# northamerica_usa_vt002 - Granville Gulf - 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/2978
#
# 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_vt002 - Granville Gulf - 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: Granville Gulf
#	Location:
#	Country: United States
#	Northernmost_Latitude: 44.03
#	Southernmost_Latitude: 44.03
#	Easternmost_Longitude: -72.83
#	Westernmost_Longitude: -72.83
#	Elevation: 500 m
#--------------------
# Data_Collection
#	Collection_Name: northamerica_usa_vt002B
#	Earliest_Year: 1698
#	Most_Recent_Year: 1981
#	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":"3.77009939909","T2":"13.6713422056","M1":"0.0226198127159","M2":"0.569746027196"}}
#--------------------
# Species
#	Species_Name: eastern hemlock
#	Species_Code: TSCA
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# Chronology:
#
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#
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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
1698	0.91
1699	0.901
1700	0.614
1701	0.682
1702	0.575
1703	0.717
1704	0.69
1705	0.666
1706	0.655
1707	0.775
1708	0.672
1709	0.942
1710	1.204
1711	1.792
1712	1.848
1713	1.372
1714	1.46
1715	1.31
1716	0.907
1717	1.256
1718	1.045
1719	0.936
1720	0.91
1721	1.03
1722	0.954
1723	0.422
1724	0.532
1725	0.77
1726	0.64
1727	0.841
1728	0.709
1729	0.739
1730	0.763
1731	0.949
1732	0.817
1733	0.761
1734	0.873
1735	0.771
1736	0.646
1737	0.622
1738	0.568
1739	0.578
1740	0.537
1741	0.242
1742	0.478
1743	0.73
1744	0.745
1745	0.903
1746	0.75
1747	0.763
1748	0.504
1749	0.539
1750	0.624
1751	0.758
1752	0.903
1753	0.914
1754	0.835
1755	0.714
1756	0.858
1757	0.767
1758	0.69
1759	0.851
1760	0.931
1761	0.924
1762	0.79
1763	0.834
1764	0.998
1765	1.098
1766	0.868
1767	0.892
1768	1.03
1769	1.33
1770	0.864
1771	1.168
1772	1.164
1773	1.133
1774	0.932
1775	1.083
1776	1.227
1777	1.403
1778	1.023
1779	0.945
1780	0.949
1781	1.003
1782	1.042
1783	1.082
1784	1.111
1785	1.107
1786	1.365
1787	1.229
1788	1.53
1789	1.451
1790	1.026
1791	0.797
1792	0.954
1793	1.494
1794	1.117
1795	1.261
1796	1.094
1797	1.173
1798	0.785
1799	1.121
1800	1.286
1801	1.585
1802	1.228
1803	1.292
1804	1.128
1805	1.201
1806	0.891
1807	0.948
1808	0.937
1809	0.726
1810	0.539
1811	0.535
1812	1.171
1813	1.149
1814	1.314
1815	1.652
1816	1.263
1817	1.065
1818	0.875
1819	0.62
1820	0.535
1821	0.475
1822	0.575
1823	0.806
1824	0.835
1825	0.861
1826	0.603
1827	0.71
1828	0.744
1829	0.757
1830	1.028
1831	1.097
1832	1.281
1833	1.207
1834	1.436
1835	0.94
1836	0.652
1837	0.609
1838	0.725
1839	0.495
1840	0.546
1841	0.517
1842	0.413
1843	0.802
1844	0.819
1845	1.127
1846	0.957
1847	0.801
1848	1.014
1849	1.134
1850	0.95
1851	1.175
1852	0.875
1853	0.742
1854	0.692
1855	0.735
1856	1.026
1857	1.008
1858	1.26
1859	1.145
1860	1.191
1861	1.171
1862	1.142
1863	0.914
1864	0.838
1865	0.838
1866	1.372
1867	1.282
1868	1.255
1869	0.932
1870	1.007
1871	0.919
1872	0.822
1873	0.75
1874	0.869
1875	1.014
1876	0.993
1877	0.641
1878	0.735
1879	0.73
1880	0.9
1881	0.899
1882	1.171
1883	0.752
1884	1.068
1885	0.978
1886	1.277
1887	0.901
1888	1.114
1889	1.491
1890	1.579
1891	1.439
1892	1.736
1893	1.423
1894	1.602
1895	0.988
1896	1.002
1897	1.131
1898	1.333
1899	0.771
1900	0.629
1901	0.65
1902	0.917
1903	1.282
1904	1.244
1905	1.335
1906	1.085
1907	0.955
1908	0.913
1909	0.733
1910	1.095
1911	0.827
1912	0.961
1913	1.212
1914	0.852
1915	0.965
1916	1.123
1917	0.823
1918	0.591
1919	0.832
1920	0.895
1921	0.81
1922	0.769
1923	0.808
1924	1.025
1925	0.9
1926	1.121
1927	1.157
1928	1.086
1929	0.959
1930	1.055
1931	0.999
1932	1.025
1933	0.854
1934	0.73
1935	0.924
1936	1.023
1937	0.946
1938	0.996
1939	1.006
1940	0.833
1941	1.06
1942	0.686
1943	0.858
1944	0.82
1945	1.173
1946	1.349
1947	1.165
1948	0.573
1949	0.81
1950	0.64
1951	0.874
1952	0.917
1953	0.74
1954	0.865
1955	1.126
1956	0.724
1957	0.824
1958	0.827
1959	0.677
1960	0.45
1961	1.046
1962	0.712
1963	0.831
1964	0.845
1965	0.789
1966	0.848
1967	1.158
1968	1.095
1969	0.935
1970	1.023
1971	0.96
1972	1.05
1973	1.472
1974	1.202
1975	1.058
1976	0.975
1977	1.065
1978	0.952
1979	1.327
1980	1.191
1981	1.229