# northamerica_usa_al001 - Sipsey Wilderness - Breitenmoser Tree Ring Chronology Data
#-----------------------------------------------------------------------
#		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.
#
#
# 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/3029
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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_al001 - Sipsey Wilderness - 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: Sipsey Wilderness
#	Location:
#	Country: United States
#	Northernmost_Latitude: 34.33
#	Southernmost_Latitude: 34.33
#	Easternmost_Longitude: -87.45
#	Westernmost_Longitude: -87.45
#	Elevation: 250 m
#--------------------
# Data_Collection
#	Collection_Name: northamerica_usa_al001B
#	Earliest_Year: 1716
#	Most_Recent_Year: 1985
#	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":"5.02021760264","T2":"17.4914164107","M1":"0.0223985172886","M2":"0.570445094702"}}
#--------------------
# Species
#	Species_Name: white oak
#	Species_Code: QUAL
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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
1716	1.001
1717	1.021
1718	1.064
1719	1.222
1720	0.99
1721	1.129
1722	1.018
1723	0.851
1724	0.82
1725	0.562
1726	0.678
1727	0.692
1728	0.896
1729	0.869
1730	0.79
1731	0.884
1732	0.71
1733	1.261
1734	1.057
1735	0.722
1736	0.584
1737	0.605
1738	0.801
1739	0.864
1740	0.979
1741	1.219
1742	1.045
1743	0.715
1744	0.519
1745	0.641
1746	0.595
1747	0.758
1748	0.663
1749	0.698
1750	0.681
1751	0.774
1752	0.824
1753	0.773
1754	0.895
1755	0.781
1756	0.778
1757	0.691
1758	0.921
1759	0.84
1760	1.044
1761	1.254
1762	0.729
1763	0.978
1764	1.064
1765	0.949
1766	0.804
1767	0.858
1768	1.407
1769	0.878
1770	1.037
1771	1.17
1772	0.791
1773	0.803
1774	1.013
1775	1.092
1776	0.809
1777	0.95
1778	0.99
1779	0.656
1780	0.875
1781	1.107
1782	1.681
1783	1.493
1784	1.079
1785	1.076
1786	0.853
1787	0.913
1788	0.539
1789	0.452
1790	0.57
1791	0.651
1792	0.701
1793	0.775
1794	0.777
1795	1.026
1796	1.228
1797	1.215
1798	0.955
1799	0.663
1800	0.815
1801	0.815
1802	1.067
1803	0.832
1804	0.987
1805	1.27
1806	1.017
1807	0.927
1808	0.934
1809	0.983
1810	0.985
1811	0.927
1812	0.812
1813	0.846
1814	0.938
1815	0.817
1816	0.861
1817	0.829
1818	0.862
1819	1.023
1820	0.971
1821	0.839
1822	0.605
1823	0.856
1824	0.726
1825	0.407
1826	0.626
1827	0.832
1828	0.688
1829	0.632
1830	1.038
1831	1.187
1832	1.505
1833	1.366
1834	1.34
1835	1.321
1836	1.28
1837	1.14
1838	1.144
1839	0.995
1840	1.235
1841	1.196
1842	1.119
1843	1.106
1844	0.933
1845	0.977
1846	0.989
1847	1.104
1848	1.208
1849	1.019
1850	1.083
1851	0.813
1852	0.998
1853	0.866
1854	1.03
1855	1.143
1856	1.376
1857	1.146
1858	1.085
1859	0.808
1860	1.073
1861	1.039
1862	0.929
1863	1.178
1864	1.117
1865	1.026
1866	1.162
1867	1.351
1868	0.972
1869	1.114
1870	1.225
1871	1.25
1872	1.236
1873	1.141
1874	0.91
1875	1.009
1876	1.164
1877	1.16
1878	1.182
1879	0.849
1880	1.052
1881	1.075
1882	1.091
1883	1.312
1884	1.17
1885	1.017
1886	0.953
1887	0.901
1888	0.953
1889	1.118
1890	1.016
1891	0.915
1892	0.982
1893	1.078
1894	0.794
1895	1.145
1896	1.15
1897	1.021
1898	1.203
1899	1.119
1900	1.38
1901	1.435
1902	1.249
1903	1.503
1904	1.248
1905	1.084
1906	1.387
1907	1.129
1908	1.333
1909	1.237
1910	1.239
1911	0.87
1912	1.162
1913	1.064
1914	0.888
1915	0.972
1916	1.131
1917	1.139
1918	1.028
1919	1.113
1920	1.115
1921	0.876
1922	1.174
1923	0.992
1924	1.172
1925	0.84
1926	1.195
1927	0.848
1928	0.944
1929	0.988
1930	0.911
1931	0.934
1932	1.044
1933	0.89
1934	0.938
1935	1.158
1936	0.856
1937	0.874
1938	1.141
1939	0.986
1940	1.046
1941	0.818
1942	0.842
1943	0.738
1944	0.83
1945	1.154
1946	1.1
1947	0.906
1948	0.777
1949	0.843
1950	0.888
1951	1.107
1952	0.765
1953	0.611
1954	0.763
1955	0.768
1956	0.82
1957	0.774
1958	0.884
1959	0.877
1960	0.864
1961	0.988
1962	0.818
1963	0.905
1964	0.804
1965	0.866
1966	0.799
1967	0.941
1968	0.753
1969	0.871
1970	0.887
1971	1.091
1972	0.989
1973	1.209
1974	0.974
1975	0.984
1976	0.978
1977	0.736
1978	0.943
1979	0.806
1980	0.798
1981	0.943
1982	0.873
1983	0.865
1984	0.811
1985	0.868