# northamerica_usa_ia014 - Backbone State Park - 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/3855
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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_usa_ia014 - Backbone State Park - Breitenmoser Tree Ring Chronology Data
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# 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: Backbone State Park
#	Location:
#	Country: United States
#	Northernmost_Latitude: 42.62
#	Southernmost_Latitude: 42.62
#	Easternmost_Longitude: -91.57
#	Westernmost_Longitude: -91.57
#	Elevation: 335 m
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# Data_Collection
#	Collection_Name: northamerica_usa_ia014B
#	Earliest_Year: 1832
#	Most_Recent_Year: 1977
#	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":"5.37093203947","T2":"14.9955166329","M1":"0.0225763889684","M2":"0.573874578813"}}
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# Species
#	Species_Name: eastern white pine
#	Species_Code: PIST
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# Chronology:
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# Variables
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# 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
1832	0.905
1833	0.975
1834	0.862
1835	0.915
1836	0.755
1837	0.771
1838	0.66
1839	0.691
1840	0.871
1841	0.758
1842	0.921
1843	0.734
1844	1.027
1845	0.916
1846	1.031
1847	1.157
1848	1.044
1849	1.054
1850	1.067
1851	0.992
1852	0.887
1853	1.036
1854	1.145
1855	0.998
1856	0.748
1857	0.839
1858	1.021
1859	0.938
1860	0.881
1861	0.891
1862	0.969
1863	1.035
1864	0.942
1865	1.139
1866	1.058
1867	0.918
1868	0.808
1869	1.476
1870	0.812
1871	0.847
1872	0.907
1873	0.618
1874	0.543
1875	0.837
1876	0.936
1877	1.121
1878	1.144
1879	0.973
1880	1.346
1881	1.196
1882	1.401
1883	1.388
1884	1.198
1885	1.55
1886	1.108
1887	0.621
1888	0.762
1889	1.173
1890	1.088
1891	1.268
1892	1.076
1893	0.699
1894	0.732
1895	0.548
1896	0.893
1897	0.845
1898	0.854
1899	1.051
1900	0.86
1901	0.623
1902	1.096
1903	1.334
1904	0.943
1905	1.334
1906	1.042
1907	1.254
1908	1.637
1909	1.072
1910	0.758
1911	0.52
1912	0.846
1913	0.813
1914	1.107
1915	1.271
1916	0.973
1917	1.105
1918	1.126
1919	0.832
1920	0.965
1921	0.829
1922	0.967
1923	0.701
1924	1.215
1925	1.402
1926	1.125
1927	0.919
1928	1.002
1929	1.033
1930	0.958
1931	0.622
1932	0.857
1933	0.663
1934	0.289
1935	0.82
1936	0.493
1937	0.576
1938	0.82
1939	0.714
1940	0.622
1941	0.77
1942	1.096
1943	0.691
1944	0.775
1945	1.197
1946	0.966
1947	1.142
1948	0.987
1949	1.028
1950	0.912
1951	0.983
1952	0.778
1953	0.988
1954	0.924
1955	1.089
1956	0.744
1957	0.888
1958	0.919
1959	0.964
1960	1.27
1961	1.061
1962	1.366
1963	1.269
1964	1.193
1965	1.103
1966	0.903
1967	0.695
1968	1.076
1969	1.215
1970	0.882
1971	1.181
1972	1.134
1973	0.923
1974	1.179
1975	1.089
1976	0.964
1977	0.734