# northamerica_canada_cana097 - Peyto Lake - 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/4584
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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_cana097 - Peyto Lake - 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: Peyto Lake
#	Location:
#	Country: Canada
#	Northernmost_Latitude: 51.75
#	Southernmost_Latitude: 51.75
#	Easternmost_Longitude: -116.22
#	Westernmost_Longitude: -116.22
#	Elevation: 2050 m
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# Data_Collection
#	Collection_Name: northamerica_canada_cana097B
#	Earliest_Year: 1717
#	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":"3.49280946516","T2":"16.9474708497","M1":"0.0227613386307","M2":"0.397038693036"}}
#--------------------
# 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
1717	1.29
1718	1.159
1719	0.891
1720	0.785
1721	0.986
1722	1.025
1723	0.734
1724	1.012
1725	0.91
1726	0.989
1727	1.089
1728	1.098
1729	1.144
1730	1.211
1731	0.961
1732	0.902
1733	0.884
1734	1.09
1735	1.033
1736	1.337
1737	0.799
1738	1.015
1739	0.974
1740	1.043
1741	1.129
1742	0.978
1743	0.918
1744	1.097
1745	0.977
1746	0.487
1747	0.98
1748	0.916
1749	0.951
1750	0.909
1751	0.932
1752	0.93
1753	1.015
1754	1.022
1755	0.749
1756	1.15
1757	1.018
1758	1.159
1759	0.995
1760	1.137
1761	1.072
1762	0.849
1763	1.163
1764	1.08
1765	1.117
1766	1.062
1767	1.198
1768	1.198
1769	1.233
1770	1.143
1771	1.262
1772	1.156
1773	1.458
1774	1.106
1775	1.148
1776	1.202
1777	1.084
1778	0.999
1779	0.831
1780	0.982
1781	1.28
1782	0.83
1783	1.215
1784	1.021
1785	1.043
1786	1.118
1787	1.094
1788	1.099
1789	1.132
1790	1.061
1791	1.018
1792	1.21
1793	1.117
1794	1.169
1795	1.006
1796	0.979
1797	0.918
1798	1.097
1799	0.591
1800	0.942
1801	1.102
1802	0.881
1803	1.111
1804	1.117
1805	1.086
1806	0.932
1807	0.999
1808	1.351
1809	1.095
1810	0.998
1811	1.136
1812	0.862
1813	1.079
1814	0.77
1815	0.961
1816	1.016
1817	1.116
1818	0.912
1819	0.969
1820	1.207
1821	0.989
1822	0.987
1823	0.942
1824	0.65
1825	0.846
1826	0.924
1827	0.823
1828	0.875
1829	1.093
1830	1.098
1831	1.04
1832	0.739
1833	0.965
1834	0.943
1835	1.033
1836	0.814
1837	0.776
1838	0.651
1839	1.272
1840	1.071
1841	0.936
1842	1.023
1843	1.031
1844	0.821
1845	1.139
1846	0.949
1847	0.933
1848	0.974
1849	0.844
1850	1.093
1851	0.949
1852	1.098
1853	0.814
1854	0.747
1855	1.054
1856	0.832
1857	1.099
1858	0.841
1859	1.182
1860	0.883
1861	0.911
1862	1.062
1863	1.297
1864	0.973
1865	1.191
1866	1.065
1867	0.829
1868	1.087
1869	1.035
1870	1.01
1871	1.03
1872	0.864
1873	0.794
1874	0.924
1875	1.014
1876	0.927
1877	0.864
1878	0.935
1879	0.927
1880	1.186
1881	0.712
1882	1.091
1883	1.022
1884	0.884
1885	0.916
1886	0.968
1887	0.817
1888	0.89
1889	0.693
1890	0.834
1891	0.806
1892	0.771
1893	0.843
1894	0.859
1895	0.875
1896	1.095
1897	1.068
1898	0.944
1899	0.823
1900	0.879
1901	0.969
1902	0.902
1903	1.056
1904	1.091
1905	0.887
1906	0.923
1907	0.884
1908	0.926
1909	0.982
1910	0.912
1911	0.94
1912	1.117
1913	1.082
1914	1.113
1915	0.743
1916	0.963
1917	1.026
1918	1.147
1919	1.032
1920	0.935
1921	0.626
1922	0.941
1923	0.872
1924	0.856
1925	0.902
1926	0.901
1927	0.788
1928	0.872
1929	0.662
1930	0.756
1931	0.644
1932	0.776
1933	0.943
1934	0.85
1935	1.206
1936	1.262
1937	1.045
1938	1.17
1939	0.953
1940	1.094
1941	1.08
1942	0.823
1943	0.974
1944	1.146
1945	1.358
1946	0.816
1947	1.082
1948	1.321
1949	1.166
1950	1.516
1951	1.193
1952	1.037
1953	1.194
1954	1.214
1955	1.5
1956	1.094
1957	0.987
1958	1.388
1959	1.058
1960	1.019
1961	1.035
1962	0.651
1963	0.96
1964	1.193
1965	0.935
1966	0.892
1967	1.466
1968	1.05
1969	1.151
1970	1.454
1971	0.765
1972	0.787
1973	0.898
1974	0.953
1975	1.272
1976	0.795
1977	0.992
1978	1.173
1979	1.12
1980	0.956
1981	0.941
1982	1.228
1983	1.122