# northamerica_usa_nc006 - Kelsey Tract - 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/2988
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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_nc006 - Kelsey 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 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: Kelsey Tract
#	Location:
#	Country: United States
#	Northernmost_Latitude: 35.08
#	Southernmost_Latitude: 35.08
#	Easternmost_Longitude: -83.18
#	Westernmost_Longitude: -83.18
#	Elevation: 1000 m
#--------------------
# Data_Collection
#	Collection_Name: northamerica_usa_nc006B
#	Earliest_Year: 1704
#	Most_Recent_Year: 1983
#	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":"4.95769596262","T2":"15.1853301483","M1":"0.0224572130031","M2":"0.594464034435"}}
#--------------------
# Species
#	Species_Name: Carolina hemlock
#	Species_Code: TSCR
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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
1704	0.84
1705	0.802
1706	0.65
1707	0.762
1708	0.567
1709	0.659
1710	0.886
1711	1.054
1712	1.167
1713	0.91
1714	0.829
1715	0.575
1716	0.984
1717	1.063
1718	0.872
1719	1.163
1720	1.068
1721	1.114
1722	0.989
1723	1.053
1724	0.988
1725	0.747
1726	0.904
1727	0.786
1728	0.935
1729	1.079
1730	0.989
1731	1.033
1732	0.703
1733	1.075
1734	1.332
1735	1.122
1736	1.333
1737	1.185
1738	1.053
1739	1.08
1740	0.972
1741	1.095
1742	1.152
1743	1.0
1744	0.856
1745	0.859
1746	0.853
1747	0.917
1748	0.765
1749	0.984
1750	0.974
1751	0.97
1752	1.042
1753	0.992
1754	0.839
1755	0.866
1756	0.9
1757	0.784
1758	0.865
1759	1.067
1760	0.686
1761	1.21
1762	0.937
1763	1.103
1764	0.897
1765	1.025
1766	1.316
1767	1.266
1768	1.383
1769	1.337
1770	1.166
1771	1.083
1772	0.817
1773	1.127
1774	1.015
1775	1.039
1776	1.028
1777	1.103
1778	1.117
1779	0.895
1780	0.946
1781	1.007
1782	0.702
1783	1.046
1784	0.967
1785	0.959
1786	1.08
1787	0.877
1788	1.005
1789	0.781
1790	0.777
1791	0.886
1792	1.103
1793	1.101
1794	1.177
1795	1.079
1796	1.022
1797	0.806
1798	1.041
1799	0.855
1800	0.931
1801	0.745
1802	0.744
1803	0.868
1804	1.244
1805	1.147
1806	1.106
1807	1.365
1808	1.157
1809	1.086
1810	0.927
1811	0.968
1812	0.977
1813	0.996
1814	1.313
1815	1.278
1816	1.351
1817	1.55
1818	0.949
1819	0.756
1820	0.681
1821	0.533
1822	0.754
1823	1.049
1824	0.96
1825	1.055
1826	0.873
1827	0.955
1828	0.917
1829	1.061
1830	0.857
1831	1.013
1832	0.851
1833	1.115
1834	1.089
1835	1.095
1836	1.001
1837	0.879
1838	1.005
1839	0.874
1840	0.859
1841	0.958
1842	1.127
1843	0.994
1844	1.139
1845	0.962
1846	1.167
1847	1.093
1848	1.081
1849	1.19
1850	1.246
1851	1.197
1852	1.241
1853	1.228
1854	1.535
1855	1.243
1856	1.06
1857	1.314
1858	1.136
1859	1.067
1860	1.022
1861	1.21
1862	1.1
1863	1.247
1864	1.152
1865	1.121
1866	1.073
1867	1.047
1868	0.829
1869	0.922
1870	1.154
1871	0.792
1872	1.17
1873	0.996
1874	0.884
1875	0.805
1876	0.542
1877	0.615
1878	0.731
1879	0.777
1880	0.758
1881	0.757
1882	0.915
1883	0.593
1884	0.83
1885	0.822
1886	0.698
1887	0.67
1888	0.821
1889	0.78
1890	0.699
1891	0.593
1892	0.557
1893	0.632
1894	0.758
1895	0.489
1896	0.545
1897	0.734
1898	0.622
1899	0.685
1900	0.797
1901	0.946
1902	0.883
1903	1.094
1904	1.113
1905	1.162
1906	1.117
1907	1.011
1908	1.24
1909	1.072
1910	0.983
1911	0.868
1912	0.717
1913	0.675
1914	0.568
1915	0.731
1916	0.638
1917	0.612
1918	0.684
1919	0.922
1920	1.121
1921	1.037
1922	0.906
1923	0.817
1924	0.671
1925	0.712
1926	0.399
1927	0.668
1928	0.666
1929	0.869
1930	0.861
1931	0.997
1932	0.718
1933	0.545
1934	0.674
1935	0.863
1936	0.614
1937	0.678
1938	0.599
1939	0.676
1940	0.867
1941	0.765
1942	0.851
1943	0.803
1944	0.806
1945	0.913
1946	1.066
1947	1.039
1948	1.309
1949	1.449
1950	1.338
1951	1.127
1952	1.237
1953	1.058
1954	0.841
1955	1.134
1956	1.048
1957	1.291
1958	1.371
1959	1.516
1960	1.107
1961	1.216
1962	1.306
1963	1.317
1964	0.786
1965	0.736
1966	0.783
1967	0.971
1968	1.097
1969	0.997
1970	0.99
1971	1.253
1972	1.3
1973	1.422
1974	1.491
1975	1.382
1976	1.614
1977	1.372
1978	1.011
1979	1.066
1980	1.228
1981	0.978
1982	1.006
1983	1.203