# northamerica_usa_ga009 - Moody Tract - 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
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# Title
#	Study_Name: northamerica_usa_ga009 - Moody Tract - 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: Moody Tract
#	Location:
#	Country: United States
#	Northernmost_Latitude: 31.93
#	Southernmost_Latitude: 31.93
#	Easternmost_Longitude: -82.32
#	Westernmost_Longitude: -82.32
#	Elevation: 24 m
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# Data_Collection
#	Collection_Name: northamerica_usa_ga009B
#	Earliest_Year: 1851
#	Most_Recent_Year: 1992
#	Time_Unit: y_ad
#	Core_Length:
#	Notes: {"sensitivity":"moisture"}{"T1":"3.92057784988"}{"T2":"18.7379125649"}{"M1":"0.0228018045245"}{"M2":"0.577437169335"}
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# Species
#	Species_Name: overcup oak
#	Species_Code: QULY
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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
1851	0.974
1852	1.323
1853	0.964
1854	0.912
1855	0.708
1856	0.662
1857	1.028
1858	1.021
1859	1.021
1860	0.783
1861	0.703
1862	1.001
1863	1.205
1864	0.656
1865	0.786
1866	0.865
1867	0.794
1868	0.824
1869	0.642
1870	0.521
1871	1.173
1872	0.586
1873	1.13
1874	1.16
1875	0.746
1876	0.553
1877	0.761
1878	0.531
1879	0.56
1880	0.668
1881	0.737
1882	1.063
1883	0.959
1884	1.273
1885	0.604
1886	1.33
1887	0.754
1888	0.804
1889	0.9
1890	0.446
1891	0.58
1892	0.78
1893	0.812
1894	0.59
1895	0.83
1896	0.295
1897	0.836
1898	0.515
1899	0.473
1900	0.676
1901	0.85
1902	0.732
1903	1.013
1904	0.503
1905	0.55
1906	0.825
1907	0.8
1908	0.886
1909	0.899
1910	0.885
1911	0.407
1912	0.936
1913	0.745
1914	0.529
1915	0.748
1916	0.517
1917	1.07
1918	0.721
1919	1.167
1920	1.45
1921	0.978
1922	1.321
1923	1.229
1924	1.235
1925	0.681
1926	0.774
1927	0.565
1928	1.54
1929	1.88
1930	0.712
1931	0.82
1932	0.676
1933	0.772
1934	0.946
1935	0.596
1936	0.826
1937	1.025
1938	1.054
1939	1.216
1940	1.039
1941	0.811
1942	0.847
1943	1.124
1944	1.135
1945	1.422
1946	1.146
1947	1.023
1948	0.959
1949	1.263
1950	0.929
1951	0.729
1952	0.755
1953	1.136
1954	0.715
1955	0.452
1956	1.104
1957	1.431
1958	1.154
1959	0.968
1960	1.108
1961	1.453
1962	1.106
1963	1.448
1964	1.195
1965	1.432
1966	1.531
1967	1.263
1968	1.351
1969	1.541
1970	1.423
1971	1.862
1972	1.078
1973	1.769
1974	1.254
1975	1.507
1976	1.314
1977	1.037
1978	1.137
1979	1.265
1980	1.019
1981	0.669
1982	0.925
1983	0.891
1984	1.128
1985	0.62
1986	0.514
1987	0.61
1988	0.77
1989	0.589
1990	0.734
1991	0.871
1992	0.664