# northamerica_usa_tn - Scotts Gap - 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/3182
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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_tn - Scotts Gap - 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: Scotts Gap
#	Location:
#	Country: United States
#	Northernmost_Latitude: 35.6
#	Southernmost_Latitude: 35.6
#	Easternmost_Longitude: -83.92
#	Westernmost_Longitude: -83.92
#	Elevation: 520 m
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# Data_Collection
#	Collection_Name: northamerica_usa_tnB
#	Earliest_Year: 1744
#	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":"5.10946946135","T2":"17.1239319723","M1":"0.0230813214534","M2":"0.607965004165"}}
#--------------------
# Species
#	Species_Name: tuliptree
#	Species_Code: LITU
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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
1744	1.187
1745	1.346
1746	1.104
1747	1.194
1748	1.202
1749	1.049
1750	1.294
1751	0.918
1752	0.611
1753	0.803
1754	1.172
1755	0.748
1756	0.879
1757	0.983
1758	0.658
1759	0.882
1760	0.827
1761	0.933
1762	0.702
1763	0.988
1764	0.858
1765	0.833
1766	0.597
1767	0.818
1768	0.992
1769	0.724
1770	0.747
1771	1.033
1772	0.774
1773	0.891
1774	0.168
1775	0.669
1776	0.547
1777	0.756
1778	0.586
1779	0.301
1780	0.94
1781	1.047
1782	1.451
1783	1.631
1784	0.513
1785	1.389
1786	1.207
1787	1.483
1788	1.171
1789	1.048
1790	0.69
1791	0.854
1792	0.944
1793	0.988
1794	0.99
1795	0.88
1796	1.505
1797	1.156
1798	1.145
1799	1.159
1800	1.315
1801	1.089
1802	1.556
1803	1.529
1804	1.424
1805	1.738
1806	1.717
1807	1.05
1808	0.773
1809	0.95
1810	1.144
1811	0.667
1812	0.535
1813	0.61
1814	1.034
1815	0.844
1816	1.193
1817	1.088
1818	1.029
1819	0.426
1820	1.051
1821	0.763
1822	0.781
1823	1.104
1824	1.373
1825	1.177
1826	0.908
1827	1.092
1828	0.894
1829	0.844
1830	1.571
1831	1.333
1832	1.301
1833	0.926
1834	0.834
1835	0.738
1836	0.787
1837	0.737
1838	0.587
1839	0.418
1840	0.697
1841	0.841
1842	0.808
1843	1.113
1844	0.934
1845	1.168
1846	1.005
1847	1.078
1848	1.288
1849	1.012
1850	0.727
1851	0.847
1852	1.102
1853	1.305
1854	0.179
1855	0.645
1856	0.926
1857	0.965
1858	1.142
1859	0.868
1860	1.138
1861	0.546
1862	0.919
1863	1.106
1864	0.814
1865	0.778
1866	1.011
1867	1.018
1868	0.831
1869	1.137
1870	0.839
1871	0.809
1872	0.587
1873	0.65
1874	0.244
1875	1.072
1876	1.067
1877	0.638
1878	0.92
1879	0.374
1880	0.58
1881	0.88
1882	0.925
1883	1.03
1884	0.954
1885	0.904
1886	0.945
1887	1.097
1888	0.778
1889	1.238
1890	1.35
1891	1.015
1892	1.452
1893	1.302
1894	1.103
1895	0.759
1896	0.897
1897	1.189
1898	0.54
1899	0.786
1900	1.002
1901	0.829
1902	0.87
1903	1.206
1904	1.086
1905	0.969
1906	1.178
1907	1.089
1908	0.909
1909	1.257
1910	1.231
1911	0.651
1912	1.294
1913	0.832
1914	0.458
1915	1.153
1916	1.821
1917	1.352
1918	1.11
1919	0.841
1920	0.93
1921	0.597
1922	1.564
1923	1.45
1924	1.083
1925	0.366
1926	0.616
1927	0.706
1928	1.265
1929	1.075
1930	0.59
1931	0.745
1932	0.772
1933	0.47
1934	0.685
1935	0.96
1936	0.261
1937	0.756
1938	1.015
1939	1.042
1940	0.87
1941	0.842
1942	1.06
1943	1.148
1944	0.385
1945	0.903
1946	1.15
1947	0.92
1948	0.746
1949	1.109
1950	1.199
1951	1.156
1952	0.964
1953	0.689
1954	0.704
1955	0.878
1956	0.76
1957	0.871
1958	1.04
1959	0.848
1960	1.091
1961	1.192
1962	1.069
1963	0.911
1964	0.825
1965	0.782
1966	0.825
1967	0.869
1968	1.298
1969	1.066
1970	0.825
1971	1.091
1972	1.512
1973	1.552
1974	1.631
1975	1.437
1976	1.225
1977	0.891
1978	1.042
1979	0.948
1980	0.905
1981	0.908