# northamerica_usa_tn016 - Boogerman Trail Tennessee - 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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# Online_Resource: https://www.ncdc.noaa.gov/paleo/study/24611
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# Original_Source_URL:https://www.ncdc.noaa.gov/paleo/study/5385
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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
#--------------------
# Title
#	Study_Name: northamerica_usa_tn016 - Boogerman Trail Tennessee - Breitenmoser Tree Ring Chronology Data
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# 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 VaganovÃÂ¢ÃÂÃÂ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 4ÃÂ¢ÃÂÃÂ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 modelÃÂ¢ÃÂÃÂ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.
#--------------------
#	Authors: Anderson, D.M., Tardif, R., Horlick, K., Erb, M.P., Hakim, G.J., Noone, D., Perkins, W.A., and E. Steig
#	Published_Date_or_Year: 2018
#	Published_Title: Additions to the last millennium reanalysis multi-proxy database
#	Journal_Name: Data Science Journal
#	Volume:
#	Edition:
#	Issue:
#	Pages:
#	Report_Number:
#	DOI:
#	Online_Resource:
#	Full_Citation: Anderson, D.M., Tardif, R., Horlick, K., Erb, M.P., Hakim, G., J., Noone, D., Perkins, W.A., and E. Steig, submitted. Additions to the last millennium reanalysis multi-proxy database. Data Science Journal.
#	Abstract: Progress in paleoclimatology increasingly occurs via data syntheses. We describe additions to a collection prepared for use in paleoclimate state estimation, specifically the Last Millennium Reanalysis (LMR).  The 2290 additional series include 2152 tree ring chronologies and 138 other series.  They supplement the collection used previously and together form a database titled LMRdb 1.0.0. The additional data draws from lake core, ice core, coral, speleothem, and tree ring archives, using published data primarily from the NOAA Paleoclimatology archive and a set of tree ring width chronologies standardized from raw International Tree Ring Data Bank ring width series. In contrast to many previous paleo compilations, the data were not selected (screened) on the basis of their environmental correlation, multi-century length, or other attributes. The inclusion of proxies sensitive to moisture and other environmental variables expands their use in data assimilation.  A preliminary calibration using linear regression with mean annual temperature reveals characteristics of the proxy series and their relationship to temperature, as well as the noise and error characteristics of the records. The additional records are structured as individual files in the NOAA Paleoclimatology format and archived at NOAA Paleoclimatology (Anderson et al. 2018) and will continue to be improved and expanded as part of the LMR Project.  The additions represent a four-fold increase in the number of records available for assimilation, provide expanded geographic coverage, and add additional proxy variables.  Applications include data assimilation, proxy system model development, and paleoclimate reconstruction using climate field reconstruction and other methods.
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# Funding_Agency
#	Funding_Agency_Name: Swiss National Science Foundation
#	Grant:
#--------------------
#	Funding_Agency_Name: National Science Foundation
#	Grant:AGS-1304263
#	Funding_Agency_Name: National Oceanic and Atmospheric Administration
#	Grant:NA14OAR4310176
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# Site_Information
