# northamerica_usa_mn002 - Beyond Munker Island - 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.
#
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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/5062
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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_mn002 - Beyond Munker Island - 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: Beyond Munker Island
#	Location:
#	Country: United States
#	Northernmost_Latitude: 48.22
#	Southernmost_Latitude: 48.22
#	Easternmost_Longitude: -90.9
#	Westernmost_Longitude: -90.9
#	Elevation: 442 m
#--------------------
# Data_Collection
#	Collection_Name: northamerica_usa_mn002B
#	Earliest_Year: 1688
#	Most_Recent_Year: 1971
#	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":"3.14928214455","T2":"13.3802010659","M1":"0.0228045217449","M2":"0.599628088281"}}
#--------------------
# Species
#	Species_Name: red pine
#	Species_Code: PIRE
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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
1688	0.967
1689	0.998
1690	0.889
1691	0.946
1692	0.999
1693	1.078
1694	1.216
1695	1.282
1696	1.022
1697	0.831
1698	1.057
1699	0.792
1700	1.052
1701	0.959
1702	1.007
1703	1.272
1704	0.991
1705	1.125
1706	0.899
1707	1.093
1708	0.982
1709	0.933
1710	0.89
1711	1.033
1712	0.781
1713	0.905
1714	0.791
1715	0.987
1716	0.836
1717	0.601
1718	0.712
1719	0.742
1720	0.995
1721	0.727
1722	0.885
1723	1.033
1724	0.715
1725	0.771
1726	0.691
1727	0.598
1728	0.653
1729	0.832
1730	1.005
1731	1.017
1732	0.945
1733	0.89
1734	1.082
1735	0.946
1736	0.496
1737	0.953
1738	1.101
1739	0.471
1740	1.065
1741	0.975
1742	0.643
1743	0.935
1744	1.077
1745	1.203
1746	1.795
1747	1.929
1748	2.159
1749	1.733
1750	1.45
1751	1.354
1752	1.56
1753	1.267
1754	1.078
1755	0.899
1756	1.408
1757	1.095
1758	1.035
1759	1.195
1760	0.713
1761	0.772
1762	1.275
1763	0.97
1764	0.937
1765	1.247
1766	0.901
1767	1.366
1768	0.983
1769	1.002
1770	0.98
1771	0.765
1772	0.948
1773	0.84
1774	0.976
1775	0.985
1776	0.536
1777	1.015
1778	1.143
1779	1.016
1780	0.78
1781	1.225
1782	1.044
1783	1.146
1784	1.153
1785	0.867
1786	0.685
1787	1.261
1788	1.089
1789	1.131
1790	0.704
1791	0.822
1792	0.887
1793	1.076
1794	0.572
1795	0.663
1796	0.798
1797	0.758
1798	0.778
1799	0.975
1800	0.797
1801	0.815
1802	1.075
1803	0.999
1804	0.205
1805	0.959
1806	0.646
1807	0.545
1808	0.473
1809	0.519
1810	0.728
1811	0.813
1812	0.839
1813	0.891
1814	1.047
1815	1.125
1816	1.207
1817	1.356
1818	1.043
1819	1.494
1820	1.449
1821	0.907
1822	1.499
1823	1.114
1824	1.019
1825	1.242
1826	0.945
1827	1.082
1828	1.494
1829	0.926
1830	1.258
1831	1.208
1832	1.595
1833	1.503
1834	1.993
1835	1.063
1836	1.272
1837	1.103
1838	1.244
1839	0.925
1840	0.658
1841	0.895
1842	1.0
1843	1.031
1844	0.937
1845	0.931
1846	0.765
1847	1.034
1848	1.17
1849	1.006
1850	1.061
1851	0.868
1852	0.791
1853	0.526
1854	1.304
1855	0.791
1856	1.167
1857	1.047
1858	1.172
1859	1.235
1860	0.809
1861	0.948
1862	0.492
1863	0.579
1864	0.487
1865	0.691
1866	0.407
1867	0.678
1868	0.736
1869	0.692
1870	0.728
1871	0.484
1872	0.9
1873	0.914
1874	0.638
1875	0.467
1876	0.908
1877	0.976
1878	0.695
1879	0.566
1880	0.711
1881	0.862
1882	0.495
1883	0.618
1884	0.672
1885	0.943
1886	0.619
1887	0.912
1888	0.917
1889	0.735
1890	0.784
1891	0.732
1892	0.894
1893	0.625
1894	0.631
1895	1.178
1896	1.151
1897	1.104
1898	1.247
1899	1.468
1900	1.3
1901	1.369
1902	1.114
1903	0.785
1904	1.256
1905	1.519
1906	1.015
1907	0.956
1908	1.373
1909	0.852
1910	0.399
1911	0.7
1912	0.846
1913	0.83
1914	0.756
1915	1.034
1916	1.143
1917	1.175
1918	1.232
1919	0.945
1920	1.081
1921	0.628
1922	0.876
1923	0.796
1924	0.584
1925	1.081
1926	1.263
1927	1.169
1928	1.257
1929	0.949
1930	1.192
1931	0.871
1932	0.83
1933	1.021
1934	0.724
1935	1.1
1936	0.873
1937	0.697
1938	0.975
1939	0.96
1940	0.824
1941	0.802
1942	0.896
1943	0.679
1944	1.032
1945	1.022
1946	0.971
1947	1.083
1948	0.666
1949	1.078
1950	1.187
1951	1.051
1952	1.143
1953	1.212
1954	0.984
1955	0.972
1956	1.123
1957	1.057
1958	0.706
1959	0.847
1960	0.878
1961	0.701
1962	1.085
1963	0.947
1964	1.393
1965	1.698
1966	1.161
1967	1.327
1968	1.563
1969	1.188
1970	0.808
1971	0.874