# northamerica_usa_ia012 - White Pine Hollow Forest Preserve - Breitenmoser Tree Ring Chronology Data
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#		World Data Center for Paleoclimatology, Boulder
#				and
#		NOAA Paleoclimatology Program
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# 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: northamerica_usa_ia012 - White Pine Hollow Forest Preserve - 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: White Pine Hollow Forest Preserve
#	Location:
#	Country: United States
#	Northernmost_Latitude: 42.62
#	Southernmost_Latitude: 42.62
#	Easternmost_Longitude: -91.12
#	Westernmost_Longitude: -91.12
#	Elevation: 320 m
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# Data_Collection
#	Collection_Name: northamerica_usa_ia012B
#	Earliest_Year: 1879
#	Most_Recent_Year: 1975
#	Time_Unit: y_ad
#	Core_Length:
#	Notes: {"sensitivity":"moisture"}{"T1":"4.09746343718"}{"T2":"14.8270219959"}{"M1":"0.0224789609195"}{"M2":"0.505940953032"}
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# Species
#	Species_Name: eastern white pine
#	Species_Code: PIST
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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
1879	0.871
1880	1.115
1881	0.708
1882	0.807
1883	0.922
1884	0.864
1885	0.658
1886	0.568
1887	0.615
1888	0.841
1889	0.933
1890	0.72
1891	0.947
1892	0.886
1893	0.704
1894	0.492
1895	0.393
1896	0.884
1897	1.138
1898	1.178
1899	1.686
1900	1.109
1901	0.937
1902	1.487
1903	1.442
1904	1.166
1905	1.102
1906	1.215
1907	1.44
1908	1.645
1909	0.966
1910	0.825
1911	0.867
1912	1.247
1913	1.051
1914	1.072
1915	1.174
1916	0.718
1917	0.97
1918	1.068
1919	0.953
1920	1.096
1921	0.955
1922	1.229
1923	0.829
1924	1.422
1925	1.418
1926	1.341
1927	1.042
1928	0.997
1929	1.021
1930	0.803
1931	0.5
1932	0.703
1933	0.641
1934	0.582
1935	1.084
1936	0.638
1937	0.74
1938	1.017
1939	1.027
1940	0.728
1941	0.586
1942	0.606
1943	0.53
1944	0.832
1945	1.359
1946	1.35
1947	1.295
1948	1.039
1949	1.018
1950	1.078
1951	0.909
1952	0.673
1953	0.929
1954	0.795
1955	0.885
1956	0.678
1957	0.814
1958	0.981
1959	1.041
1960	1.023
1961	1.024
1962	1.102
1963	0.989
1964	1.054
1965	1.018
1966	0.87
1967	1.063
1968	1.436
1969	1.096
1970	0.696
1971	1.027
1972	1.04
1973	0.875
1974	1.286
1975	0.906