# northamerica_usa_co536 - Hidden Valley - Breitenmoser Tree Ring Chronology Data
#-----------------------------------------------------------------------
#		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_co536 - Hidden Valley - 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: Hidden Valley
#	Location:
#	Country: United States
#	Northernmost_Latitude: 40.4
#	Southernmost_Latitude: 40.4
#	Easternmost_Longitude: -105.63
#	Westernmost_Longitude: -105.63
#	Elevation: 2828 m
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# Data_Collection
#	Collection_Name: northamerica_usa_co536B
#	Earliest_Year: 1867
#	Most_Recent_Year: 1987
#	Time_Unit: y_ad
#	Core_Length:
#	Notes: {"sensitivity":"moisture"}{"T1":"2.99672363242"}{"T2":"13.4024806922"}{"M1":"0.023192263962"}{"M2":"0.563779273921"}
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# Species
#	Species_Name: lodgepole pine
#	Species_Code: PICO
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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
1867	0.94
1868	1.03
1869	1.116
1870	1.117
1871	0.919
1872	0.959
1873	0.907
1874	0.98
1875	0.986
1876	1.057
1877	0.852
1878	0.975
1879	0.939
1880	0.752
1881	0.828
1882	0.923
1883	0.942
1884	0.933
1885	1.195
1886	1.027
1887	1.059
1888	1.013
1889	1.031
1890	0.918
1891	1.096
1892	1.051
1893	0.751
1894	1.255
1895	1.154
1896	1.074
1897	0.985
1898	1.164
1899	1.166
1900	1.067
1901	1.106
1902	0.898
1903	0.969
1904	1.048
1905	0.839
1906	0.966
1907	1.097
1908	1.005
1909	0.891
1910	1.046
1911	0.888
1912	0.969
1913	1.001
1914	0.991
1915	1.096
1916	1.109
1917	1.129
1918	1.068
1919	0.875
1920	0.922
1921	1.066
1922	0.888
1923	0.97
1924	0.971
1925	0.914
1926	1.052
1927	0.981
1928	0.995
1929	1.011
1930	0.94
1931	0.93
1932	1.041
1933	0.807
1934	0.818
1935	0.712
1936	1.016
1937	1.032
1938	1.038
1939	0.934
1940	0.794
1941	0.887
1942	0.997
1943	1.05
1944	0.988
1945	1.208
1946	1.072
1947	1.311
1948	1.134
1949	1.294
1950	1.152
1951	0.414
1952	0.491
1953	0.759
1954	0.565
1955	0.774
1956	0.696
1957	0.841
1958	0.837
1959	0.911
1960	1.015
1961	1.076
1962	1.25
1963	1.144
1964	0.971
1965	1.013
1966	1.084
1967	1.156
1968	1.124
1969	1.299
1970	1.132
1971	1.09
1972	1.097
1973	1.032
1974	0.951
1975	1.272
1976	1.127
1977	0.752
1978	0.941
1979	1.064
1980	0.962
1981	0.853
1982	0.966
1983	0.896
1984	1.039
1985	1.2
1986	1.438
1987	1.339