# northamerica_usa_nc003 - Grandfather Mountain - 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/2977
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# Description/Documentation lines begin with #
# Data lines have no #
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# Archive: Tree Rings
#--------------------
# Contribution_Date
#	Date: 2016-01-07
#--------------------
# Title
#	Study_Name: northamerica_usa_nc003 - Grandfather Mountain - 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 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: Grandfather Mountain
#	Location:
#	Country: United States
#	Northernmost_Latitude: 36.07
#	Southernmost_Latitude: 36.07
#	Easternmost_Longitude: -81.82
#	Westernmost_Longitude: -81.82
#	Elevation: 1800 m
#--------------------
# Data_Collection
#	Collection_Name: northamerica_usa_nc003B
#	Earliest_Year: 1726
#	Most_Recent_Year: 1983
#	Time_Unit: y_ad
#	Core_Length:
#	Notes: {"database":{"database1":"LMR","database2":"Breits"}} {"climateInterpretation":{"basis":"", "climateVariable":"M", "climateVariableDetail":"air", "interpDirection":"positive", "seasonality":"[6, 7, 8]"}}{"VSLite_parameters":{"T1":"5.09080876159","T2":"14.362409484","M1":"0.0219070389899","M2":"0.592379030058"}}
#--------------------
# Species
#	Species_Name: red spruce
#	Species_Code: PCRU
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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
1726	1.084
1727	1.236
1728	1.215
1729	1.444
1730	1.125
1731	0.831
1732	0.83
1733	1.343
1734	1.343
1735	1.088
1736	1.133
1737	1.175
1738	1.046
1739	1.102
1740	1.005
1741	0.855
1742	0.95
1743	0.691
1744	0.758
1745	1.068
1746	0.867
1747	0.847
1748	0.454
1749	0.917
1750	0.925
1751	0.981
1752	1.131
1753	1.071
1754	1.078
1755	1.247
1756	1.223
1757	1.005
1758	0.959
1759	1.184
1760	0.841
1761	0.739
1762	0.794
1763	1.009
1764	1.048
1765	1.093
1766	1.246
1767	1.235
1768	1.534
1769	0.998
1770	0.976
1771	0.785
1772	0.857
1773	0.803
1774	0.64
1775	0.397
1776	0.579
1777	1.256
1778	1.249
1779	0.584
1780	0.644
1781	0.701
1782	0.875
1783	0.933
1784	0.785
1785	0.831
1786	1.046
1787	0.796
1788	0.751
1789	0.898
1790	0.946
1791	1.043
1792	1.203
1793	1.012
1794	0.894
1795	0.79
1796	1.216
1797	0.569
1798	0.88
1799	0.643
1800	0.889
1801	1.086
1802	1.169
1803	1.021
1804	1.123
1805	0.939
1806	0.912
1807	0.691
1808	0.869
1809	0.675
1810	0.994
1811	1.266
1812	1.207
1813	1.099
1814	1.339
1815	1.574
1816	1.613
1817	1.519
1818	1.064
1819	0.929
1820	0.854
1821	0.666
1822	0.811
1823	1.51
1824	1.432
1825	1.492
1826	1.056
1827	1.442
1828	1.3
1829	1.215
1830	1.122
1831	1.062
1832	0.984
1833	1.052
1834	0.873
1835	0.92
1836	0.938
1837	0.853
1838	1.039
1839	0.897
1840	0.889
1841	0.725
1842	0.886
1843	1.203
1844	1.1
1845	1.176
1846	0.889
1847	0.963
1848	1.052
1849	1.071
1850	1.216
1851	1.533
1852	1.51
1853	1.271
1854	1.007
1855	0.937
1856	0.821
1857	1.053
1858	0.844
1859	0.862
1860	0.602
1861	0.659
1862	0.869
1863	1.126
1864	0.912
1865	1.06
1866	0.956
1867	1.269
1868	1.041
1869	0.916
1870	0.88
1871	0.853
1872	1.072
1873	0.818
1874	0.871
1875	1.155
1876	1.031
1877	0.947
1878	1.164
1879	1.026
1880	0.965
1881	1.149
1882	1.181
1883	1.036
1884	0.936
1885	0.923
1886	0.918
1887	1.138
1888	1.037
1889	1.248
1890	1.123
1891	0.732
1892	1.042
1893	0.988
1894	0.981
1895	0.847
1896	0.597
1897	1.147
1898	1.012
1899	0.989
1900	0.981
1901	0.723
1902	0.774
1903	0.975
1904	0.998
1905	1.111
1906	1.277
1907	1.057
1908	1.255
1909	1.246
1910	1.433
1911	0.708
1912	0.692
1913	0.816
1914	0.57
1915	0.3
1916	0.557
1917	0.76
1918	0.499
1919	0.629
1920	0.962
1921	0.651
1922	0.789
1923	0.973
1924	0.884
1925	0.589
1926	0.354
1927	0.594
1928	0.88
1929	1.298
1930	1.274
1931	1.576
1932	0.953
1933	0.936
1934	0.783
1935	0.806
1936	0.817
1937	0.675
1938	0.724
1939	0.7
1940	0.761
1941	0.738
1942	0.794
1943	0.558
1944	0.814
1945	0.728
1946	0.661
1947	0.991
1948	0.924
1949	0.962
1950	0.659
1951	0.666
1952	0.384
1953	0.363
1954	0.486
1955	0.748
1956	0.808
1957	0.928
1958	0.981
1959	1.225
1960	1.275
1961	1.274
1962	0.935
1963	1.405
1964	1.176
1965	1.027
1966	1.068
1967	1.014
1968	1.039
1969	0.949
1970	1.034
1971	1.108
1972	1.192
1973	1.203
1974	0.996
1975	0.949
1976	1.453
1977	1.377
1978	0.988
1979	1.008
1980	1.337
1981	0.781
1982	0.995
1983	1.032