# northamerica_usa_nc004 - Joyce Kilmer Wilderness - 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/2986
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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_nc004 - Joyce Kilmer Wilderness - 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: Joyce Kilmer Wilderness
#	Location:
#	Country: United States
#	Northernmost_Latitude: 35.22
#	Southernmost_Latitude: 35.22
#	Easternmost_Longitude: -83.97
#	Westernmost_Longitude: -83.97
#	Elevation: 1000 m
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# Data_Collection
#	Collection_Name: northamerica_usa_nc004B
#	Earliest_Year: 1692
#	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":"4.96697486376","T2":"16.7758417144","M1":"0.0220752152908","M2":"0.527924692906"}}
#--------------------
# 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
#
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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
1692	1.349
1693	1.053
1694	1.364
1695	1.081
1696	1.078
1697	0.944
1698	1.03
1699	0.517
1700	0.679
1701	0.893
1702	0.865
1703	0.87
1704	0.969
1705	0.858
1706	0.923
1707	1.118
1708	0.775
1709	0.976
1710	1.103
1711	1.187
1712	1.208
1713	0.836
1714	0.826
1715	0.765
1716	0.811
1717	0.99
1718	0.775
1719	0.897
1720	0.84
1721	1.082
1722	0.968
1723	0.89
1724	1.026
1725	0.975
1726	0.869
1727	0.834
1728	1.014
1729	0.96
1730	0.856
1731	0.95
1732	1.033
1733	1.15
1734	1.089
1735	0.913
1736	0.819
1737	0.991
1738	0.896
1739	1.225
1740	0.899
1741	1.047
1742	0.886
1743	0.677
1744	0.808
1745	0.871
1746	0.77
1747	0.849
1748	0.722
1749	0.807
1750	1.024
1751	0.82
1752	0.676
1753	0.75
1754	0.818
1755	0.728
1756	0.788
1757	0.938
1758	1.022
1759	0.811
1760	0.824
1761	0.995
1762	0.634
1763	0.452
1764	0.564
1765	0.704
1766	0.856
1767	0.932
1768	1.001
1769	1.099
1770	0.893
1771	1.067
1772	0.784
1773	0.87
1774	0.748
1775	0.674
1776	1.046
1777	0.859
1778	0.842
1779	1.17
1780	1.196
1781	0.979
1782	0.987
1783	0.938
1784	0.732
1785	0.855
1786	1.224
1787	1.067
1788	1.165
1789	1.032
1790	1.093
1791	0.959
1792	0.838
1793	1.282
1794	1.442
1795	1.03
1796	1.078
1797	1.01
1798	1.096
1799	0.801
1800	1.193
1801	0.93
1802	1.052
1803	1.161
1804	1.315
1805	1.224
1806	1.209
1807	1.11
1808	1.045
1809	0.996
1810	1.353
1811	1.204
1812	1.207
1813	1.269
1814	1.214
1815	1.127
1816	1.187
1817	1.122
1818	1.284
1819	0.936
1820	0.938
1821	0.942
1822	1.157
1823	1.285
1824	1.373
1825	1.278
1826	1.218
1827	1.155
1828	1.017
1829	1.213
1830	1.025
1831	1.255
1832	1.218
1833	1.303
1834	1.155
1835	1.189
1836	1.139
1837	0.815
1838	0.829
1839	0.824
1840	1.073
1841	0.978
1842	1.035
1843	1.036
1844	0.956
1845	1.039
1846	1.125
1847	1.143
1848	1.367
1849	1.262
1850	1.29
1851	1.273
1852	1.198
1853	1.06
1854	1.254
1855	1.145
1856	1.014
1857	1.023
1858	0.907
1859	0.938
1860	1.016
1861	0.883
1862	0.994
1863	1.047
1864	0.743
1865	0.772
1866	0.872
1867	0.873
1868	0.865
1869	0.955
1870	0.982
1871	0.993
1872	0.938
1873	1.008
1874	0.95
1875	1.264
1876	1.085
1877	0.961
1878	1.084
1879	0.916
1880	1.088
1881	0.951
1882	1.049
1883	0.851
1884	0.921
1885	1.011
1886	1.071
1887	0.924
1888	0.869
1889	0.768
1890	0.803
1891	0.92
1892	1.045
1893	0.982
1894	0.769
1895	0.892
1896	0.837
1897	0.92
1898	0.853
1899	0.888
1900	0.812
1901	0.85
1902	0.941
1903	1.153
1904	1.121
1905	1.107
1906	1.18
1907	1.215
1908	1.027
1909	1.081
1910	0.997
1911	0.81
1912	1.086
1913	1.023
1914	0.837
1915	0.929
1916	0.995
1917	0.851
1918	1.012
1919	0.962
1920	1.07
1921	1.039
1922	1.109
1923	1.053
1924	0.92
1925	0.715
1926	0.744
1927	0.816
1928	0.987
1929	0.798
1930	0.76
1931	0.705
1932	1.012
1933	0.768
1934	1.019
1935	1.115
1936	0.902
1937	1.172
1938	1.295
1939	1.198
1940	1.135
1941	1.009
1942	1.051
1943	1.081
1944	0.979
1945	1.139
1946	1.183
1947	1.095
1948	0.946
1949	1.048
1950	1.058
1951	1.124
1952	0.978
1953	1.01
1954	0.906
1955	0.897
1956	0.835
1957	0.986
1958	0.929
1959	0.983
1960	0.936
1961	0.858
1962	0.99
1963	0.951
1964	0.964
1965	0.93
1966	0.906
1967	0.874
1968	1.155
1969	0.962
1970	1.203
1971	1.046
1972	0.945
1973	1.02
1974	0.694
1975	0.815
1976	0.786
1977	0.701
1978	0.761
1979	0.758
1980	0.757
1981	0.679
1982	0.834
1983	0.779