#	Site_Name: Boogerman Trail Tennessee
#	Location:
#	Country: United States
#	Northernmost_Latitude: 35.6
#	Southernmost_Latitude: 35.6
#	Easternmost_Longitude: -83.08
#	Westernmost_Longitude: -83.08
#	Elevation: 1065 m
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# Data_Collection
#	Collection_Name: northamerica_usa_tn016B
#	Earliest_Year: 1773
#	Most_Recent_Year: 1995
#	Time_Unit: y_ad
#	Core_Length:
#	Notes: {"database":{"database1":"LMR","database2":"Breits"}} {"climateInterpretation":{"basis":"", "climateVariable":"T", "climateVariableDetail":"air", "interpDirection":"positive", "seasonality":"[6, 7, 8]"}}{"VSLite_parameters":{"T1":"3.18559114417","T2":"19.0863653453","M1":"0.0224284572325","M2":"0.538104873243"}}
#--------------------
# Species
#	Species_Name: tuliptree
#	Species_Code: LITU
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# Chronology:
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# Variables
#
# 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)
#
##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
1773	1.294
1774	0.113
1775	0.983
1776	1.037
1777	0.97
1778	0.998
1779	0.743
1780	1.369
1781	0.966
1782	1.538
1783	2.28
1784	1.156
1785	0.944
1786	1.14
1787	1.291
1788	0.977
1789	1.027
1790	1.069
1791	1.184
1792	1.203
1793	1.529
1794	1.511
1795	1.281
1796	1.538
1797	0.827
1798	0.501
1799	0.699
1800	0.859
1801	0.93
1802	1.18
1803	1.14
1804	1.107
1805	1.318
1806	1.23
1807	1.066
1808	0.75
1809	0.973
1810	1.155
1811	1.087
1812	0.868
1813	0.801
1814	1.23
1815	0.9
1816	0.687
1817	0.905
1818	0.772
1819	0.711
1820	1.032
1821	0.748
1822	0.942
1823	1.152
1824	1.039
1825	1.528
1826	1.14
1827	1.515
1828	1.55
1829	1.12
1830	1.017
1831	0.966
1832	0.892
1833	0.929
1834	0.923
1835	0.932
1836	0.832
1837	0.696
1838	0.94
1839	0.553
1840	1.307
1841	0.761
1842	0.997
1843	0.989
1844	0.875
1845	1.001
1846	0.856
1847	0.901
1848	0.752
1849	0.728
1850	1.151
1851	1.119
1852	1.007
1853	1.038
1854	0.793
1855	1.086
1856	0.825
1857	0.807
1858	0.69
1859	0.649
1860	0.828
1861	0.881
1862	1.12
1863	0.832
1864	0.727
1865	0.739
1866	1.054
1867	0.876
1868	0.994
1869	0.8
1870	0.979
1871	1.008
1872	1.118
1873	0.895
1874	0.575
1875	1.1
1876	1.083
1877	0.967
1878	1.103
1879	0.644
1880	0.987
1881	1.064
1882	0.945
1883	0.792
1884	1.095
1885	0.711
1886	0.506
1887	0.784
1888	0.864
1889	1.086
1890	0.867
1891	0.901
1892	1.029
1893	0.942
1894	0.775
1895	0.898
1896	0.596
1897	1.741
1898	0.932
1899	0.821
1900	0.842
1901	1.127
1902	1.037
1903	1.405
1904	0.73
1905	0.879
1906	0.986
1907	1.076
1908	0.802
1909	1.141
1910	0.857
1911	0.815
1912	0.952
1913	1.427
1914	0.627
1915	1.189
1916	1.544
1917	1.18
1918	0.742
1919	1.212
1920	0.736
1921	0.91
1922	1.324
1923	1.612
1924	1.132
1925	0.62
1926	0.712
1927	0.92
1928	1.576
1929	1.314
1930	0.918
1931	0.86
1932	1.019
1933	1.286
1934	1.796
1935	1.523
1936	1.036
1937	1.557
1938	1.517
1939	1.443
1940	1.2
1941	1.127
1942	1.236
1943	1.325
1944	0.829
1945	0.836
1946	1.176
1947	0.832
1948	0.937
1949	1.063
1950	1.417
1951	1.258
1952	0.917
1953	1.157
1954	0.773
1955	0.887
1956	0.912
1957	1.092
1958	0.71
1959	0.798
1960	1.012
1961	0.988
1962	0.908
1963	0.688
1964	0.733
1965	0.661
1966	0.17
1967	0.624
1968	0.752
1969	0.703
1970	0.62
1971	0.772
1972	1.04
1973	1.003
1974	1.083
1975	0.78
1976	0.848
1977	0.757
1978	0.655
1979	0.699
1980	0.917
1981	0.725
1982	0.909
1983	0.766
1984	0.621
1985	0.808
1986	0.595
1987	0.752
1988	0.695
1989	1.074
1990	1.019
1991	1.081
1992	1.346
1993	1.357
1994	1.327
1995	1.784