# northamerica_canada_cana171w - Athabasca Glacier - 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/4319
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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_cana171w - Athabasca Glacier - 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.
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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: Athabasca Glacier
#	Location:
#	Country: Canada
#	Northernmost_Latitude: 52.25
#	Southernmost_Latitude: 52.25
#	Easternmost_Longitude: -117.25
#	Westernmost_Longitude: -117.25
#	Elevation: 2000 m
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# Data_Collection
#	Collection_Name: northamerica_canada_cana171wB
#	Earliest_Year: 1736
#	Most_Recent_Year: 1994
#	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":"3.82173721828","T2":"16.7590567294","M1":"0.0221892278726","M2":"0.396381050387"}}
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# 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
1736	0.961
1737	0.734
1738	0.92
1739	0.753
1740	0.842
1741	0.801
1742	0.902
1743	0.905
1744	0.947
1745	1.043
1746	0.701
1747	0.928
1748	1.214
1749	0.891
1750	0.899
1751	0.899
1752	0.784
1753	0.929
1754	1.106
1755	0.985
1756	1.203
1757	1.065
1758	1.106
1759	0.972
1760	0.962
1761	1.086
1762	0.852
1763	1.016
1764	0.915
1765	0.932
1766	0.865
1767	0.907
1768	1.157
1769	1.142
1770	1.2
1771	1.342
1772	1.216
1773	1.35
1774	1.109
1775	1.16
1776	1.125
1777	1.124
1778	1.033
1779	0.832
1780	0.971
1781	0.984
1782	0.863
1783	1.036
1784	0.931
1785	0.955
1786	1.078
1787	1.061
1788	1.125
1789	1.058
1790	0.96
1791	1.035
1792	1.246
1793	0.982
1794	1.118
1795	1.083
1796	1.067
1797	0.942
1798	1.133
1799	0.75
1800	0.98
1801	1.231
1802	1.071
1803	1.221
1804	1.02
1805	1.067
1806	1.057
1807	0.948
1808	1.223
1809	0.999
1810	0.988
1811	1.165
1812	0.934
1813	0.994
1814	0.716
1815	0.829
1816	0.911
1817	1.07
1818	0.9
1819	0.852
1820	1.006
1821	0.87
1822	0.793
1823	0.933
1824	0.74
1825	1.016
1826	0.942
1827	0.818
1828	0.897
1829	0.999
1830	1.302
1831	1.071
1832	0.787
1833	0.941
1834	1.012
1835	1.073
1836	0.774
1837	0.854
1838	0.918
1839	1.146
1840	1.037
1841	0.917
1842	0.957
1843	0.999
1844	0.778
1845	1.016
1846	0.895
1847	0.87
1848	0.931
1849	0.834
1850	1.065
1851	1.042
1852	1.065
1853	0.878
1854	0.854
1855	0.922
1856	0.843
1857	1.141
1858	0.894
1859	1.007
1860	0.798
1861	0.824
1862	1.068
1863	1.209
1864	0.96
1865	1.009
1866	1.008
1867	0.924
1868	1.044
1869	1.059
1870	1.036
1871	0.926
1872	0.854
1873	0.802
1874	0.935
1875	0.831
1876	0.985
1877	0.882
1878	0.996
1879	1.134
1880	1.104
1881	0.974
1882	1.227
1883	1.109
1884	1.037
1885	1.079
1886	1.275
1887	0.953
1888	1.013
1889	0.81
1890	0.985
1891	1.105
1892	1.009
1893	0.791
1894	1.108
1895	1.101
1896	1.231
1897	1.146
1898	0.973
1899	0.921
1900	1.009
1901	1.002
1902	0.927
1903	1.025
1904	1.084
1905	0.983
1906	0.985
1907	1.091
1908	1.145
1909	1.145
1910	1.021
1911	1.014
1912	1.022
1913	1.125
1914	1.075
1915	0.882
1916	1.024
1917	1.211
1918	1.177
1919	0.989
1920	0.931
1921	0.872
1922	1.004
1923	0.931
1924	0.855
1925	1.008
1926	0.865
1927	0.895
1928	0.876
1929	0.697
1930	0.706
1931	0.698
1932	0.808
1933	0.987
1934	0.873
1935	0.929
1936	0.991
1937	0.936
1938	1.005
1939	0.692
1940	0.929
1941	0.847
1942	0.886
1943	1.015
1944	1.033
1945	1.06
1946	0.972
1947	0.991
1948	1.305
1949	1.061
1950	1.404
1951	1.082
1952	0.985
1953	0.995
1954	1.214
1955	1.234
1956	0.987
1957	0.931
1958	1.07
1959	1.004
1960	1.085
1961	0.953
1962	0.692
1963	0.929
1964	0.912
1965	0.923
1966	0.791
1967	1.189
1968	0.903
1969	1.104
1970	1.103
1971	0.721
1972	0.713
1973	0.909
1974	0.768
1975	0.974
1976	0.673
1977	0.995
1978	1.023
1979	0.906
1980	0.669
1981	0.841
1982	1.042
1983	1.053
1984	0.935
1985	1.032
1986	1.063
1987	1.173
1988	1.018
1989	0.942
1990	1.168
1991	0.894
1992	0.938
1993	0.948
1994	0.977