# europe_swit189 - Glarus GL - 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
#--------------------
# Contribution_Date
#	Date: 2016-01-07
#--------------------
# Title
#	Study_Name: europe_swit189 - Glarus GL - 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: Glarus GL
#	Location:
#	Country: Switzerland
#	Northernmost_Latitude: 47.03
#	Southernmost_Latitude: 47.03
#	Easternmost_Longitude: 9.07
#	Westernmost_Longitude: 9.07
#	Elevation: 1500 m
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# Data_Collection
#	Collection_Name: europe_swit189B
#	Earliest_Year: 1841
#	Most_Recent_Year: 2007
#	Time_Unit: y_ad
#	Core_Length:
#	Notes: {"sensitivity":"temperature"}{"T1":"5.57222059241"}{"T2":"20.0251098004"}{"M1":"0.0221168344488"}{"M2":"0.360372149731"}
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# Species
#	Species_Name: Norway spruce
#	Species_Code: PCAB
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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
1841	0.843
1842	1.275
1843	0.79
1844	0.954
1845	0.952
1846	1.211
1847	1.025
1848	1.059
1849	1.271
1850	1.075
1851	0.997
1852	1.09
1853	0.996
1854	1.0
1855	0.935
1856	0.961
1857	1.161
1858	1.007
1859	1.0
1860	0.756
1861	0.92
1862	0.787
1863	1.076
1864	1.092
1865	1.183
1866	1.076
1867	1.287
1868	1.186
1869	1.297
1870	1.212
1871	1.131
1872	1.05
1873	1.157
1874	1.022
1875	1.055
1876	0.947
1877	0.902
1878	1.003
1879	0.98
1880	1.052
1881	1.433
1882	1.168
1883	1.039
1884	1.016
1885	1.001
1886	0.814
1887	1.071
1888	0.816
1889	1.048
1890	0.856
1891	0.734
1892	0.859
1893	0.903
1894	0.96
1895	1.023
1896	0.876
1897	0.954
1898	0.861
1899	0.916
1900	0.883
1901	1.065
1902	0.877
1903	0.889
1904	1.219
1905	1.119
1906	0.877
1907	0.888
1908	1.156
1909	0.745
1910	0.968
1911	1.153
1912	0.842
1913	0.723
1914	0.793
1915	0.88
1916	0.863
1917	1.101
1918	0.769
1919	0.866
1920	0.881
1921	1.017
1922	0.921
1923	1.174
1924	1.204
1925	1.203
1926	0.959
1927	0.991
1928	1.127
1929	0.903
1930	0.88
1931	1.004
1932	0.872
1933	0.692
1934	0.758
1935	0.888
1936	0.873
1937	0.95
1938	1.003
1939	1.019
1940	1.017
1941	1.053
1942	1.142
1943	1.243
1944	1.26
1945	1.379
1946	1.249
1947	1.357
1948	0.737
1949	1.073
1950	0.949
1951	1.083
1952	1.297
1953	1.094
1954	0.876
1955	1.013
1956	0.796
1957	0.753
1958	0.784
1959	0.84
1960	0.762
1961	0.838
1962	0.774
1963	0.887
1964	1.048
1965	0.852
1966	0.976
1967	1.073
1968	1.033
1969	1.228
1970	1.105
1971	0.96
1972	0.929
1973	1.057
1974	0.737
1975	0.767
1976	0.848
1977	0.952
1978	0.843
1979	0.957
1980	0.756
1981	0.942
1982	1.205
1983	1.221
1984	0.933
1985	1.114
1986	1.0
1987	0.787
1988	1.102
1989	1.032
1990	0.922
1991	0.894
1992	0.856
1993	0.894
1994	1.113
1995	0.948
1996	0.802
1997	0.766
1998	0.887
1999	0.955
2000	1.137
2001	1.318
2002	1.111
2003	1.109
2004	0.869
2005	1.04
2006	1.236
2007	1.089