# northamerica_usa_ar009 - Russellville - 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/4990
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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_ar009 - Russellville - 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: Russellville
#	Location:
#	Country: United States
#	Northernmost_Latitude: 35.65
#	Southernmost_Latitude: 35.65
#	Easternmost_Longitude: -93.07
#	Westernmost_Longitude: -93.07
#	Elevation: 564 m
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# Data_Collection
#	Collection_Name: northamerica_usa_ar009B
#	Earliest_Year: 1761
#	Most_Recent_Year: 1972
#	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":"4.79273915812","T2":"16.4442529943","M1":"0.0220188527913","M2":"0.536379824648"}}
#--------------------
# 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
1761	1.165
1762	0.92
1763	1.328
1764	1.073
1765	1.227
1766	0.969
1767	0.601
1768	1.013
1769	1.128
1770	1.176
1771	1.05
1772	0.753
1773	1.134
1774	0.986
1775	1.273
1776	1.423
1777	1.218
1778	0.902
1779	1.238
1780	1.221
1781	1.527
1782	1.232
1783	1.356
1784	1.071
1785	0.99
1786	1.071
1787	1.463
1788	1.393
1789	1.202
1790	1.465
1791	1.257
1792	0.87
1793	1.129
1794	0.991
1795	1.109
1796	1.332
1797	1.321
1798	1.103
1799	0.784
1800	0.722
1801	0.628
1802	0.987
1803	0.802
1804	0.967
1805	1.346
1806	1.243
1807	0.898
1808	0.851
1809	0.936
1810	1.156
1811	1.15
1812	0.781
1813	0.772
1814	0.883
1815	0.843
1816	0.719
1817	0.79
1818	1.003
1819	0.781
1820	0.749
1821	0.72
1822	0.878
1823	1.036
1824	0.778
1825	0.849
1826	1.03
1827	0.884
1828	0.936
1829	0.848
1830	0.894
1831	0.77
1832	0.83
1833	0.969
1834	0.854
1835	0.907
1836	1.022
1837	1.06
1838	0.773
1839	0.649
1840	0.871
1841	0.641
1842	0.95
1843	0.934
1844	1.058
1845	0.938
1846	0.976
1847	0.868
1848	0.857
1849	0.791
1850	0.689
1851	0.753
1852	0.784
1853	0.782
1854	0.833
1855	0.582
1856	0.694
1857	0.898
1858	0.86
1859	0.658
1860	0.708
1861	0.773
1862	0.62
1863	0.61
1864	0.653
1865	0.669
1866	0.79
1867	0.881
1868	0.654
1869	0.885
1870	0.988
1871	0.792
1872	0.838
1873	0.839
1874	0.605
1875	0.644
1876	0.903
1877	0.843
1878	0.923
1879	0.699
1880	0.799
1881	0.83
1882	1.009
1883	1.055
1884	0.828
1885	0.764
1886	0.81
1887	0.948
1888	0.956
1889	1.08
1890	1.136
1891	1.137
1892	1.247
1893	1.259
1894	0.906
1895	1.01
1896	0.661
1897	0.69
1898	0.768
1899	0.967
1900	0.732
1901	0.761
1902	0.751
1903	1.065
1904	1.101
1905	1.25
1906	1.432
1907	1.143
1908	1.198
1909	1.431
1910	1.239
1911	0.766
1912	1.145
1913	0.887
1914	0.936
1915	1.375
1916	1.226
1917	1.285
1918	1.0
1919	1.107
1920	1.455
1921	1.163
1922	1.346
1923	1.643
1924	1.783
1925	0.845
1926	0.96
1927	1.367
1928	1.417
1929	1.35
1930	1.092
1931	1.232
1932	1.134
1933	0.968
1934	0.965
1935	1.469
1936	1.075
1937	1.255
1938	1.484
1939	1.047
1940	1.054
1941	0.911
1942	1.019
1943	0.947
1944	0.839
1945	1.296
1946	1.312
1947	1.163
1948	1.081
1949	1.167
1950	1.083
1951	1.178
1952	0.842
1953	0.742
1954	0.727
1955	0.912
1956	0.758
1957	0.85
1958	0.8
1959	0.921
1960	0.818
1961	0.778
1962	0.776
1963	0.797
1964	0.795
1965	0.913
1966	0.805
1967	0.845
1968	0.784
1969	0.669
1970	0.71
1971	0.755
1972	0.6