# northamerica_usa_mn016 - Mud River - Breitenmoser Tree Ring Chronology Data
#-----------------------------------------------------------------------
#		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_mn016 - Mud River - 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: Mud River
#	Location:
#	Country: United States
#	Northernmost_Latitude: 48.32
#	Southernmost_Latitude: 48.32
#	Easternmost_Longitude: -95.7
#	Westernmost_Longitude: -95.7
#	Elevation: 354 m
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# Data_Collection
#	Collection_Name: northamerica_usa_mn016B
#	Earliest_Year: 1814
#	Most_Recent_Year: 1983
#	Time_Unit: y_ad
#	Core_Length:
#	Notes: {"sensitivity":"moisture"}{"T1":"5.32894439417"}{"T2":"17.1013188017"}{"M1":"0.0226810779675"}{"M2":"0.470734607201"}
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# Species
#	Species_Name: burr oak
#	Species_Code: QUMA
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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
1814	1.06
1815	1.137
1816	0.778
1817	0.922
1818	0.78
1819	0.811
1820	0.828
1821	0.878
1822	0.855
1823	0.8
1824	0.759
1825	0.571
1826	0.809
1827	0.852
1828	1.075
1829	1.258
1830	0.771
1831	0.853
1832	0.974
1833	1.055
1834	0.809
1835	0.68
1836	0.631
1837	0.656
1838	0.571
1839	0.437
1840	0.624
1841	0.609
1842	0.53
1843	0.662
1844	0.554
1845	0.621
1846	0.66
1847	0.854
1848	0.858
1849	0.878
1850	1.055
1851	1.127
1852	1.167
1853	1.102
1854	1.093
1855	0.758
1856	0.645
1857	0.677
1858	0.729
1859	0.652
1860	0.831
1861	0.862
1862	0.743
1863	0.562
1864	0.46
1865	0.505
1866	0.675
1867	0.79
1868	0.733
1869	0.669
1870	0.99
1871	0.542
1872	0.997
1873	0.924
1874	0.765
1875	0.981
1876	1.113
1877	1.058
1878	1.064
1879	1.041
1880	1.059
1881	1.126
1882	0.907
1883	0.895
1884	0.763
1885	0.971
1886	0.909
1887	0.816
1888	1.018
1889	0.611
1890	0.93
1891	0.803
1892	1.057
1893	0.924
1894	0.997
1895	0.91
1896	1.115
1897	1.008
1898	0.935
1899	1.163
1900	0.67
1901	1.295
1902	1.274
1903	0.917
1904	1.03
1905	0.726
1906	0.715
1907	0.921
1908	0.903
1909	1.046
1910	0.665
1911	1.039
1912	1.248
1913	1.162
1914	1.223
1915	0.822
1916	0.985
1917	0.834
1918	0.839
1919	1.105
1920	1.063
1921	0.958
1922	1.25
1923	1.235
1924	1.062
1925	1.188
1926	0.958
1927	1.041
1928	1.144
1929	0.994
1930	0.876
1931	1.005
1932	1.093
1933	1.139
1934	0.713
1935	1.533
1936	0.977
1937	1.759
1938	1.634
1939	1.33
1940	1.496
1941	1.437
1942	1.805
1943	1.403
1944	1.373
1945	1.102
1946	0.691
1947	1.131
1948	1.137
1949	1.404
1950	1.272
1951	0.982
1952	0.694
1953	0.87
1954	0.824
1955	1.123
1956	0.985
1957	1.338
1958	1.052
1959	1.073
1960	1.003
1961	0.792
1962	1.064
1963	1.163
1964	0.797
1965	0.927
1966	0.99
1967	0.968
1968	1.016
1969	1.007
1970	0.91
1971	0.726
1972	0.849
1973	0.917
1974	0.947
1975	0.971
1976	0.844
1977	0.993
1978	0.62
1979	0.76
1980	0.652
1981	0.857
1982	0.972
1983	0.705