# northamerica_usa_wa029 - Butte Camp - Breitenmoser Tree Ring Chronology Data
#-----------------------------------------------------------------------
#		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/2882
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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_wa029 - Butte Camp - 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: Butte Camp
#	Location:
#	Country: United States
#	Northernmost_Latitude: 46.17
#	Southernmost_Latitude: 46.17
#	Easternmost_Longitude: -122.2
#	Westernmost_Longitude: -122.2
#	Elevation: 1300 m
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# Data_Collection
#	Collection_Name: northamerica_usa_wa029B
#	Earliest_Year: 1773
#	Most_Recent_Year: 1976
#	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":"6.05602402298","T2":"18.186227412","M1":"0.022582955164","M2":"0.372097284996"}}
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# Species
#	Species_Name: noble fir
#	Species_Code: ABPR
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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)
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##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
1773	1.174
1774	0.939
1775	0.709
1776	0.988
1777	0.953
1778	1.116
1779	1.216
1780	1.206
1781	0.886
1782	0.882
1783	0.97
1784	1.125
1785	0.889
1786	1.224
1787	0.75
1788	1.345
1789	1.199
1790	1.027
1791	1.31
1792	0.785
1793	0.991
1794	1.146
1795	0.974
1796	0.841
1797	0.838
1798	0.943
1799	0.619
1800	0.878
1801	0.857
1802	1.348
1803	1.016
1804	1.21
1805	1.056
1806	0.898
1807	1.231
1808	1.037
1809	1.075
1810	0.954
1811	1.105
1812	1.132
1813	0.865
1814	1.302
1815	1.011
1816	1.289
1817	1.292
1818	1.099
1819	0.935
1820	1.007
1821	1.041
1822	1.058
1823	0.702
1824	0.649
1825	0.995
1826	0.976
1827	0.895
1828	0.966
1829	1.119
1830	0.919
1831	1.065
1832	0.858
1833	1.189
1834	1.195
1835	0.98
1836	0.875
1837	0.89
1838	1.029
1839	0.995
1840	0.729
1841	0.922
1842	0.751
1843	0.872
1844	0.758
1845	0.995
1846	1.13
1847	1.009
1848	1.276
1849	0.886
1850	0.861
1851	1.247
1852	0.925
1853	1.119
1854	1.043
1855	1.242
1856	0.994
1857	1.269
1858	1.212
1859	1.263
1860	1.706
1861	1.467
1862	1.296
1863	1.472
1864	1.03
1865	0.969
1866	1.01
1867	0.897
1868	1.091
1869	0.777
1870	0.704
1871	0.666
1872	0.62
1873	0.959
1874	1.064
1875	1.089
1876	0.684
1877	1.061
1878	1.192
1879	1.271
1880	0.837
1881	1.122
1882	1.093
1883	1.039
1884	0.782
1885	0.838
1886	0.756
1887	0.604
1888	0.76
1889	0.652
1890	0.606
1891	0.835
1892	0.954
1893	1.011
1894	1.127
1895	1.376
1896	1.01
1897	1.003
1898	0.906
1899	0.637
1900	0.904
1901	1.003
1902	0.88
1903	0.973
1904	1.235
1905	0.972
1906	0.906
1907	0.788
1908	0.8
1909	0.756
1910	0.947
1911	0.984
1912	1.013
1913	1.198
1914	1.641
1915	1.224
1916	0.997
1917	1.062
1918	0.803
1919	0.886
1920	1.001
1921	0.939
1922	1.238
1923	1.155
1924	0.702
1925	0.728
1926	0.769
1927	0.706
1928	0.862
1929	0.875
1930	0.834
1931	0.694
1932	0.528
1933	0.875
1934	1.028
1935	0.815
1936	0.77
1937	0.74
1938	0.782
1939	0.707
1940	0.747
1941	0.771
1942	0.691
1943	0.901
1944	1.091
1945	0.886
1946	1.045
1947	1.33
1948	1.145
1949	1.3
1950	1.304
1951	1.283
1952	1.006
1953	0.732
1954	1.237
1955	1.304
1956	1.245
1957	1.495
1958	1.436
1959	0.804
1960	1.136
1961	1.042
1962	0.78
1963	0.961
1964	0.936
1965	1.174
1966	0.997
1967	0.975
1968	0.73
1969	0.852
1970	0.953
1971	0.527
1972	0.905
1973	0.863
1974	0.473
1975	0.83
1976	0.508