# northamerica_canada_cana226 - Kokanee - 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/5517
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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_cana226 - Kokanee - 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: Kokanee
#	Location:
#	Country: Canada
#	Northernmost_Latitude: 49.73
#	Southernmost_Latitude: 49.73
#	Easternmost_Longitude: -117.17
#	Westernmost_Longitude: -117.17
#	Elevation: 1950 m
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# Data_Collection
#	Collection_Name: northamerica_canada_cana226B
#	Earliest_Year: 1751
#	Most_Recent_Year: 1997
#	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":"5.46228535955","T2":"17.4016351245","M1":"0.02215847304","M2":"0.37070467644"}}
#--------------------
# Species
#	Species_Name: Engelmann spruce
#	Species_Code: PCEN
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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
1751	1.157
1752	0.905
1753	0.916
1754	0.83
1755	0.846
1756	1.075
1757	0.96
1758	1.099
1759	1.175
1760	0.951
1761	1.073
1762	1.104
1763	1.193
1764	1.098
1765	1.045
1766	0.933
1767	1.223
1768	1.058
1769	1.221
1770	0.954
1771	0.954
1772	0.884
1773	1.181
1774	0.957
1775	0.857
1776	1.05
1777	0.942
1778	1.077
1779	0.936
1780	0.981
1781	1.0
1782	0.953
1783	1.388
1784	1.12
1785	0.929
1786	0.959
1787	0.788
1788	0.884
1789	0.806
1790	1.091
1791	0.914
1792	0.959
1793	0.772
1794	0.983
1795	0.919
1796	1.031
1797	0.846
1798	1.046
1799	0.794
1800	0.913
1801	0.909
1802	0.95
1803	0.847
1804	0.854
1805	1.004
1806	0.778
1807	0.901
1808	0.903
1809	0.845
1810	0.871
1811	1.03
1812	0.934
1813	0.762
1814	0.83
1815	0.918
1816	0.909
1817	0.938
1818	0.812
1819	0.975
1820	0.95
1821	0.88
1822	0.972
1823	0.847
1824	0.682
1825	0.89
1826	0.829
1827	0.837
1828	0.956
1829	0.909
1830	0.793
1831	0.968
1832	0.644
1833	0.946
1834	0.999
1835	0.922
1836	0.71
1837	0.884
1838	0.774
1839	1.087
1840	0.874
1841	0.912
1842	0.997
1843	1.137
1844	0.791
1845	0.877
1846	0.774
1847	0.806
1848	0.999
1849	0.766
1850	0.848
1851	0.892
1852	0.809
1853	0.768
1854	0.757
1855	0.896
1856	0.743
1857	0.862
1858	0.917
1859	1.151
1860	0.928
1861	1.039
1862	1.085
1863	1.269
1864	1.002
1865	1.282
1866	1.002
1867	0.884
1868	1.127
1869	0.888
1870	0.939
1871	1.106
1872	1.022
1873	1.122
1874	1.123
1875	1.126
1876	0.85
1877	1.06
1878	1.378
1879	1.29
1880	1.2
1881	1.02
1882	1.141
1883	0.89
1884	0.697
1885	0.981
1886	1.155
1887	0.937
1888	1.022
1889	0.935
1890	0.972
1891	1.124
1892	1.159
1893	1.098
1894	1.105
1895	1.051
1896	1.069
1897	0.993
1898	1.154
1899	0.984
1900	1.11
1901	1.168
1902	1.066
1903	1.216
1904	1.497
1905	1.122
1906	1.07
1907	1.108
1908	1.22
1909	0.941
1910	1.084
1911	1.183
1912	1.125
1913	1.218
1914	1.288
1915	0.962
1916	1.156
1917	1.244
1918	1.056
1919	1.307
1920	1.143
1921	0.877
1922	1.029
1923	0.918
1924	0.866
1925	1.088
1926	0.796
1927	0.756
1928	0.903
1929	0.813
1930	0.851
1931	0.764
1932	0.892
1933	0.971
1934	1.121
1935	1.004
1936	1.16
1937	1.091
1938	1.378
1939	1.016
1940	1.161
1941	0.962
1942	0.862
1943	1.01
1944	1.253
1945	1.303
1946	0.888
1947	1.088
1948	1.229
1949	1.204
1950	1.343
1951	1.061
1952	1.102
1953	1.142
1954	1.036
1955	1.03
1956	1.01
1957	1.071
1958	1.266
1959	0.905
1960	0.956
1961	0.987
1962	0.859
1963	1.102
1964	1.029
1965	1.359
1966	1.123
1967	1.251
1968	0.719
1969	0.823
1970	1.004
1971	0.738
1972	0.646
1973	0.928
1974	0.651
1975	0.885
1976	0.675
1977	0.843
1978	0.811
1979	0.844
1980	0.612
1981	0.82
1982	0.711
1983	0.646
1984	0.95
1985	0.709
1986	0.699
1987	0.933
1988	0.93
1989	0.928
1990	1.036
1991	0.639
1992	1.091
1993	0.689
1994	1.141
1995	0.782
1996	0.901
1997	0.845