# northamerica_usa_ok022 - Lake Arbuckle - Breitenmoser Tree Ring Chronology Data
#-----------------------------------------------------------------------
#		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/4875
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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_ok022 - Lake Arbuckle - 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: Lake Arbuckle
#	Location:
#	Country: United States
#	Northernmost_Latitude: 32.42
#	Southernmost_Latitude: 32.42
#	Easternmost_Longitude: -96.98
#	Westernmost_Longitude: -96.98
#	Elevation: 280 m
#--------------------
# Data_Collection
#	Collection_Name: northamerica_usa_ok022B
#	Earliest_Year: 1720
#	Most_Recent_Year: 1995
#	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":"4.39646968692","T2":"16.683365792","M1":"0.022985774603","M2":"0.516535885101"}}
#--------------------
# Species
#	Species_Name: post oak
#	Species_Code: QUST
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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
1720	1.052
1721	1.149
1722	0.738
1723	0.914
1724	0.65
1725	0.826
1726	0.519
1727	0.806
1728	0.597
1729	0.947
1730	0.726
1731	0.963
1732	1.254
1733	1.116
1734	1.34
1735	1.374
1736	0.606
1737	0.531
1738	0.705
1739	0.724
1740	0.862
1741	1.024
1742	0.597
1743	0.539
1744	0.579
1745	1.098
1746	1.393
1747	1.329
1748	1.394
1749	1.434
1750	1.424
1751	1.641
1752	0.939
1753	1.08
1754	1.197
1755	0.702
1756	0.912
1757	0.931
1758	1.193
1759	0.732
1760	1.242
1761	1.138
1762	1.114
1763	1.291
1764	1.289
1765	0.957
1766	1.052
1767	0.709
1768	0.608
1769	0.7
1770	0.667
1771	0.871
1772	0.401
1773	0.631
1774	0.988
1775	1.047
1776	0.893
1777	0.935
1778	0.862
1779	0.803
1780	0.991
1781	1.22
1782	1.232
1783	1.181
1784	0.938
1785	0.834
1786	0.464
1787	0.867
1788	1.182
1789	0.952
1790	1.109
1791	0.931
1792	0.913
1793	1.02
1794	0.77
1795	1.084
1796	1.261
1797	0.982
1798	0.877
1799	1.398
1800	0.896
1801	0.617
1802	0.725
1803	0.955
1804	1.067
1805	0.685
1806	0.816
1807	1.053
1808	0.763
1809	1.074
1810	1.172
1811	1.291
1812	0.99
1813	0.939
1814	1.18
1815	1.239
1816	0.975
1817	1.536
1818	1.092
1819	1.142
1820	0.938
1821	0.951
1822	0.784
1823	0.93
1824	0.646
1825	0.82
1826	1.488
1827	1.151
1828	1.068
1829	0.891
1830	0.915
1831	0.811
1832	0.847
1833	1.105
1834	1.172
1835	1.045
1836	1.731
1837	1.233
1838	0.924
1839	0.801
1840	1.154
1841	0.992
1842	0.652
1843	1.296
1844	1.276
1845	0.879
1846	0.985
1847	0.923
1848	0.956
1849	1.135
1850	1.105
1851	0.977
1852	1.031
1853	0.952
1854	1.016
1855	0.494
1856	0.795
1857	0.915
1858	1.085
1859	0.702
1860	0.782
1861	0.733
1862	0.733
1863	0.611
1864	0.545
1865	0.719
1866	0.791
1867	1.009
1868	1.015
1869	1.102
1870	1.118
1871	1.031
1872	0.938
1873	1.097
1874	0.824
1875	0.883
1876	1.042
1877	0.851
1878	0.848
1879	0.634
1880	0.616
1881	0.897
1882	0.804
1883	0.806
1884	0.826
1885	0.877
1886	0.593
1887	0.487
1888	0.956
1889	0.733
1890	0.913
1891	1.021
1892	1.031
1893	0.827
1894	0.865
1895	0.575
1896	0.742
1897	1.056
1898	1.096
1899	1.129
1900	0.985
1901	0.866
1902	0.967
1903	1.309
1904	0.943
1905	0.877
1906	1.197
1907	2.238
1908	2.283
1909	1.405
1910	1.031
1911	0.665
1912	1.132
1913	0.897
1914	1.186
1915	1.433
1916	1.34
1917	0.969
1918	0.593
1919	1.176
1920	1.288
1921	1.316
1922	0.953
1923	0.892
1924	1.135
1925	0.497
1926	0.853
1927	0.902
1928	1.219
1929	1.146
1930	0.881
1931	0.981
1932	1.023
1933	1.035
1934	0.876
1935	1.239
1936	0.903
1937	1.08
1938	0.981
1939	0.713
1940	0.942
1941	1.201
1942	1.456
1943	1.166
1944	1.194
1945	1.237
1946	1.231
1947	1.168
1948	0.94
1949	0.957
1950	0.998
1951	1.012
1952	0.798
1953	0.631
1954	0.903
1955	0.921
1956	0.585
1957	0.868
1958	1.093
1959	0.7
1960	1.036
1961	0.843
1962	0.898
1963	0.787
1964	0.763
1965	1.068
1966	0.605
1967	1.008
1968	1.13
1969	1.067
1970	0.999
1971	0.832
1972	0.766
1973	1.129
1974	0.982
1975	1.202
1976	0.949
1977	0.906
1978	0.816
1979	0.925
1980	0.683
1981	0.801
1982	1.089
1983	1.076
1984	0.839
1985	1.147
1986	0.857
1987	1.085
1988	0.884
1989	1.041
1990	1.019
1991	0.948
1992	1.225
1993	1.181
1994	1.041
1995	1.24