# northamerica_canada_cana152 - Big White - 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.
#
#
# 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/4088
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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_cana152 - Big White - 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: Big White
#	Location:
#	Country: Canada
#	Northernmost_Latitude: 49.87
#	Southernmost_Latitude: 49.87
#	Easternmost_Longitude: -118.85
#	Westernmost_Longitude: -118.85
#	Elevation: 1700 m
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# Data_Collection
#	Collection_Name: northamerica_canada_cana152B
#	Earliest_Year: 1726
#	Most_Recent_Year: 1998
#	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":"7.84401378608","T2":"18.2773018033","M1":"0.0227235813406","M2":"0.355417409915"}}
#--------------------
# Species
#	Species_Name: subalpine fir
#	Species_Code: ABLA
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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
1726	1.043
1727	1.551
1728	1.21
1729	1.169
1730	0.924
1731	0.734
1732	0.941
1733	1.092
1734	0.907
1735	0.806
1736	1.209
1737	1.136
1738	0.906
1739	1.101
1740	0.601
1741	1.066
1742	0.896
1743	0.951
1744	1.075
1745	0.99
1746	1.017
1747	1.209
1748	1.5
1749	1.105
1750	1.199
1751	1.182
1752	0.874
1753	0.603
1754	1.004
1755	1.102
1756	1.534
1757	1.247
1758	0.991
1759	1.007
1760	0.866
1761	0.996
1762	1.01
1763	1.368
1764	1.306
1765	1.213
1766	1.178
1767	1.269
1768	1.219
1769	1.14
1770	0.911
1771	1.02
1772	0.877
1773	0.881
1774	0.958
1775	0.706
1776	0.99
1777	1.143
1778	0.791
1779	0.672
1780	0.831
1781	0.758
1782	0.82
1783	1.458
1784	1.184
1785	0.999
1786	1.032
1787	0.76
1788	0.939
1789	0.869
1790	0.837
1791	1.165
1792	1.025
1793	1.052
1794	0.98
1795	0.978
1796	0.98
1797	0.749
1798	0.763
1799	0.798
1800	0.797
1801	0.474
1802	0.729
1803	0.806
1804	0.808
1805	0.863
1806	0.623
1807	0.804
1808	1.009
1809	0.826
1810	0.85
1811	1.0
1812	0.748
1813	0.738
1814	0.85
1815	0.846
1816	0.947
1817	0.828
1818	0.807
1819	0.853
1820	0.721
1821	0.853
1822	1.02
1823	0.856
1824	0.849
1825	1.002
1826	0.65
1827	0.828
1828	0.975
1829	0.824
1830	0.771
1831	0.964
1832	0.953
1833	0.983
1834	1.108
1835	1.012
1836	0.794
1837	0.942
1838	0.776
1839	0.98
1840	0.629
1841	0.648
1842	0.82
1843	0.92
1844	0.848
1845	0.792
1846	0.875
1847	0.927
1848	0.811
1849	0.818
1850	0.952
1851	0.857
1852	0.705
1853	0.621
1854	0.632
1855	0.816
1856	0.702
1857	0.727
1858	0.742
1859	0.766
1860	0.689
1861	0.715
1862	0.799
1863	0.901
1864	0.711
1865	1.07
1866	1.046
1867	0.822
1868	0.802
1869	0.706
1870	0.77
1871	0.82
1872	0.874
1873	0.905
1874	0.931
1875	1.023
1876	0.835
1877	0.925
1878	0.984
1879	0.976
1880	1.065
1881	1.295
1882	1.454
1883	1.338
1884	1.344
1885	1.695
1886	1.65
1887	1.399
1888	1.456
1889	1.327
1890	1.418
1891	1.33
1892	1.096
1893	1.109
1894	1.287
1895	1.356
1896	1.4
1897	1.304
1898	1.316
1899	1.107
1900	1.568
1901	1.505
1902	1.336
1903	1.423
1904	1.544
1905	1.426
1906	1.423
1907	1.408
1908	1.513
1909	1.219
1910	1.194
1911	1.267
1912	1.229
1913	1.308
1914	1.311
1915	1.181
1916	1.143
1917	1.076
1918	1.155
1919	1.084
1920	1.096
1921	0.975
1922	1.05
1923	0.999
1924	1.014
1925	0.767
1926	1.124
1927	1.172
1928	1.187
1929	1.046
1930	1.125
1931	1.05
1932	1.117
1933	1.189
1934	1.169
1935	1.189
1936	1.191
1937	1.158
1938	1.283
1939	1.117
1940	1.248
1941	1.256
1942	1.189
1943	0.717
1944	0.823
1945	0.548
1946	0.445
1947	0.332
1948	0.27
1949	0.323
1950	0.486
1951	0.519
1952	0.559
1953	0.446
1954	0.401
1955	0.554
1956	0.517
1957	0.624
1958	0.818
1959	0.761
1960	0.923
1961	0.859
1962	0.905
1963	1.126
1964	1.088
1965	1.155
1966	1.221
1967	1.118
1968	0.928
1969	1.12
1970	1.093
1971	0.923
1972	0.872
1973	0.997
1974	0.783
1975	0.982
1976	1.065
1977	1.146
1978	1.058
1979	1.06
1980	0.968
1981	1.176
1982	0.988
1983	0.862
1984	1.043
1985	0.898
1986	0.896
1987	1.061
1988	0.94
1989	0.633
1990	0.864
1991	0.794
1992	1.009
1993	0.808
1994	0.961
1995	0.767
1996	0.857
1997	0.707
1998	0.973