# northamerica_canada_cana107 - Capilano Watershed Vancouver Recollection - 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/3119
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# Description/Documentation lines begin with #
# Data lines have no #
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# Archive: Tree Rings
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# Contribution_Date
#	Date: 2016-01-07
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# Title
#	Study_Name: northamerica_canada_cana107 - Capilano Watershed Vancouver Recollection - Breitenmoser Tree Ring Chronology Data
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# 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.
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#	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: Capilano Watershed Vancouver Recollection
#	Location:
#	Country: Canada
#	Northernmost_Latitude: 49.52
#	Southernmost_Latitude: 49.52
#	Easternmost_Longitude: -123.07
#	Westernmost_Longitude: -123.07
#	Elevation: 1000 m
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# Data_Collection
#	Collection_Name: northamerica_canada_cana107B
#	Earliest_Year: 1735
#	Most_Recent_Year: 1992
#	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":"4.89909730433","T2":"18.5870227067","M1":"0.0226292734463","M2":"0.360141206181"}}
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# Species
#	Species_Name: Pacific silver fir
#	Species_Code: ABAM
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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
1735	0.991
1736	0.993
1737	0.882
1738	0.837
1739	0.717
1740	0.623
1741	0.771
1742	0.523
1743	0.82
1744	0.767
1745	0.78
1746	0.739
1747	0.998
1748	0.738
1749	1.016
1750	1.169
1751	1.078
1752	0.91
1753	1.135
1754	0.734
1755	0.823
1756	1.14
1757	0.929
1758	0.883
1759	1.024
1760	0.858
1761	0.955
1762	0.92
1763	1.124
1764	1.061
1765	1.13
1766	1.085
1767	0.922
1768	0.818
1769	0.861
1770	1.018
1771	0.963
1772	1.015
1773	0.943
1774	1.126
1775	0.665
1776	1.018
1777	1.116
1778	0.865
1779	0.747
1780	1.123
1781	0.896
1782	0.992
1783	1.108
1784	1.033
1785	1.066
1786	1.073
1787	0.745
1788	1.037
1789	0.994
1790	0.797
1791	1.202
1792	1.059
1793	0.966
1794	1.056
1795	1.077
1796	0.869
1797	0.758
1798	1.161
1799	1.015
1800	1.003
1801	0.832
1802	1.004
1803	0.881
1804	1.079
1805	1.151
1806	0.819
1807	1.219
1808	0.761
1809	1.042
1810	0.65
1811	0.819
1812	1.007
1813	1.263
1814	1.221
1815	1.001
1816	1.213
1817	1.354
1818	1.131
1819	0.853
1820	1.097
1821	0.973
1822	1.279
1823	1.0
1824	0.863
1825	1.195
1826	0.953
1827	0.951
1828	0.978
1829	1.252
1830	1.191
1831	1.304
1832	0.966
1833	1.202
1834	1.426
1835	1.152
1836	1.175
1837	1.026
1838	0.914
1839	1.252
1840	1.069
1841	1.335
1842	1.135
1843	1.242
1844	1.11
1845	0.827
1846	1.292
1847	1.003
1848	1.138
1849	0.651
1850	0.724
1851	0.91
1852	0.801
1853	0.777
1854	0.645
1855	1.014
1856	0.727
1857	1.015
1858	1.01
1859	1.157
1860	1.364
1861	1.007
1862	0.642
1863	0.854
1864	0.703
1865	0.938
1866	0.768
1867	0.746
1868	1.041
1869	1.014
1870	0.532
1871	0.89
1872	1.375
1873	0.816
1874	1.026
1875	1.131
1876	0.417
1877	0.686
1878	0.662
1879	0.7
1880	0.909
1881	0.982
1882	1.044
1883	1.184
1884	1.014
1885	0.946
1886	1.133
1887	0.771
1888	0.655
1889	0.983
1890	0.808
1891	1.211
1892	1.138
1893	1.277
1894	1.72
1895	1.66
1896	1.393
1897	1.21
1898	1.025
1899	0.663
1900	1.109
1901	1.103
1902	1.262
1903	1.219
1904	1.528
1905	1.282
1906	1.038
1907	0.969
1908	0.882
1909	0.553
1910	1.238
1911	1.345
1912	1.427
1913	1.393
1914	1.621
1915	0.793
1916	0.561
1917	0.981
1918	0.988
1919	1.007
1920	1.181
1921	0.501
1922	1.206
1923	0.977
1924	0.902
1925	1.013
1926	1.019
1927	0.62
1928	0.797
1929	0.949
1930	1.03
1931	0.821
1932	0.514
1933	0.858
1934	1.339
1935	1.191
1936	0.953
1937	1.029
1938	1.211
1939	0.64
1940	0.837
1941	1.223
1942	1.048
1943	1.076
1944	1.218
1945	0.812
1946	0.713
1947	1.283
1948	1.12
1949	1.114
1950	1.109
1951	1.427
1952	0.806
1953	0.811
1954	0.807
1955	1.422
1956	1.02
1957	1.25
1958	1.458
1959	0.776
1960	1.314
1961	1.16
1962	0.663
1963	1.091
1964	0.647
1965	1.301
1966	0.579
1967	0.942
1968	0.886
1969	0.478
1970	0.461
1971	0.368
1972	0.337
1973	0.385
1974	0.262
1975	0.61
1976	0.483
1977	1.062
1978	0.874
1979	0.918
1980	0.917
1981	1.104
1982	0.66
1983	1.001
1984	1.064
1985	1.316
1986	0.89
1987	1.145
1988	0.73
1989	0.742
1990	1.029
1991	0.736
1992	1.233