# northamerica_usa_ok - Arbuckle Mountains - 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/3463
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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_ok - Arbuckle Mountains - 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 VaganovÃÂ¢ÃÂÃÂShashkin 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 4ÃÂ¢ÃÂÃÂ6 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 modelÃÂ¢ÃÂÃÂs 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.
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#	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: Arbuckle Mountains
#	Location:
#	Country: United States
#	Northernmost_Latitude: 34.45
#	Southernmost_Latitude: 34.45
#	Easternmost_Longitude: -97.03
#	Westernmost_Longitude: -97.03
#	Elevation: 900 m
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# Data_Collection
#	Collection_Name: northamerica_usa_okB
#	Earliest_Year: 1767
#	Most_Recent_Year: 1973
#	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":"4.17513603535","T2":"17.2693971697","M1":"0.0229044161877","M2":"0.47642718064"}}
#--------------------
# 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
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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
1767	0.74
1768	0.704
1769	0.893
1770	0.655
1771	0.836
1772	0.286
1773	0.605
1774	0.944
1775	0.891
1776	1.079
1777	0.98
1778	0.94
1779	0.636
1780	0.868
1781	1.306
1782	1.156
1783	1.193
1784	0.836
1785	0.721
1786	0.418
1787	0.855
1788	1.099
1789	0.883
1790	0.854
1791	0.754
1792	0.672
1793	1.035
1794	0.824
1795	0.954
1796	1.074
1797	0.799
1798	0.761
1799	1.29
1800	0.808
1801	0.529
1802	1.063
1803	1.595
1804	1.284
1805	0.852
1806	0.82
1807	1.322
1808	0.766
1809	1.421
1810	1.262
1811	1.355
1812	1.009
1813	1.12
1814	0.992
1815	1.369
1816	0.931
1817	1.868
1818	1.369
1819	1.288
1820	1.02
1821	1.087
1822	0.878
1823	1.089
1824	0.722
1825	1.258
1826	1.631
1827	1.346
1828	1.064
1829	0.911
1830	1.07
1831	0.961
1832	0.886
1833	1.374
1834	0.976
1835	1.033
1836	1.702
1837	1.276
1838	1.148
1839	0.958
1840	1.188
1841	0.977
1842	0.761
1843	1.23
1844	1.261
1845	0.977
1846	1.164
1847	1.078
1848	1.027
1849	1.048
1850	0.968
1851	1.011
1852	1.022
1853	1.089
1854	1.262
1855	0.433
1856	0.811
1857	0.841
1858	1.002
1859	0.732
1860	0.85
1861	0.692
1862	0.692
1863	0.62
1864	0.624
1865	0.85
1866	0.916
1867	0.936
1868	0.932
1869	1.096
1870	1.098
1871	1.0
1872	0.9
1873	1.49
1874	0.808
1875	1.031
1876	1.29
1877	1.068
1878	0.911
1879	0.683
1880	0.843
1881	0.894
1882	0.99
1883	0.955
1884	0.928
1885	0.96
1886	0.637
1887	0.578
1888	0.965
1889	0.682
1890	1.018
1891	1.128
1892	1.094
1893	0.854
1894	0.901
1895	0.509
1896	0.859
1897	1.187
1898	1.13
1899	1.086
1900	0.784
1901	0.708
1902	0.875
1903	1.002
1904	0.891
1905	0.957
1906	1.129
1907	1.343
1908	1.423
1909	1.053
1910	0.856
1911	0.62
1912	1.215
1913	0.945
1914	1.016
1915	1.406
1916	1.153
1917	0.848
1918	0.467
1919	1.042
1920	1.217
1921	1.222
1922	0.838
1923	1.009
1924	1.039
1925	0.561
1926	0.843
1927	0.879
1928	1.14
1929	0.994
1930	0.97
1931	0.961
1932	1.049
1933	0.99
1934	0.861
1935	1.012
1936	0.773
1937	0.776
1938	0.819
1939	0.67
1940	0.779
1941	0.88
1942	0.989
1943	0.924
1944	0.96
1945	1.021
1946	1.033
1947	1.06
1948	0.985
1949	0.978
1950	1.132
1951	1.186
1952	0.833
1953	0.723
1954	1.364
1955	1.097
1956	0.778
1957	0.844
1958	1.198
1959	0.841
1960	1.069
1961	1.011
1962	1.235
1963	1.046
1964	0.971
1965	1.236
1966	0.86
1967	1.235
1968	1.419
1969	1.165
1970	1.076
1971	0.985
1972	1.067
1973	1.296