# europe_swed310 - Bettna, Soedermanland - 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
#--------------------
# Contribution_Date
#	Date: 2016-01-07
#--------------------
# Title
#	Study_Name: europe_swed310 - Bettna, Soedermanland - 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: Bettna, Soedermanland
#	Location:
#	Country: Sweden
#	Northernmost_Latitude: 58.9
#	Southernmost_Latitude: 58.9
#	Easternmost_Longitude: 16.63
#	Westernmost_Longitude: 16.63
#	Elevation: 30 m
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# Data_Collection
#	Collection_Name: europe_swed310B
#	Earliest_Year: 1858
#	Most_Recent_Year: 1997
#	Time_Unit: y_ad
#	Core_Length:
#	Notes: {"sensitivity":"moisture"}{"T1":"4.63891055811"}{"T2":"17.6994304956"}{"M1":"0.0227007497604"}{"M2":"0.457400010758"}
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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
1858	0.84
1859	0.74
1860	0.86
1861	0.907
1862	1.097
1863	1.101
1864	0.807
1865	1.163
1866	1.454
1867	1.087
1868	1.144
1869	0.822
1870	0.904
1871	0.965
1872	1.174
1873	1.026
1874	1.092
1875	0.932
1876	0.841
1877	0.931
1878	1.319
1879	0.808
1880	1.068
1881	0.684
1882	1.034
1883	0.692
1884	1.062
1885	0.766
1886	0.944
1887	0.987
1888	1.005
1889	1.131
1890	1.302
1891	1.363
1892	1.305
1893	1.263
1894	1.521
1895	1.103
1896	1.171
1897	1.241
1898	1.228
1899	0.927
1900	0.859
1901	0.85
1902	0.59
1903	0.74
1904	0.869
1905	0.918
1906	1.02
1907	0.914
1908	0.755
1909	0.771
1910	1.148
1911	1.096
1912	1.167
1913	0.999
1914	0.855
1915	1.029
1916	0.822
1917	0.64
1918	0.864
1919	1.251
1920	0.98
1921	0.973
1922	1.236
1923	1.164
1924	1.153
1925	1.237
1926	0.936
1927	1.01
1928	0.985
1929	0.911
1930	0.912
1931	0.757
1932	1.069
1933	0.817
1934	1.098
1935	1.107
1936	1.298
1937	1.056
1938	1.566
1939	2.141
1940	0.846
1941	0.793
1942	0.793
1943	1.026
1944	0.741
1945	1.441
1946	1.361
1947	0.957
1948	0.986
1949	0.947
1950	0.953
1951	1.168
1952	0.916
1953	1.034
1954	0.991
1955	0.795
1956	0.785
1957	1.106
1958	0.905
1959	0.666
1960	0.836
1961	0.719
1962	0.576
1963	0.679
1964	0.814
1965	0.748
1966	0.694
1967	0.81
1968	0.8
1969	0.473
1970	0.412
1971	0.546
1972	0.673
1973	0.832
1974	0.985
1975	1.377
1976	1.065
1977	0.968
1978	1.215
1979	1.193
1980	1.062
1981	1.18
1982	1.042
1983	0.847
1984	1.017
1985	0.706
1986	0.605
1987	0.612
1988	0.701
1989	0.546
1990	1.094
1991	1.03
1992	0.977
1993	0.96
1994	0.858
1995	1.023
1996	1.072
1997	1.403