# northamerica_canada_cana112 - Kootenai 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.
#
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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/2829
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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_cana112 - Kootenai 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: Kootenai Pass
#	Location:
#	Country: Canada
#	Northernmost_Latitude: 49.08
#	Southernmost_Latitude: 49.08
#	Easternmost_Longitude: -116.75
#	Westernmost_Longitude: -116.75
#	Elevation: 1850 m
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# Data_Collection
#	Collection_Name: northamerica_canada_cana112B
#	Earliest_Year: 1727
#	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":"5.74506097817","T2":"18.370905582","M1":"0.0229545398788","M2":"0.365066507303"}}
#--------------------
# 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
#
#--------------------
# Data:
# Data lines follow (have no #)
# Data line format - tab-delimited text, variable short name as header
# Missing Values: nan
#
age	trsgi
1727	1.102
1728	1.22
1729	1.153
1730	1.045
1731	1.085
1732	1.034
1733	1.025
1734	1.002
1735	0.946
1736	1.162
1737	1.18
1738	1.127
1739	1.17
1740	0.813
1741	1.149
1742	1.14
1743	1.052
1744	0.855
1745	0.943
1746	0.826
1747	1.01
1748	1.068
1749	0.873
1750	1.082
1751	1.159
1752	0.773
1753	0.974
1754	0.906
1755	0.939
1756	1.216
1757	1.109
1758	1.179
1759	1.025
1760	1.138
1761	1.074
1762	1.005
1763	1.104
1764	1.056
1765	1.08
1766	0.883
1767	1.059
1768	1.1
1769	1.063
1770	0.993
1771	1.157
1772	0.917
1773	1.265
1774	1.147
1775	0.837
1776	1.12
1777	1.02
1778	1.06
1779	1.012
1780	0.906
1781	1.017
1782	0.924
1783	1.228
1784	1.06
1785	0.96
1786	0.959
1787	0.824
1788	0.903
1789	0.719
1790	1.103
1791	0.929
1792	0.983
1793	0.958
1794	1.18
1795	1.128
1796	1.088
1797	0.926
1798	1.117
1799	0.779
1800	0.906
1801	1.047
1802	1.17
1803	1.037
1804	1.019
1805	1.019
1806	0.834
1807	1.228
1808	1.063
1809	1.067
1810	0.779
1811	1.174
1812	1.045
1813	0.838
1814	0.746
1815	0.833
1816	0.858
1817	0.985
1818	0.775
1819	0.889
1820	0.89
1821	0.77
1822	0.903
1823	0.818
1824	0.608
1825	0.784
1826	0.75
1827	0.812
1828	0.852
1829	0.831
1830	0.756
1831	1.044
1832	0.511
1833	0.87
1834	0.949
1835	0.814
1836	0.553
1837	0.769
1838	0.517
1839	0.991
1840	0.805
1841	0.799
1842	0.852
1843	1.035
1844	0.862
1845	0.899
1846	1.005
1847	1.094
1848	1.33
1849	1.045
1850	1.065
1851	1.038
1852	0.936
1853	0.924
1854	0.828
1855	1.064
1856	0.741
1857	0.71
1858	0.703
1859	1.039
1860	0.874
1861	0.814
1862	0.829
1863	1.11
1864	0.751
1865	1.107
1866	1.023
1867	0.835
1868	1.029
1869	0.943
1870	0.915
1871	1.081
1872	1.138
1873	1.138
1874	1.228
1875	1.285
1876	0.925
1877	1.039
1878	1.369
1879	1.314
1880	1.119
1881	1.135
1882	1.166
1883	1.062
1884	0.743
1885	1.109
1886	1.369
1887	1.037
1888	1.131
1889	1.179
1890	1.202
1891	1.084
1892	1.022
1893	0.91
1894	0.938
1895	1.003
1896	1.013
1897	0.805
1898	1.03
1899	0.76
1900	0.832
1901	0.876
1902	0.887
1903	1.018
1904	1.252
1905	1.053
1906	0.965
1907	1.104
1908	1.131
1909	0.966
1910	0.994
1911	1.017
1912	1.099
1913	1.111
1914	1.205
1915	0.843
1916	1.042
1917	1.137
1918	1.113
1919	1.145
1920	1.099
1921	0.885
1922	0.958
1923	0.8
1924	0.895
1925	1.023
1926	0.829
1927	0.829
1928	0.838
1929	0.882
1930	0.906
1931	0.943
1932	1.029
1933	1.084
1934	1.063
1935	1.043
1936	1.259
1937	1.121
1938	1.338
1939	1.13
1940	1.245
1941	1.101
1942	0.846
1943	1.062
1944	1.301
1945	1.264
1946	1.048
1947	1.194
1948	1.138
1949	1.076
1950	1.113
1951	1.058
1952	0.946
1953	1.058
1954	1.033
1955	1.011
1956	0.963
1957	0.98
1958	1.165
1959	1.043
1960	1.247
1961	1.182
1962	1.028
1963	1.085
1964	0.931
1965	1.183
1966	1.197
1967	1.282
1968	0.855
1969	0.918
1970	1.021
1971	0.793
1972	0.606
1973	0.887
1974	0.731
1975	0.904
1976	0.863
1977	0.958
1978	0.97
1979	0.992
1980	0.714
1981	0.719
1982	0.745
1983	0.654