# northamerica_canada_cana092 - Pine Pass - 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/4590
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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_canada_cana092 - Pine Pass - 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
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# Site_Information
#	Site_Name: Pine Pass
#	Location:
#	Country: Canada
#	Northernmost_Latitude: 55.5
#	Southernmost_Latitude: 55.5
#	Easternmost_Longitude: -122.67
#	Westernmost_Longitude: -122.67
#	Elevation: 780 m
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# Data_Collection
#	Collection_Name: northamerica_canada_cana092B
#	Earliest_Year: 1755
#	Most_Recent_Year: 1983
#	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":"3.89044089674","T2":"18.3752223686","M1":"0.0227340134843","M2":"0.308179091631"}}
#--------------------
# Species
#	Species_Name: white spruce
#	Species_Code: PCGL
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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
1755	0.967
1756	1.089
1757	0.969
1758	1.015
1759	0.834
1760	0.811
1761	1.156
1762	1.316
1763	0.929
1764	0.976
1765	1.294
1766	1.414
1767	1.153
1768	1.031
1769	1.042
1770	0.984
1771	0.937
1772	0.979
1773	1.29
1774	1.126
1775	1.171
1776	1.069
1777	1.133
1778	1.158
1779	1.41
1780	1.123
1781	0.892
1782	1.25
1783	1.201
1784	1.254
1785	1.194
1786	1.045
1787	1.011
1788	1.001
1789	0.897
1790	0.84
1791	1.004
1792	1.099
1793	0.825
1794	1.237
1795	1.13
1796	1.177
1797	0.489
1798	0.735
1799	0.395
1800	0.598
1801	0.887
1802	1.121
1803	1.098
1804	1.188
1805	1.606
1806	1.286
1807	1.352
1808	1.537
1809	1.335
1810	1.292
1811	1.247
1812	1.037
1813	0.951
1814	0.954
1815	1.079
1816	1.25
1817	0.911
1818	1.031
1819	0.851
1820	0.874
1821	0.816
1822	0.918
1823	0.836
1824	0.75
1825	0.342
1826	0.399
1827	0.653
1828	0.957
1829	0.519
1830	0.563
1831	0.667
1832	0.917
1833	0.723
1834	0.747
1835	0.8
1836	0.921
1837	1.062
1838	0.993
1839	0.956
1840	0.882
1841	0.922
1842	1.149
1843	1.047
1844	0.863
1845	0.902
1846	0.901
1847	0.986
1848	0.623
1849	0.67
1850	1.034
1851	0.775
1852	0.677
1853	0.72
1854	0.884
1855	0.686
1856	0.482
1857	0.741
1858	0.908
1859	1.049
1860	0.853
1861	0.925
1862	1.194
1863	0.778
1864	0.721
1865	0.959
1866	1.247
1867	0.929
1868	0.785
1869	0.779
1870	0.935
1871	1.294
1872	1.133
1873	1.053
1874	1.143
1875	1.215
1876	0.772
1877	1.126
1878	1.11
1879	1.39
1880	1.54
1881	1.326
1882	1.162
1883	1.057
1884	1.321
1885	1.324
1886	1.302
1887	1.053
1888	1.085
1889	1.081
1890	1.235
1891	0.908
1892	0.853
1893	0.626
1894	0.721
1895	0.28
1896	0.591
1897	0.263
1898	0.488
1899	0.112
1900	0.392
1901	0.214
1902	0.371
1903	0.546
1904	0.767
1905	0.799
1906	0.868
1907	1.092
1908	1.184
1909	1.219
1910	1.49
1911	1.632
1912	1.332
1913	1.221
1914	1.377
1915	1.563
1916	1.216
1917	1.164
1918	1.064
1919	1.075
1920	1.097
1921	1.337
1922	1.39
1923	1.113
1924	1.219
1925	0.86
1926	0.763
1927	0.871
1928	0.853
1929	0.88
1930	1.006
1931	0.896
1932	1.114
1933	1.147
1934	1.292
1935	0.884
1936	1.103
1937	1.119
1938	1.244
1939	1.285
1940	1.293
1941	1.29
1942	1.134
1943	1.226
1944	1.555
1945	1.41
1946	1.633
1947	1.462
1948	1.411
1949	1.162
1950	1.601
1951	1.504
1952	1.269
1953	1.119
1954	1.33
1955	1.011
1956	0.565
1957	0.604
1958	0.733
1959	0.901
1960	1.011
1961	0.929
1962	0.747
1963	0.749
1964	0.711
1965	0.85
1966	0.82
1967	0.84
1968	0.576
1969	0.777
1970	0.716
1971	0.731
1972	0.684
1973	0.695
1974	0.754
1975	0.819
1976	0.668
1977	0.636
1978	0.68
1979	0.667
1980	0.665
1981	0.695
1982	0.64
1983	0.456