525"}{"M2":"0.28548770843"}
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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
1794	1.119
1795	0.988
1796	1.004
1797	0.993
1798	1.215
1799	1.129
1800	0.976
1801	0.981
1802	1.03
1803	1.036
1804	0.859
1805	1.124
1806	0.722
1807	1.092
1808	0.773
1809	0.967
1810	1.011
1811	1.161
1812	1.0
1813	1.115
1814	1.329
1815	1.135
1816	0.715
1817	0.858
1818	1.051
1819	1.2
1820	0.917
1821	0.727
1822	1.075
1823	1.315
1824	1.027
1825	1.411
1826	1.144
1827	1.177
1828	1.331
1829	1.482
1830	1.258
1831	1.186
1832	0.952
1833	0.54
1834	0.866
1835	0.982
1836	0.75
1837	1.022
1838	0.966
1839	0.884
1840	0.932
1841	1.039
1842	0.935
1843	0.859
1844	0.629
1845	0.653
1846	0.603
1847	0.439
1848	0.549
1849	0.729
1850	0.716
1851	0.673
1852	0.782
1853	0.715
1854	0.657
1855	0.499
1856	0.338
1857	0.352
1858	0.35
1859	0.596
1860	0.586
1861	0.793
1862	0.754
1863	0.79
1864	1.258
1865	1.145
1866	0.963
1867	0.879
1868	1.066
1869	1.42
1870	1.201
1871	1.164
1872	0.75
1873	0.736
1874	0.858
1875	1.132
1876	1.112
1877	1.331
1878	1.682
1879	1.009
1880	1.066
1881	1.163
1882	1.157
1883	0.962
1884	1.061
1885	1.322
1886	1.094
1887	1.273
1888	1.387
1889	1.276
1890	1.075
1891	1.107
1892	1.483
1893	1.778
1894	1.144
1895	1.053
1896	0.603
1897	0.971
1898	0.96
1899	0.892
1900	0.931
1901	1.221
1902	1.18
1903	1.286
1904	1.398
1905	1.046
1906	0.884
1907	0.883
1908	0.83
1909	0.768
1910	0.86
1911	1.229
1912	0.902
1913	0.953
1914	1.179
1915	1.099
1916	0.989
1917	1.045
1918	1.131
1919	1.26
1920	1.372
1921	1.127
1922	0.848
1923	1.357
1924	1.022
1925	0.976
1926	0.941
1927	1.054
1928	1.087
1929	1.106
1930	1.003
1931	0.853
1932	1.07
1933	1.074
1934	0.698
1935	0.738
1936	0.965
1937	0.88
1938	0.646
1939	0.734
1940	0.839
1941	0.529
1942	0.513
1943	0.838
1944	1.069
1945	1.142
1946	0.78
1947	1.044
1948	1.347
1949	0.977
1950	0.506
1951	0.882
1952	1.007
1953	0.96
1954	0.619
1955	0.897
1956	0.887
1957	0.862
1958	1.228
1959	1.198
1960	1.003
1961	0.887
1962	0.51
1963	0.55
1964	0.917
1965	0.62
1966	0.613
1967	0.564
1968	0.783
1969	0.879
1970	1.086
1971	1.209
1972	0.913
1973	1.299
1974	1.172
1975	1.074
1976	1.276
1977	1.295
1978	1.261
1979	1.18
1980	1.159
1981	1.131
1982	1.048
1983	1.302
1984	1.17
1985	1.377