# northamerica_usa_pa002 - Bear Run - 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/2959
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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_usa_pa002 - Bear Run - 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: Bear Run
#	Location:
#	Country: United States
#	Northernmost_Latitude: 40.88
#	Southernmost_Latitude: 40.88
#	Easternmost_Longitude: -77.32
#	Westernmost_Longitude: -77.32
#	Elevation: 400 m
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# Data_Collection
#	Collection_Name: northamerica_usa_pa002B
#	Earliest_Year: 1726
#	Most_Recent_Year: 1981
#	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":"4.55478777737","T2":"17.3929517465","M1":"0.0226856974274","M2":"0.369263372186"}}
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# Species
#	Species_Name: eastern hemlock
#	Species_Code: TSCA
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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
1726	0.699
1727	0.69
1728	0.844
1729	0.685
1730	0.733
1731	0.825
1732	0.633
1733	0.59
1734	0.684
1735	0.409
1736	0.527
1737	0.566
1738	0.613
1739	0.792
1740	0.852
1741	0.577
1742	0.606
1743	0.734
1744	0.68
1745	0.818
1746	0.712
1747	0.912
1748	0.653
1749	0.622
1750	0.811
1751	0.817
1752	0.99
1753	0.919
1754	1.269
1755	0.589
1756	0.972
1757	0.716
1758	0.694
1759	0.869
1760	0.937
1761	0.752
1762	0.797
1763	0.869
1764	0.927
1765	1.008
1766	1.244
1767	1.116
1768	1.229
1769	1.189
1770	1.003
1771	1.455
1772	1.216
1773	1.364
1774	1.088
1775	1.341
1776	1.264
1777	1.502
1778	1.301
1779	1.397
1780	1.248
1781	1.34
1782	1.249
1783	1.137
1784	0.994
1785	1.063
1786	1.203
1787	0.933
1788	1.115
1789	1.062
1790	1.12
1791	1.148
1792	1.003
1793	1.277
1794	1.097
1795	1.155
1796	1.032
1797	1.263
1798	1.098
1799	0.804
1800	0.982
1801	1.172
1802	1.203
1803	0.99
1804	0.944
1805	0.89
1806	1.049
1807	0.88
1808	1.096
1809	1.1
1810	1.084
1811	1.027
1812	1.162
1813	1.076
1814	0.894
1815	1.23
1816	1.125
1817	1.177
1818	1.055
1819	0.658
1820	0.741
1821	0.823
1822	0.703
1823	0.644
1824	0.799
1825	0.905
1826	0.737
1827	0.896
1828	1.126
1829	1.097
1830	1.31
1831	1.411
1832	1.261
1833	1.128
1834	1.252
1835	1.049
1836	0.994
1837	0.938
1838	1.084
1839	0.639
1840	0.893
1841	0.89
1842	1.011
1843	0.813
1844	0.725
1845	0.821
1846	0.85
1847	0.983
1848	1.122
1849	0.934
1850	0.905
1851	1.143
1852	1.187
1853	0.79
1854	0.921
1855	0.747
1856	0.656
1857	1.04
1858	1.224
1859	1.027
1860	0.902
1861	0.922
1862	0.956
1863	0.9
1864	0.831
1865	0.617
1866	0.751
1867	0.909
1868	1.031
1869	0.839
1870	0.818
1871	0.964
1872	0.745
1873	0.649
1874	0.747
1875	0.728
1876	1.001
1877	0.879
1878	0.997
1879	0.88
1880	0.917
1881	0.778
1882	0.923
1883	0.925
1884	1.353
1885	1.261
1886	1.823
1887	1.449
1888	0.998
1889	1.559
1890	1.315
1891	1.276
1892	1.433
1893	1.106
1894	1.203
1895	0.752
1896	0.786
1897	1.184
1898	1.248
1899	1.036
1900	0.898
1901	0.882
1902	1.204
1903	1.383
1904	1.342
1905	1.099
1906	1.274
1907	0.992
1908	1.139
1909	0.934
1910	0.833
1911	0.883
1912	0.737
1913	1.04
1914	0.825
1915	0.747
1916	0.805
1917	0.928
1918	0.774
1919	0.968
1920	0.772
1921	0.976
1922	0.924
1923	0.783
1924	0.609
1925	1.108
1926	0.72
1927	0.836
1928	1.162
1929	1.057
1930	0.939
1931	0.827
1932	0.849
1933	0.881
1934	0.708
1935	0.933
1936	0.752
1937	0.801
1938	0.944
1939	0.985
1940	0.643
1941	0.655
1942	0.759
1943	0.917
1944	0.669
1945	0.691
1946	1.104
1947	1.075
1948	0.801
1949	1.094
1950	0.889
1951	1.149
1952	0.727
1953	0.705
1954	0.962
1955	0.944
1956	1.105
1957	1.157
1958	0.815
1959	1.044
1960	0.599
1961	1.429
1962	0.951
1963	1.057
1964	1.059
1965	0.775
1966	0.619
1967	0.783
1968	0.623
1969	0.838
1970	0.926
1971	0.948
1972	0.577
1973	0.919
1974	0.769
1975	1.194
1976	1.127
1977	0.901
1978	0.852
1979	1.124
1980	0.942
1981	1.088