# northamerica_usa_me010 - Elephant Mountain - 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/2949
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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_me010 - Elephant Mountain - 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: Elephant Mountain
#	Location:
#	Country: United States
#	Northernmost_Latitude: 44.77
#	Southernmost_Latitude: 44.77
#	Easternmost_Longitude: -70.77
#	Westernmost_Longitude: -70.77
#	Elevation: 930 m
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# Data_Collection
#	Collection_Name: northamerica_usa_me010B
#	Earliest_Year: 1700
#	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":"4.88430291088","T2":"18.3413189144","M1":"0.0227253481715","M2":"0.433112424106"}}
#--------------------
# Species
#	Species_Name: red spruce
#	Species_Code: PCRU
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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
1700	0.89
1701	0.898
1702	1.148
1703	0.94
1704	0.868
1705	1.167
1706	1.217
1707	0.848
1708	0.826
1709	1.019
1710	1.001
1711	0.703
1712	0.784
1713	0.646
1714	0.796
1715	0.969
1716	0.766
1717	0.772
1718	0.775
1719	0.798
1720	0.561
1721	0.664
1722	0.722
1723	0.711
1724	0.593
1725	0.728
1726	0.632
1727	0.764
1728	0.767
1729	0.922
1730	0.724
1731	0.842
1732	0.778
1733	0.578
1734	0.884
1735	0.632
1736	0.621
1737	0.516
1738	0.581
1739	0.537
1740	0.524
1741	0.288
1742	0.559
1743	0.692
1744	0.902
1745	1.224
1746	1.333
1747	1.278
1748	0.778
1749	0.782
1750	0.856
1751	0.646
1752	0.912
1753	1.137
1754	1.385
1755	1.014
1756	1.019
1757	0.867
1758	0.954
1759	1.043
1760	1.028
1761	1.198
1762	0.991
1763	0.788
1764	0.919
1765	0.804
1766	0.96
1767	0.834
1768	0.752
1769	0.876
1770	0.792
1771	0.838
1772	0.754
1773	0.875
1774	0.858
1775	1.124
1776	0.928
1777	1.238
1778	0.911
1779	0.96
1780	1.142
1781	0.937
1782	0.914
1783	0.923
1784	1.092
1785	1.185
1786	1.384
1787	1.038
1788	0.949
1789	1.031
1790	0.969
1791	0.907
1792	0.71
1793	1.081
1794	0.73
1795	0.706
1796	0.782
1797	1.01
1798	0.868
1799	0.859
1800	1.066
1801	1.099
1802	0.871
1803	1.318
1804	1.033
1805	0.663
1806	0.367
1807	0.418
1808	0.189
1809	0.391
1810	0.461
1811	0.641
1812	0.89
1813	1.109
1814	1.097
1815	1.426
1816	1.042
1817	1.321
1818	1.185
1819	1.388
1820	0.828
1821	1.104
1822	1.138
1823	0.993
1824	1.094
1825	1.431
1826	1.319
1827	1.31
1828	1.285
1829	1.357
1830	1.84
1831	1.535
1832	1.352
1833	1.573
1834	1.575
1835	1.355
1836	1.52
1837	1.182
1838	1.108
1839	1.035
1840	1.402
1841	1.065
1842	0.939
1843	1.046
1844	0.869
1845	1.424
1846	1.268
1847	0.853
1848	1.144
1849	0.755
1850	0.756
1851	0.793
1852	0.776
1853	0.808
1854	0.908
1855	1.028
1856	1.174
1857	1.062
1858	1.084
1859	1.136
1860	1.117
1861	1.234
1862	1.202
1863	1.077
1864	0.972
1865	0.929
1866	0.935
1867	0.925
1868	0.788
1869	0.658
1870	0.92
1871	0.65
1872	0.645
1873	0.741
1874	0.988
1875	0.764
1876	0.476
1877	0.492
1878	0.656
1879	1.12
1880	1.141
1881	0.802
1882	0.871
1883	0.989
1884	1.023
1885	1.035
1886	1.161
1887	0.959
1888	0.999
1889	0.845
1890	0.91
1891	1.086
1892	1.3
1893	1.219
1894	1.284
1895	1.0
1896	1.153
1897	0.83
1898	0.881
1899	0.907
1900	1.087
1901	0.985
1902	0.936
1903	1.057
1904	1.251
1905	0.974
1906	1.3
1907	0.955
1908	1.004
1909	0.777
1910	0.893
1911	0.832
1912	0.949
1913	1.216
1914	1.051
1915	0.779
1916	0.875
1917	0.886
1918	0.588
1919	0.624
1920	0.609
1921	0.684
1922	0.806
1923	0.792
1924	1.091
1925	0.9
1926	1.074
1927	1.074
1928	1.229
1929	1.038
1930	1.259
1931	1.476
1932	1.289
1933	1.2
1934	1.019
1935	0.82
1936	0.748
1937	0.978
1938	0.747
1939	1.049
1940	0.81
1941	0.964
1942	0.773
1943	0.738
1944	0.903
1945	0.8
1946	0.914
1947	1.1
1948	0.906
1949	1.111
1950	0.912
1951	0.955
1952	1.057
1953	1.074
1954	1.122
1955	1.423
1956	0.793
1957	1.057
1958	1.009
1959	1.062
1960	0.927
1961	1.223
1962	0.855
1963	1.028
1964	0.97
1965	0.957
1966	0.847
1967	0.999
1968	0.858
1969	0.806
1970	0.905
1971	0.932
1972	0.922
1973	0.726
1974	0.654
1975	0.816
1976	0.57