# northamerica_usa_ar018 - Blackfork Mountain - Breitenmoser Tree Ring Chronology Data
#-----------------------------------------------------------------------
#		World Data Center for Paleoclimatology, Boulder
#				and
#		NOAA Paleoclimatology Program
#-----------------------------------------------------------------------
# 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/4816
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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_ar018 - Blackfork Mountain - 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.
#--------------------
#	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: Blackfork Mountain
#	Location:
#	Country: United States
#	Northernmost_Latitude: 34.72
#	Southernmost_Latitude: 34.72
#	Easternmost_Longitude: -94.45
#	Westernmost_Longitude: -94.45
#	Elevation: 745 m
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# Data_Collection
#	Collection_Name: northamerica_usa_ar018B
#	Earliest_Year: 1740
#	Most_Recent_Year: 1980
#	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":"5.01115277955","T2":"17.7568013365","M1":"0.0226952972427","M2":"0.550409151989"}}
#--------------------
# 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
1740	0.961
1741	1.066
1742	0.852
1743	0.854
1744	1.274
1745	1.005
1746	0.852
1747	0.779
1748	0.781
1749	0.716
1750	0.906
1751	0.773
1752	0.86
1753	1.39
1754	1.308
1755	1.206
1756	0.941
1757	0.829
1758	1.074
1759	1.189
1760	0.961
1761	1.255
1762	0.798
1763	0.818
1764	0.81
1765	0.714
1766	0.781
1767	0.53
1768	0.669
1769	0.725
1770	0.856
1771	0.742
1772	0.419
1773	0.516
1774	0.882
1775	0.966
1776	0.99
1777	0.911
1778	0.894
1779	1.158
1780	0.835
1781	0.82
1782	0.709
1783	1.012
1784	0.968
1785	0.741
1786	0.911
1787	1.164
1788	1.069
1789	0.924
1790	0.975
1791	1.087
1792	0.761
1793	1.022
1794	0.862
1795	1.018
1796	1.106
1797	0.953
1798	0.845
1799	0.752
1800	0.885
1801	0.38
1802	1.24
1803	0.982
1804	1.062
1805	1.024
1806	1.241
1807	0.881
1808	0.875
1809	0.868
1810	1.025
1811	1.14
1812	0.551
1813	0.861
1814	0.897
1815	0.625
1816	0.876
1817	1.28
1818	0.874
1819	1.034
1820	0.886
1821	1.016
1822	0.904
1823	0.729
1824	0.743
1825	0.74
1826	1.421
1827	0.935
1828	1.014
1829	1.179
1830	0.907
1831	0.891
1832	0.983
1833	1.277
1834	1.335
1835	1.204
1836	1.587
1837	1.3
1838	0.72
1839	0.658
1840	0.933
1841	0.696
1842	0.642
1843	0.83
1844	1.042
1845	0.877
1846	0.891
1847	0.709
1848	1.035
1849	1.104
1850	1.002
1851	0.843
1852	1.029
1853	0.874
1854	0.902
1855	0.541
1856	0.582
1857	1.222
1858	0.979
1859	0.793
1860	0.769
1861	0.841
1862	0.672
1863	0.521
1864	1.022
1865	1.204
1866	1.423
1867	1.278
1868	0.93
1869	1.692
1870	1.454
1871	1.181
1872	1.174
1873	1.26
1874	0.932
1875	1.078
1876	1.257
1877	1.288
1878	1.204
1879	0.868
1880	1.375
1881	1.325
1882	1.208
1883	1.296
1884	1.022
1885	1.129
1886	0.995
1887	1.044
1888	1.159
1889	1.062
1890	1.163
1891	1.077
1892	1.081
1893	1.197
1894	0.826
1895	0.99
1896	1.027
1897	0.847
1898	0.962
1899	1.097
1900	0.913
1901	1.003
1902	1.023
1903	0.96
1904	1.3
1905	1.039
1906	1.119
1907	0.962
1908	0.886
1909	0.863
1910	0.821
1911	0.673
1912	1.014
1913	0.885
1914	0.963
1915	1.343
1916	1.212
1917	0.876
1918	0.864
1919	1.147
1920	1.121
1921	1.423
1922	1.313
1923	1.035
1924	1.165
1925	0.922
1926	0.981
1927	1.064
1928	1.172
1929	1.181
1930	1.12
1931	0.804
1932	0.985
1933	0.962
1934	0.829
1935	1.34
1936	1.095
1937	1.136
1938	1.235
1939	1.283
1940	1.222
1941	1.12
1942	1.031
1943	0.953
1944	0.903
1945	0.756
1946	0.747
1947	0.736
1948	0.763
1949	0.907
1950	0.999
1951	1.018
1952	0.666
1953	0.555
1954	0.67
1955	0.887
1956	0.764
1957	1.077
1958	1.269
1959	1.226
1960	0.967
1961	0.919
1962	0.911
1963	0.89
1964	0.609
1965	1.117
1966	0.657
1967	0.738
1968	1.033
1969	1.002
1970	0.901
1971	0.814
1972	0.837
1973	1.063
1974	0.946
1975	1.056
1976	1.197
1977	0.854
1978	0.92
1979	0.83
1980	0.82