# northamerica_usa_nc4 - Kit Springs Branch  Nantahala - 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.
#
#
# 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/2680
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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_nc4 - Kit Springs Branch  Nantahala - 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
#------------------
# Site_Information
#	Site_Name: Kit Springs Branch  Nantahala
#	Location:
#	Country: United States
#	Northernmost_Latitude: 35.28
#	Southernmost_Latitude: 35.28
#	Easternmost_Longitude: -83.93
#	Westernmost_Longitude: -83.93
#	Elevation: 1300 m
#--------------------
# Data_Collection
#	Collection_Name: northamerica_usa_nc4B
#	Earliest_Year: 1706
#	Most_Recent_Year: 1992
#	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":"3.65404430449","T2":"17.2615174498","M1":"0.0225025263132","M2":"0.517154817096"}}
#--------------------
# Species
#	Species_Name: eastern hemlock
#	Species_Code: TSCA
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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
#
#--------------------
# Data:
# Data lines follow (have no #)
# Data line format - tab-delimited text, variable short name as header
# Missing Values: nan
#
age	trsgi
1706	0.765
1707	0.774
1708	0.667
1709	0.659
1710	0.742
1711	0.829
1712	0.82
1713	0.736
1714	0.68
1715	0.723
1716	0.928
1717	0.934
1718	0.986
1719	0.959
1720	0.946
1721	0.907
1722	1.0
1723	0.941
1724	0.88
1725	1.05
1726	0.942
1727	0.865
1728	0.708
1729	0.988
1730	0.898
1731	0.891
1732	0.95
1733	0.949
1734	1.053
1735	0.949
1736	1.028
1737	1.129
1738	0.888
1739	0.937
1740	0.97
1741	0.952
1742	1.154
1743	1.068
1744	1.119
1745	1.268
1746	1.089
1747	1.23
1748	0.978
1749	1.187
1750	1.249
1751	1.159
1752	1.146
1753	1.116
1754	0.984
1755	0.903
1756	0.935
1757	0.876
1758	1.02
1759	1.146
1760	1.21
1761	1.149
1762	1.306
1763	1.067
1764	1.047
1765	1.09
1766	1.096
1767	0.944
1768	1.019
1769	1.044
1770	0.906
1771	1.112
1772	1.154
1773	1.31
1774	1.41
1775	1.116
1776	1.375
1777	1.259
1778	1.084
1779	1.014
1780	1.062
1781	0.996
1782	0.812
1783	0.9
1784	0.799
1785	0.801
1786	0.959
1787	0.929
1788	0.931
1789	0.984
1790	0.87
1791	0.725
1792	0.811
1793	0.972
1794	1.001
1795	0.933
1796	1.008
1797	0.86
1798	0.891
1799	0.856
1800	0.873
1801	0.77
1802	0.672
1803	0.812
1804	0.93
1805	0.929
1806	1.002
1807	0.926
1808	0.921
1809	0.815
1810	1.029
1811	0.973
1812	1.046
1813	0.916
1814	1.049
1815	1.11
1816	1.176
1817	1.126
1818	1.268
1819	0.813
1820	0.856
1821	0.87
1822	0.898
1823	0.956
1824	0.894
1825	0.95
1826	0.921
1827	0.965
1828	0.969
1829	1.125
1830	0.907
1831	1.04
1832	1.189
1833	1.188
1834	1.194
1835	1.133
1836	1.336
1837	1.274
1838	1.229
1839	0.945
1840	1.08
1841	1.274
1842	1.125
1843	1.128
1844	0.91
1845	0.955
1846	1.083
1847	1.198
1848	1.261
1849	1.192
1850	1.116
1851	0.971
1852	0.905
1853	1.19
1854	1.059
1855	0.777
1856	0.817
1857	0.832
1858	1.03
1859	1.077
1860	1.069
1861	0.956
1862	1.207
1863	0.999
1864	0.945
1865	0.827
1866	0.68
1867	0.792
1868	0.793
1869	0.918
1870	1.006
1871	1.124
1872	1.047
1873	0.956
1874	0.888
1875	0.868
1876	0.879
1877	0.841
1878	0.843
1879	0.849
1880	0.854
1881	1.019
1882	0.881
1883	1.118
1884	1.012
1885	0.956
1886	0.738
1887	0.771
1888	0.748
1889	0.967
1890	0.934
1891	0.651
1892	0.677
1893	0.716
1894	0.817
1895	0.71
1896	0.857
1897	1.006
1898	0.804
1899	0.827
1900	0.959
1901	0.891
1902	0.604
1903	0.846
1904	0.816
1905	0.834
1906	0.769
1907	0.567
1908	0.685
1909	0.891
1910	0.833
1911	1.04
1912	0.824
1913	1.262
1914	1.047
1915	0.985
1916	1.244
1917	1.051
1918	0.828
1919	1.092
1920	1.06
1921	1.074
1922	0.842
1923	1.281
1924	1.034
1925	0.993
1926	0.718
1927	0.932
1928	1.176
1929	1.343
1930	1.084
1931	0.881
1932	1.107
1933	1.106
1934	1.071
1935	1.046
1936	1.014
1937	0.751
1938	0.972
1939	1.096
1940	1.12
1941	1.109
1942	0.968
1943	1.251
1944	0.962
1945	1.167
1946	1.18
1947	1.327
1948	1.095
1949	1.257
1950	1.031
1951	1.17
1952	0.838
1953	0.96
1954	0.857
1955	0.825
1956	1.22
1957	1.133
1958	1.141
1959	1.082
1960	0.883
1961	1.122
1962	1.16
1963	1.084
1964	1.183
1965	0.785
1966	1.018
1967	0.684
1968	0.919
1969	0.7
1970	0.828
1971	0.755
1972	0.759
1973	1.044
1974	0.954
1975	1.175
1976	0.918
1977	0.739
1978	0.649
1979	0.737
1980	0.824
1981	0.708
1982	0.758
1983	0.857
1984	1.054
1985	1.101
1986	0.912
1987	0.892
1988	0.992
1989	0.851
1990	1.115
1991	1.38
1992	1.285