# europe_germ056w - Sirnitz NE (D), EU-Pr. - 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
#--------------------
# Title
#	Study_Name: europe_germ056w - Sirnitz NE (D), EU-Pr. - 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: Sirnitz NE (D), EU-Pr.
#	Location:
#	Country: Germany
#	Northernmost_Latitude: 47.78
#	Southernmost_Latitude: 47.78
#	Easternmost_Longitude: 7.75
#	Westernmost_Longitude: 7.75
#	Elevation: 940 m
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# Data_Collection
#	Collection_Name: europe_germ056wB
#	Earliest_Year: 1855
#	Most_Recent_Year: 1995
#	Time_Unit: y_ad
#	Core_Length:
#	Notes: {"sensitivity":"temperature"}{"T1":"4.28387550937"}{"T2":"18.3362748449"}{"M1":"0.0223737496382"}{"M2":"0.482120488681"}
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# Species
#	Species_Name: silver fir
#	Species_Code: ABAL
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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
1855	0.913
1856	1.061
1857	0.804
1858	0.804
1859	0.756
1860	0.642
1861	0.928
1862	0.617
1863	0.682
1864	0.617
1865	0.477
1866	0.651
1867	0.649
1868	0.566
1869	0.723
1870	0.823
1871	1.01
1872	0.985
1873	1.004
1874	0.956
1875	0.777
1876	0.983
1877	1.009
1878	1.165
1879	1.219
1880	1.17
1881	1.344
1882	1.216
1883	1.223
1884	1.147
1885	1.028
1886	0.971
1887	0.996
1888	0.874
1889	1.004
1890	1.069
1891	0.992
1892	0.937
1893	0.859
1894	0.768
1895	0.983
1896	0.9
1897	1.02
1898	1.289
1899	1.23
1900	1.117
1901	1.19
1902	1.121
1903	1.185
1904	1.211
1905	1.05
1906	0.922
1907	0.816
1908	0.866
1909	0.898
1910	0.858
1911	0.92
1912	0.928
1913	1.237
1914	1.153
1915	1.005
1916	1.134
1917	0.857
1918	1.031
1919	1.072
1920	0.904
1921	0.913
1922	0.528
1923	0.677
1924	0.716
1925	1.013
1926	0.926
1927	1.038
1928	1.373
1929	1.244
1930	1.297
1931	1.301
1932	1.608
1933	1.259
1934	1.118
1935	1.088
1936	1.093
1937	1.031
1938	1.07
1939	0.896
1940	0.768
1941	1.012
1942	1.213
1943	1.333
1944	1.083
1945	0.921
1946	1.03
1947	0.889
1948	0.585
1949	0.787
1950	0.712
1951	0.994
1952	0.911
1953	0.842
1954	0.942
1955	1.369
1956	0.801
1957	1.085
1958	1.1
1959	1.376
1960	1.121
1961	1.191
1962	0.911
1963	1.013
1964	1.109
1965	0.814
1966	0.967
1967	0.918
1968	0.863
1969	1.066
1970	0.876
1971	0.932
1972	0.95
1973	0.735
1974	0.454
1975	0.438
1976	0.343
1977	0.436
1978	0.487
1979	0.514
1980	0.615
1981	0.689
1982	0.852
1983	0.8
1984	1.059
1985	1.303
1986	1.241
1987	0.769
1988	1.087
1989	1.168
1990	1.287
1991	0.99
1992	1.089
1993	0.92
1994	1.274
1995	1.227