# northamerica_usa_me018 - Ironbound Island Long Cores - Breitenmoser Tree Ring Chronology Data
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#		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.
#
#
# 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/2985
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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_me018 - Ironbound Island Long Cores - 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 VaganovÃÂ¢ÃÂÃÂShashkin 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 4ÃÂ¢ÃÂÃÂ6 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 modelÃÂ¢ÃÂÃÂs 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
#------------------
# Site_Information
#	Site_Name: Ironbound Island Long Cores
#	Location:
#	Country: United States
#	Northernmost_Latitude: 44.42
#	Southernmost_Latitude: 44.42
#	Easternmost_Longitude: -68.15
#	Westernmost_Longitude: -68.15
#	Elevation: 50 m
#--------------------
# Data_Collection
#	Collection_Name: northamerica_usa_me018B
#	Earliest_Year: 1693
#	Most_Recent_Year: 1982
#	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":"5.38758648137","T2":"15.3402309767","M1":"0.0221724242923","M2":"0.446673066129"}}
#--------------------
# 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
#
#--------------------
# Data:
# Data lines follow (have no #)
# Data line format - tab-delimited text, variable short name as header
# Missing Values: nan
#
age	trsgi
1693	0.964
1694	1.274
1695	1.19
1696	1.104
1697	1.154
1698	0.94
1699	0.79
1700	1.036
1701	1.031
1702	1.096
1703	1.08
1704	0.995
1705	1.163
1706	1.19
1707	1.278
1708	1.119
1709	1.179
1710	1.018
1711	0.73
1712	0.922
1713	0.94
1714	1.045
1715	1.073
1716	0.921
1717	0.791
1718	0.997
1719	0.993
1720	0.785
1721	0.665
1722	0.809
1723	0.665
1724	0.581
1725	0.668
1726	0.629
1727	0.678
1728	0.601
1729	0.767
1730	0.823
1731	0.676
1732	0.808
1733	1.077
1734	0.797
1735	0.654
1736	0.603
1737	0.62
1738	0.723
1739	0.784
1740	0.752
1741	0.434
1742	0.535
1743	0.551
1744	0.408
1745	0.464
1746	0.615
1747	0.622
1748	0.408
1749	0.579
1750	0.608
1751	0.608
1752	0.724
1753	0.831
1754	0.82
1755	0.721
1756	1.017
1757	0.579
1758	0.59
1759	0.629
1760	0.462
1761	0.604
1762	0.767
1763	0.872
1764	0.656
1765	0.811
1766	0.848
1767	0.811
1768	0.773
1769	0.84
1770	0.732
1771	0.986
1772	0.994
1773	0.837
1774	0.692
1775	0.811
1776	0.678
1777	0.587
1778	0.715
1779	0.697
1780	0.626
1781	0.614
1782	0.841
1783	0.75
1784	0.785
1785	0.547
1786	0.48
1787	0.422
1788	0.381
1789	0.346
1790	0.352
1791	0.267
1792	0.365
1793	0.448
1794	0.442
1795	0.431
1796	0.345
1797	0.418
1798	0.36
1799	0.277
1800	0.319
1801	0.312
1802	0.273
1803	0.343
1804	0.423
1805	0.471
1806	0.278
1807	0.431
1808	0.443
1809	0.713
1810	0.636
1811	0.952
1812	1.043
1813	1.214
1814	1.249
1815	1.46
1816	1.421
1817	1.667
1818	1.042
1819	1.108
1820	1.121
1821	1.289
1822	1.525
1823	1.516
1824	1.699
1825	1.34
1826	1.286
1827	1.116
1828	1.484
1829	1.567
1830	1.946
1831	1.141
1832	1.437
1833	1.675
1834	1.532
1835	1.554
1836	1.362
1837	1.428
1838	1.06
1839	0.998
1840	0.965
1841	0.67
1842	1.115
1843	1.068
1844	1.318
1845	1.378
1846	1.519
1847	1.159
1848	1.082
1849	0.811
1850	0.862
1851	0.937
1852	1.193
1853	0.993
1854	0.725
1855	0.727
1856	0.542
1857	0.69
1858	0.93
1859	1.088
1860	1.04
1861	0.642
1862	1.014
1863	1.023
1864	1.107
1865	1.277
1866	1.036
1867	0.898
1868	0.758
1869	0.989
1870	0.956
1871	0.966
1872	0.602
1873	0.506
1874	0.69
1875	0.807
1876	0.882
1877	0.725
1878	0.857
1879	0.948
1880	1.245
1881	1.226
1882	1.166
1883	1.136
1884	1.14
1885	0.84
1886	0.857
1887	0.771
1888	0.777
1889	0.887
1890	0.96
1891	1.037
1892	1.236
1893	1.07
1894	1.138
1895	1.095
1896	1.174
1897	1.152
1898	1.13
1899	0.999
1900	1.1
1901	0.878
1902	1.117
1903	1.268
1904	1.451
1905	1.328
1906	1.475
1907	1.334
1908	1.282
1909	1.149
1910	1.299
1911	1.099
1912	1.321
1913	1.305
1914	0.936
1915	0.56
1916	0.675
1917	0.617
1918	0.988
1919	1.102
1920	1.009
1921	1.125
1922	1.207
1923	0.97
1924	0.86
1925	0.886
1926	0.763
1927	0.889
1928	1.036
1929	1.216
1930	1.409
1931	1.048
1932	1.092
1933	1.148
1934	1.151
1935	1.037
1936	1.109
1937	0.986
1938	1.043
1939	1.143
1940	1.041
1941	1.093
1942	1.176
1943	1.043
1944	0.958
1945	1.148
1946	1.401
1947	1.269
1948	1.074
1949	0.976
1950	1.065
1951	1.004
1952	0.925
1953	1.076
1954	1.157
1955	1.195
1956	0.889
1957	0.996
1958	0.992
1959	0.755
1960	0.774
1961	0.755
1962	0.856
1963	0.853
1964	0.64
1965	0.69
1966	0.512
1967	0.654
1968	0.545
1969	0.664
1970	0.756
1971	0.878
1972	0.832
1973	0.756
1974	0.837
1975	0.855
1976	0.835
1977	0.56
1978	0.663
1979	0.622
1980	0.693
1981	0.539
1982	0.921