# northamerica_canada_cana098 - Vermillion Pass - 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/4718
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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_cana098 - Vermillion 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 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: Vermillion Pass
#	Location:
#	Country: Canada
#	Northernmost_Latitude: 51.17
#	Southernmost_Latitude: 51.17
#	Easternmost_Longitude: -116.17
#	Westernmost_Longitude: -116.17
#	Elevation: 1500 m
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# Data_Collection
#	Collection_Name: northamerica_canada_cana098B
#	Earliest_Year: 1708
#	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":"5.73574652187","T2":"16.9362410313","M1":"0.0227617989615","M2":"0.406132995769"}}
#--------------------
# 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
1708	1.077
1709	1.066
1710	1.157
1711	1.079
1712	1.08
1713	1.21
1714	1.019
1715	0.838
1716	1.05
1717	0.943
1718	0.992
1719	1.004
1720	1.01
1721	0.893
1722	0.887
1723	0.91
1724	0.84
1725	0.859
1726	0.893
1727	0.986
1728	0.999
1729	0.923
1730	0.884
1731	0.834
1732	0.933
1733	0.906
1734	0.884
1735	0.939
1736	1.015
1737	0.916
1738	0.929
1739	1.034
1740	0.994
1741	0.983
1742	0.999
1743	0.977
1744	0.987
1745	1.069
1746	0.906
1747	0.973
1748	0.924
1749	0.908
1750	1.012
1751	0.94
1752	0.953
1753	0.855
1754	0.939
1755	0.975
1756	1.326
1757	1.042
1758	1.025
1759	1.008
1760	1.026
1761	1.147
1762	0.853
1763	1.164
1764	0.933
1765	0.943
1766	0.893
1767	0.989
1768	1.047
1769	1.191
1770	1.133
1771	1.121
1772	1.003
1773	1.19
1774	1.016
1775	1.085
1776	1.105
1777	1.021
1778	0.894
1779	0.738
1780	0.925
1781	0.895
1782	1.052
1783	1.084
1784	0.925
1785	0.965
1786	0.962
1787	0.976
1788	1.072
1789	0.959
1790	1.002
1791	1.0
1792	1.07
1793	0.967
1794	1.043
1795	0.901
1796	1.116
1797	0.767
1798	0.984
1799	0.715
1800	0.923
1801	0.786
1802	0.967
1803	1.091
1804	1.115
1805	0.961
1806	0.683
1807	0.699
1808	0.723
1809	0.734
1810	0.76
1811	0.801
1812	0.668
1813	0.693
1814	0.739
1815	0.711
1816	0.72
1817	0.824
1818	0.787
1819	0.865
1820	0.9
1821	0.83
1822	0.882
1823	0.997
1824	0.877
1825	0.918
1826	0.979
1827	0.927
1828	1.121
1829	0.939
1830	0.877
1831	1.033
1832	0.96
1833	0.944
1834	0.915
1835	0.917
1836	0.793
1837	0.793
1838	0.932
1839	1.121
1840	0.897
1841	0.874
1842	1.053
1843	1.092
1844	1.1
1845	1.155
1846	1.122
1847	1.291
1848	1.112
1849	1.066
1850	1.313
1851	1.208
1852	1.352
1853	1.104
1854	1.107
1855	1.362
1856	1.292
1857	1.312
1858	1.07
1859	1.346
1860	1.011
1861	1.215
1862	1.381
1863	1.288
1864	1.124
1865	1.195
1866	1.301
1867	1.223
1868	1.449
1869	1.301
1870	1.229
1871	1.053
1872	1.037
1873	0.939
1874	0.92
1875	1.103
1876	0.928
1877	1.024
1878	1.115
1879	0.955
1880	1.131
1881	1.08
1882	1.18
1883	0.916
1884	1.09
1885	1.129
1886	1.213
1887	0.93
1888	1.077
1889	0.939
1890	0.989
1891	1.085
1892	1.039
1893	1.043
1894	1.161
1895	1.045
1896	1.189
1897	1.172
1898	1.256
1899	1.137
1900	1.253
1901	1.092
1902	1.196
1903	1.368
1904	1.473
1905	1.289
1906	1.21
1907	1.201
1908	1.227
1909	1.067
1910	1.187
1911	1.283
1912	1.14
1913	1.205
1914	1.106
1915	0.972
1916	1.111
1917	1.082
1918	1.042
1919	0.958
1920	0.909
1921	0.776
1922	0.831
1923	0.431
1924	0.442
1925	0.464
1926	0.414
1927	0.5
1928	0.746
1929	0.679
1930	0.737
1931	0.671
1932	0.63
1933	0.653
1934	0.705
1935	0.724
1936	0.627
1937	0.742
1938	0.95
1939	0.815
1940	1.084
1941	1.038
1942	0.977
1943	0.747
1944	0.991
1945	0.98
1946	0.901
1947	0.836
1948	0.91
1949	0.888
1950	0.925
1951	0.617
1952	0.514
1953	0.503
1954	0.715
1955	0.662
1956	0.529
1957	0.649
1958	0.812
1959	0.836
1960	0.904
1961	0.931
1962	0.795
1963	1.055
1964	1.191
1965	1.23
1966	1.163
1967	1.22
1968	0.902
1969	1.23
1970	1.316
1971	1.082
1972	1.039
1973	1.111
1974	1.303
1975	1.385
1976	1.284
1977	1.283
1978	0.978
1979	0.995
1980	1.152
1981	0.967
1982	0.926
1983	1.043