# northamerica_usa_ca617 - Eel River - 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.
#
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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/4844
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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_ca617 - Eel River - 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
#------------------
# Site_Information
#	Site_Name: Eel River
#	Location:
#	Country: United States
#	Northernmost_Latitude: 39.82
#	Southernmost_Latitude: 39.82
#	Easternmost_Longitude: -123.07
#	Westernmost_Longitude: -123.07
#	Elevation: 610 m
#--------------------
# Data_Collection
#	Collection_Name: northamerica_usa_ca617B
#	Earliest_Year: 1704
#	Most_Recent_Year: 1996
#	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":"3.9464836586","T2":"15.8645223105","M1":"0.0227219043968","M2":"0.543375719112"}}
#--------------------
# Species
#	Species_Name: blue oak
#	Species_Code: QUDG
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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
1704	1.129
1705	0.919
1706	0.917
1707	1.036
1708	0.786
1709	0.679
1710	0.754
1711	0.913
1712	0.898
1713	0.943
1714	0.949
1715	1.131
1716	0.97
1717	0.798
1718	0.712
1719	0.581
1720	0.705
1721	0.742
1722	0.814
1723	1.127
1724	1.033
1725	1.136
1726	0.894
1727	1.38
1728	0.845
1729	1.147
1730	1.349
1731	0.97
1732	1.098
1733	0.772
1734	1.113
1735	0.911
1736	0.98
1737	1.064
1738	1.091
1739	1.245
1740	1.249
1741	0.956
1742	0.925
1743	1.011
1744	0.923
1745	1.251
1746	0.956
1747	0.907
1748	0.777
1749	0.749
1750	0.75
1751	0.802
1752	1.065
1753	1.05
1754	0.962
1755	1.018
1756	0.729
1757	0.619
1758	0.526
1759	0.69
1760	0.922
1761	1.127
1762	0.837
1763	1.1
1764	0.867
1765	1.064
1766	1.136
1767	1.072
1768	0.882
1769	1.117
1770	0.563
1771	0.821
1772	0.804
1773	1.116
1774	0.904
1775	0.835
1776	0.572
1777	0.678
1778	0.805
1779	0.865
1780	0.89
1781	0.777
1782	0.622
1783	0.595
1784	1.104
1785	1.149
1786	0.91
1787	0.872
1788	0.684
1789	1.233
1790	1.286
1791	1.147
1792	1.105
1793	0.85
1794	0.783
1795	0.578
1796	0.799
1797	0.952
1798	0.868
1799	1.115
1800	0.956
1801	1.222
1802	0.902
1803	0.945
1804	0.931
1805	1.056
1806	0.874
1807	1.0
1808	1.022
1809	1.128
1810	0.978
1811	0.873
1812	1.004
1813	0.843
1814	1.254
1815	1.125
1816	1.07
1817	0.948
1818	0.93
1819	0.964
1820	0.969
1821	0.893
1822	0.775
1823	0.855
1824	0.697
1825	1.102
1826	1.058
1827	0.801
1828	0.915
1829	0.435
1830	0.781
1831	0.801
1832	1.159
1833	1.053
1834	1.028
1835	0.871
1836	1.043
1837	1.056
1838	1.013
1839	0.797
1840	0.873
1841	0.662
1842	0.487
1843	0.692
1844	0.571
1845	0.848
1846	0.783
1847	1.028
1848	1.066
1849	0.851
1850	0.888
1851	1.113
1852	0.923
1853	1.147
1854	1.139
1855	1.007
1856	0.979
1857	1.107
1858	1.024
1859	0.982
1860	1.121
1861	0.992
1862	1.351
1863	1.297
1864	0.978
1865	0.99
1866	1.292
1867	1.046
1868	1.518
1869	1.062
1870	0.863
1871	0.577
1872	0.567
1873	0.756
1874	1.294
1875	1.104
1876	1.144
1877	1.055
1878	1.244
1879	1.523
1880	1.256
1881	0.696
1882	1.163
1883	0.815
1884	1.243
1885	1.112
1886	1.433
1887	1.388
1888	1.514
1889	1.141
1890	1.28
1891	1.424
1892	1.302
1893	1.21
1894	1.476
1895	1.285
1896	1.07
1897	1.131
1898	1.156
1899	0.968
1900	1.001
1901	0.841
1902	0.89
1903	0.985
1904	1.196
1905	1.268
1906	1.375
1907	1.298
1908	1.213
1909	0.901
1910	0.951
1911	0.652
1912	0.933
1913	1.291
1914	1.042
1915	1.167
1916	1.055
1917	1.014
1918	0.628
1919	0.547
1920	0.678
1921	1.055
1922	0.892
1923	0.825
1924	0.534
1925	1.224
1926	0.845
1927	0.988
1928	0.914
1929	0.512
1930	0.902
1931	0.798
1932	0.992
1933	0.866
1934	0.961
1935	0.974
1936	1.37
1937	1.168
1938	1.186
1939	1.127
1940	1.063
1941	1.229
1942	1.216
1943	1.062
1944	0.929
1945	1.011
1946	0.67
1947	0.875
1948	0.948
1949	0.617
1950	1.003
1951	0.999
1952	1.067
1953	1.225
1954	1.188
1955	0.939
1956	1.037
1957	1.097
1958	1.037
1959	0.557
1960	0.553
1961	0.62
1962	0.775
1963	0.835
1964	0.793
1965	0.876
1966	0.811
1967	0.973
1968	0.608
1969	0.907
1970	0.699
1971	0.901
1972	0.929
1973	1.066
1974	1.216
1975	0.983
1976	0.892
1977	0.499
1978	1.242
1979	0.851
1980	1.008
1981	1.093
1982	1.18
1983	1.295
1984	1.223
1985	0.882
1986	0.877
1987	0.621
1988	0.709
1989	0.948
1990	1.053
1991	0.806
1992	0.857
1993	1.292
1994	0.986
1995	1.117
1996	1.07