# northamerica_usa_ct002 - North Forty Tract - Breitenmoser Tree Ring Chronology Data
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#		World Data Center for Paleoclimatology, Boulder
#				and
#		NOAA Paleoclimatology Program
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# 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/3007
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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_ct002 - North Forty Tract - 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: North Forty Tract
#	Location:
#	Country: United States
#	Northernmost_Latitude: 41.97
#	Southernmost_Latitude: 41.97
#	Easternmost_Longitude: -73.22
#	Westernmost_Longitude: -73.22
#	Elevation: 250 m
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# Data_Collection
#	Collection_Name: northamerica_usa_ct002B
#	Earliest_Year: 1749
#	Most_Recent_Year: 1985
#	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":"4.63881542856","T2":"14.6231786369","M1":"0.0221784782393","M2":"0.565657379274"}}
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# Species
#	Species_Name: eastern hemlock
#	Species_Code: TSCA
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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
1749	0.808
1750	0.989
1751	1.077
1752	1.076
1753	0.834
1754	0.798
1755	0.765
1756	0.749
1757	0.839
1758	0.628
1759	0.645
1760	0.74
1761	0.726
1762	0.688
1763	0.699
1764	0.816
1765	0.834
1766	0.7
1767	0.551
1768	0.542
1769	0.617
1770	0.643
1771	0.724
1772	0.704
1773	0.736
1774	0.662
1775	0.654
1776	0.825
1777	1.001
1778	0.754
1779	0.623
1780	0.47
1781	0.371
1782	0.629
1783	0.726
1784	0.582
1785	0.385
1786	0.484
1787	0.445
1788	0.476
1789	0.644
1790	0.476
1791	0.495
1792	0.403
1793	0.517
1794	0.477
1795	0.609
1796	0.511
1797	0.567
1798	0.469
1799	0.51
1800	0.69
1801	0.782
1802	0.855
1803	0.917
1804	0.846
1805	0.938
1806	0.91
1807	1.289
1808	1.422
1809	1.391
1810	0.883
1811	1.063
1812	1.392
1813	1.419
1814	1.412
1815	1.673
1816	1.241
1817	1.3
1818	1.052
1819	0.959
1820	0.871
1821	1.034
1822	1.124
1823	1.402
1824	1.435
1825	1.269
1826	0.949
1827	1.195
1828	1.546
1829	1.238
1830	1.242
1831	1.103
1832	1.083
1833	1.13
1834	1.349
1835	0.96
1836	0.833
1837	0.668
1838	0.971
1839	0.695
1840	0.859
1841	0.832
1842	1.03
1843	0.779
1844	0.807
1845	0.946
1846	0.933
1847	1.043
1848	1.127
1849	0.973
1850	0.905
1851	0.965
1852	0.955
1853	1.064
1854	1.099
1855	1.17
1856	0.885
1857	0.831
1858	0.925
1859	1.018
1860	1.192
1861	1.285
1862	0.991
1863	1.361
1864	1.028
1865	1.081
1866	1.278
1867	1.324
1868	1.143
1869	0.591
1870	0.587
1871	0.649
1872	0.606
1873	0.605
1874	1.031
1875	0.929
1876	0.807
1877	0.535
1878	0.41
1879	0.549
1880	0.825
1881	0.692
1882	1.134
1883	0.941
1884	0.999
1885	0.731
1886	0.489
1887	0.585
1888	0.58
1889	1.043
1890	1.359
1891	1.347
1892	1.353
1893	1.411
1894	1.579
1895	0.769
1896	0.964
1897	1.444
1898	1.695
1899	0.837
1900	1.135
1901	1.138
1902	1.606
1903	1.895
1904	1.535
1905	1.216
1906	1.31
1907	1.312
1908	1.097
1909	1.161
1910	1.06
1911	0.888
1912	1.052
1913	1.189
1914	1.043
1915	1.309
1916	1.324
1917	1.108
1918	0.88
1919	0.959
1920	0.547
1921	1.096
1922	1.043
1923	0.926
1924	0.709
1925	0.978
1926	0.698
1927	1.15
1928	1.433
1929	1.025
1930	1.015
1931	0.959
1932	0.885
1933	0.797
1934	0.556
1935	1.014
1936	0.984
1937	0.973
1938	0.955
1939	0.896
1940	0.753
1941	0.842
1942	0.746
1943	0.831
1944	0.55
1945	0.733
1946	0.928
1947	0.913
1948	0.842
1949	0.812
1950	0.719
1951	1.195
1952	1.007
1953	0.924
1954	0.968
1955	0.951
1956	0.734
1957	0.678
1958	0.674
1959	0.858
1960	0.419
1961	0.905
1962	0.636
1963	0.705
1964	0.618
1965	0.753
1966	0.667
1967	1.082
1968	0.965
1969	0.654
1970	0.866
1971	0.739
1972	0.668
1973	1.207
1974	1.0
1975	1.149
1976	0.918
1977	0.947
1978	0.92
1979	1.016
1980	1.103
1981	0.948
1982	0.918
1983	0.927
1984	0.59
1985	0.816