# northamerica_usa_va016 - Watch Dog Massenhutten 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.
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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/3037
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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_va016 - Watch Dog Massenhutten 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: Watch Dog Massenhutten Mountain
#	Location:
#	Country: United States
#	Northernmost_Latitude: 38.5
#	Southernmost_Latitude: 38.5
#	Easternmost_Longitude: -78.35
#	Westernmost_Longitude: -78.35
#	Elevation: 1000 m
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# Data_Collection
#	Collection_Name: northamerica_usa_va016B
#	Earliest_Year: 1700
#	Most_Recent_Year: 1980
#	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":"3.91251781368","T2":"15.7277969759","M1":"0.0225772936314","M2":"0.540976944495"}}
#--------------------
# Species
#	Species_Name: chestnut oak
#	Species_Code: QUPR
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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
1700	0.884
1701	0.964
1702	0.938
1703	0.754
1704	0.559
1705	0.742
1706	0.808
1707	0.891
1708	0.908
1709	0.809
1710	0.792
1711	0.957
1712	1.038
1713	0.895
1714	0.868
1715	0.817
1716	0.953
1717	0.917
1718	0.9
1719	0.95
1720	1.072
1721	0.882
1722	0.921
1723	0.815
1724	0.886
1725	0.9
1726	0.812
1727	0.801
1728	0.76
1729	1.0
1730	0.855
1731	1.203
1732	0.896
1733	0.764
1734	0.734
1735	1.08
1736	1.238
1737	1.028
1738	0.923
1739	1.203
1740	1.239
1741	0.81
1742	1.187
1743	0.968
1744	0.882
1745	1.028
1746	0.752
1747	0.974
1748	0.652
1749	0.888
1750	1.108
1751	1.104
1752	1.118
1753	1.143
1754	1.34
1755	0.855
1756	1.43
1757	0.979
1758	0.785
1759	0.897
1760	0.857
1761	1.234
1762	0.97
1763	1.312
1764	1.018
1765	1.001
1766	1.235
1767	1.007
1768	1.256
1769	0.979
1770	1.316
1771	1.199
1772	0.984
1773	1.145
1774	0.773
1775	0.822
1776	1.008
1777	1.032
1778	1.141
1779	0.875
1780	1.224
1781	1.315
1782	1.152
1783	1.105
1784	1.015
1785	1.068
1786	1.215
1787	1.169
1788	1.289
1789	0.942
1790	0.943
1791	0.796
1792	0.761
1793	1.067
1794	1.109
1795	1.192
1796	1.182
1797	0.958
1798	1.106
1799	1.204
1800	1.075
1801	1.237
1802	1.146
1803	1.048
1804	1.185
1805	1.054
1806	0.856
1807	0.957
1808	1.042
1809	1.092
1810	0.883
1811	1.018
1812	0.995
1813	0.994
1814	1.052
1815	1.049
1816	0.965
1817	1.022
1818	1.098
1819	1.049
1820	0.982
1821	1.091
1822	0.908
1823	0.889
1824	1.039
1825	0.952
1826	0.865
1827	1.097
1828	1.026
1829	0.913
1830	1.07
1831	0.989
1832	1.176
1833	1.103
1834	1.025
1835	0.933
1836	1.057
1837	0.911
1838	0.917
1839	0.816
1840	1.025
1841	0.942
1842	0.87
1843	0.791
1844	0.833
1845	0.777
1846	0.828
1847	0.769
1848	0.796
1849	0.865
1850	0.959
1851	0.84
1852	0.869
1853	0.809
1854	0.979
1855	0.944
1856	0.919
1857	0.928
1858	0.841
1859	0.752
1860	0.737
1861	0.776
1862	0.93
1863	0.832
1864	0.857
1865	0.832
1866	0.816
1867	0.756
1868	0.827
1869	0.949
1870	0.932
1871	0.74
1872	0.757
1873	0.816
1874	0.738
1875	0.866
1876	0.841
1877	0.782
1878	0.958
1879	0.837
1880	0.844
1881	0.968
1882	0.919
1883	0.858
1884	0.956
1885	0.81
1886	0.873
1887	0.878
1888	0.867
1889	1.048
1890	0.9
1891	0.815
1892	0.818
1893	0.856
1894	0.82
1895	0.866
1896	0.815
1897	0.811
1898	0.785
1899	0.86
1900	0.847
1901	1.048
1902	0.89
1903	1.094
1904	1.093
1905	0.997
1906	1.141
1907	1.119
1908	1.123
1909	1.166
1910	1.121
1911	0.796
1912	1.003
1913	1.108
1914	0.819
1915	0.973
1916	1.256
1917	1.175
1918	1.004
1919	1.213
1920	1.25
1921	1.137
1922	1.181
1923	0.999
1924	1.269
1925	0.907
1926	1.03
1927	1.24
1928	1.362
1929	1.174
1930	1.077
1931	1.071
1932	1.117
1933	0.96
1934	1.034
1935	0.978
1936	0.978
1937	1.175
1938	1.194
1939	1.173
1940	1.201
1941	1.0
1942	1.079
1943	1.102
1944	0.95
1945	0.92
1946	1.037
1947	0.866
1948	0.973
1949	1.211
1950	1.262
1951	1.332
1952	1.072
1953	1.174
1954	0.997
1955	0.877
1956	1.0
1957	1.098
1958	1.085
1959	1.046
1960	0.974
1961	1.11
1962	0.997
1963	0.839
1964	0.88
1965	0.884
1966	0.768
1967	0.85
1968	0.922
1969	0.893
1970	1.064
1971	1.135
1972	1.101
1973	0.997
1974	1.03
1975	1.065
1976	1.028
1977	0.859
1978	0.95
1979	0.917
1980	0.889