# northamerica_usa_co635 - Cameron Pass - Breitenmoser Tree Ring Chronology Data
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#		World Data Center for Paleoclimatology, Boulder
#				and
#		NOAA Paleoclimatology Program
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# 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/5501
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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
#--------------------
# Title
#	Study_Name: northamerica_usa_co635 - Cameron 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.
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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: Cameron Pass
#	Location:
#	Country: United States
#	Northernmost_Latitude: 40.55
#	Southernmost_Latitude: 40.55
#	Easternmost_Longitude: -105.83
#	Westernmost_Longitude: -105.83
#	Elevation: 3100 m
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# Data_Collection
#	Collection_Name: northamerica_usa_co635B
#	Earliest_Year: 1768
#	Most_Recent_Year: 2003
#	Time_Unit: y_ad
#	Core_Length:
#	Notes: {"database":{"database1":"LMR","database2":"Breits"}} {"climateInterpretation":{"basis":"", "climateVariable":"M", "climateVariableDetail":"air", "interpDirection":"positive", "seasonality":"[6, 7, 8]"}}{"VSLite_parameters":{"T1":"5.36993406356","T2":"15.2685490271","M1":"0.022909353957","M2":"0.479591952969"}}
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# 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
1768	1.064
1769	0.951
1770	0.976
1771	1.113
1772	1.122
1773	1.109
1774	1.208
1775	1.153
1776	1.072
1777	1.13
1778	1.237
1779	1.053
1780	1.213
1781	0.892
1782	0.858
1783	1.182
1784	1.106
1785	0.956
1786	0.837
1787	1.05
1788	1.049
1789	1.006
1790	1.081
1791	0.932
1792	1.088
1793	0.942
1794	0.968
1795	1.087
1796	0.984
1797	0.893
1798	0.939
1799	0.953
1800	0.918
1801	0.892
1802	0.95
1803	0.849
1804	0.773
1805	0.74
1806	0.881
1807	0.912
1808	0.761
1809	0.961
1810	0.841
1811	0.774
1812	0.817
1813	0.815
1814	0.832
1815	0.835
1816	0.918
1817	0.96
1818	0.983
1819	0.745
1820	0.724
1821	0.674
1822	0.692
1823	0.738
1824	0.815
1825	0.841
1826	0.76
1827	0.713
1828	0.887
1829	0.879
1830	0.815
1831	0.905
1832	0.898
1833	1.123
1834	0.893
1835	1.014
1836	0.871
1837	1.208
1838	0.978
1839	0.94
1840	0.889
1841	0.966
1842	0.932
1843	1.136
1844	1.107
1845	0.736
1846	0.9
1847	0.99
1848	0.994
1849	1.058
1850	1.012
1851	0.865
1852	0.846
1853	0.982
1854	1.074
1855	1.064
1856	1.131
1857	0.985
1858	0.922
1859	0.952
1860	0.993
1861	1.059
1862	0.876
1863	1.064
1864	1.172
1865	0.928
1866	1.189
1867	0.999
1868	0.942
1869	0.979
1870	0.978
1871	1.019
1872	0.713
1873	1.264
1874	1.149
1875	1.021
1876	1.201
1877	1.005
1878	1.076
1879	0.995
1880	0.928
1881	1.036
1882	0.804
1883	0.863
1884	1.01
1885	1.072
1886	0.995
1887	0.853
1888	0.901
1889	1.02
1890	1.03
1891	0.9
1892	1.124
1893	0.747
1894	0.861
1895	0.9
1896	0.833
1897	1.007
1898	1.174
1899	0.982
1900	1.095
1901	1.07
1902	0.863
1903	1.064
1904	1.214
1905	1.164
1906	0.797
1907	1.139
1908	1.167
1909	1.182
1910	1.108
1911	1.111
1912	1.247
1913	1.435
1914	1.403
1915	1.169
1916	1.217
1917	1.26
1918	1.16
1919	1.191
1920	1.025
1921	1.225
1922	1.143
1923	1.109
1924	1.212
1925	1.224
1926	1.152
1927	1.211
1928	1.372
1929	1.263
1930	1.026
1931	1.129
1932	1.144
1933	1.167
1934	0.884
1935	0.929
1936	0.92
1937	0.797
1938	0.874
1939	0.911
1940	0.951
1941	0.839
1942	0.945
1943	0.912
1944	0.781
1945	0.651
1946	0.863
1947	0.806
1948	0.763
1949	0.759
1950	0.957
1951	1.101
1952	0.954
1953	0.983
1954	0.876
1955	1.01
1956	0.991
1957	0.974
1958	0.984
1959	0.812
1960	0.959
1961	0.983
1962	1.027
1963	1.05
1964	1.079
1965	1.098
1966	1.231
1967	0.974
1968	0.98
1969	0.892
1970	0.941
1971	0.943
1972	1.025
1973	1.061
1974	1.112
1975	1.044
1976	0.998
1977	0.974
1978	1.059
1979	1.023
1980	0.959
1981	0.875
1982	1.057
1983	1.069
1984	1.065
1985	0.996
1986	1.088
1987	1.074
1988	1.092
1989	0.989
1990	1.067
1991	1.1
1992	0.906
1993	1.041
1994	0.964
1995	0.827
1996	0.839
1997	0.834
1998	0.988
1999	0.883
2000	0.84
2001	0.882
2002	0.897
2003	0.84