# northamerica_usa_ky003 - Lilley Cornett 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.
#
#
# 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/2991
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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_ky003 - Lilley Cornett 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: Lilley Cornett Tract
#	Location:
#	Country: United States
#	Northernmost_Latitude: 37.08
#	Southernmost_Latitude: 37.08
#	Easternmost_Longitude: -83.0
#	Westernmost_Longitude: -83.0
#	Elevation: 500 m
#--------------------
# Data_Collection
#	Collection_Name: northamerica_usa_ky003B
#	Earliest_Year: 1685
#	Most_Recent_Year: 1982
#	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":"4.77795989945","T2":"16.8663676039","M1":"0.0226936948959","M2":"0.597175325788"}}
#--------------------
# Species
#	Species_Name: white oak
#	Species_Code: QUAL
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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
1685	1.205
1686	1.083
1687	1.052
1688	1.043
1689	0.777
1690	0.815
1691	0.88
1692	0.997
1693	0.729
1694	1.03
1695	1.044
1696	0.862
1697	0.878
1698	0.788
1699	0.647
1700	0.642
1701	0.794
1702	0.756
1703	0.767
1704	0.853
1705	0.87
1706	1.035
1707	0.98
1708	0.678
1709	0.863
1710	0.908
1711	0.975
1712	0.873
1713	0.976
1714	0.949
1715	0.637
1716	0.697
1717	0.961
1718	0.621
1719	0.565
1720	0.667
1721	0.682
1722	1.055
1723	0.74
1724	0.694
1725	1.049
1726	0.935
1727	0.84
1728	0.849
1729	1.013
1730	0.735
1731	0.802
1732	0.609
1733	0.78
1734	0.673
1735	0.527
1736	0.309
1737	0.437
1738	0.635
1739	0.882
1740	0.908
1741	1.169
1742	1.207
1743	0.767
1744	0.98
1745	1.479
1746	0.695
1747	0.956
1748	0.503
1749	0.695
1750	0.771
1751	0.811
1752	0.765
1753	0.728
1754	1.017
1755	0.594
1756	1.215
1757	0.913
1758	1.28
1759	1.237
1760	0.764
1761	0.842
1762	0.842
1763	0.92
1764	0.858
1765	0.727
1766	0.662
1767	0.689
1768	1.449
1769	1.137
1770	1.033
1771	1.267
1772	1.069
1773	0.768
1774	0.48
1775	0.963
1776	1.06
1777	1.091
1778	1.058
1779	1.132
1780	1.426
1781	1.474
1782	1.308
1783	1.368
1784	1.163
1785	0.907
1786	1.461
1787	1.259
1788	1.322
1789	1.227
1790	1.165
1791	1.114
1792	1.139
1793	1.635
1794	1.663
1795	1.145
1796	1.401
1797	1.0
1798	1.148
1799	1.067
1800	1.544
1801	1.638
1802	0.989
1803	0.935
1804	0.893
1805	0.762
1806	0.61
1807	0.668
1808	1.035
1809	1.276
1810	0.854
1811	1.158
1812	1.035
1813	0.871
1814	1.082
1815	1.132
1816	0.774
1817	1.229
1818	1.003
1819	0.739
1820	1.214
1821	0.714
1822	0.86
1823	0.927
1824	0.911
1825	0.712
1826	0.718
1827	1.071
1828	1.077
1829	1.006
1830	1.24
1831	1.107
1832	0.821
1833	0.885
1834	0.668
1835	0.836
1836	0.888
1837	0.969
1838	0.85
1839	0.508
1840	0.964
1841	0.808
1842	0.73
1843	0.84
1844	0.885
1845	0.941
1846	1.035
1847	1.011
1848	0.894
1849	1.345
1850	1.028
1851	1.092
1852	1.288
1853	0.794
1854	1.254
1855	1.216
1856	0.915
1857	0.861
1858	0.796
1859	0.781
1860	0.933
1861	0.84
1862	0.848
1863	0.947
1864	0.953
1865	0.846
1866	0.998
1867	0.933
1868	0.877
1869	1.145
1870	0.992
1871	0.934
1872	1.181
1873	1.088
1874	0.867
1875	1.626
1876	1.033
1877	0.985
1878	0.933
1879	0.711
1880	0.803
1881	0.908
1882	1.206
1883	1.31
1884	1.288
1885	0.968
1886	1.26
1887	0.994
1888	0.654
1889	1.088
1890	0.969
1891	1.085
1892	1.313
1893	0.986
1894	0.904
1895	0.963
1896	0.942
1897	1.294
1898	1.029
1899	1.04
1900	0.661
1901	1.196
1902	1.301
1903	0.962
1904	1.127
1905	0.91
1906	0.961
1907	1.301
1908	1.095
1909	1.47
1910	1.44
1911	0.802
1912	1.16
1913	1.106
1914	0.852
1915	1.396
1916	1.145
1917	1.12
1918	0.86
1919	1.079
1920	1.04
1921	0.898
1922	1.213
1923	1.147
1924	1.273
1925	1.02
1926	0.98
1927	1.181
1928	1.357
1929	1.145
1930	0.994
1931	0.843
1932	0.957
1933	0.841
1934	0.801
1935	1.204
1936	0.747
1937	1.085
1938	1.243
1939	1.181
1940	0.928
1941	0.755
1942	0.806
1943	0.935
1944	0.836
1945	1.091
1946	1.088
1947	1.172
1948	0.852
1949	0.858
1950	1.132
1951	1.48
1952	1.126
1953	1.035
1954	0.934
1955	0.844
1956	1.094
1957	0.82
1958	1.087
1959	0.786
1960	0.9
1961	0.87
1962	1.059
1963	0.879
1964	0.852
1965	0.896
1966	0.764
1967	0.836
1968	0.74
1969	0.874
1970	0.79
1971	0.993
1972	0.746
1973	0.984
1974	1.021
1975	0.937
1976	0.848
1977	0.933
1978	0.855
1979	1.0
1980	0.816
1981	0.854
1982	0.933