# northamerica_usa_mn019 - Itasca 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/3267
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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_mn019 - Itasca State Park - 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
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# Site_Information
#	Site_Name: Itasca State Park
#	Location:
#	Country: United States
#	Northernmost_Latitude: 47.18
#	Southernmost_Latitude: 47.18
#	Easternmost_Longitude: -95.23
#	Westernmost_Longitude: -95.23
#	Elevation: 457 m
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# Data_Collection
#	Collection_Name: northamerica_usa_mn019B
#	Earliest_Year: 1739
#	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":"3.89838847528","T2":"15.1786517736","M1":"0.0221653859964","M2":"0.519490564787"}}
#--------------------
# 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
#
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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
1739	0.939
1740	1.002
1741	0.941
1742	0.952
1743	0.865
1744	1.103
1745	0.983
1746	1.179
1747	1.256
1748	1.158
1749	1.111
1750	1.166
1751	0.988
1752	0.967
1753	0.938
1754	1.063
1755	0.991
1756	0.936
1757	0.822
1758	0.877
1759	1.015
1760	1.058
1761	1.241
1762	1.115
1763	1.106
1764	1.256
1765	1.096
1766	0.819
1767	0.944
1768	0.804
1769	0.734
1770	0.514
1771	0.492
1772	0.542
1773	0.681
1774	0.736
1775	0.889
1776	0.87
1777	1.012
1778	1.334
1779	1.286
1780	0.964
1781	1.293
1782	1.259
1783	1.421
1784	1.422
1785	1.422
1786	1.374
1787	1.339
1788	1.129
1789	1.043
1790	0.904
1791	0.867
1792	0.944
1793	0.989
1794	1.033
1795	0.81
1796	1.095
1797	0.981
1798	0.787
1799	0.883
1800	0.581
1801	0.775
1802	0.968
1803	1.179
1804	0.917
1805	0.916
1806	0.816
1807	0.921
1808	0.883
1809	0.746
1810	0.785
1811	0.813
1812	0.885
1813	0.821
1814	0.759
1815	0.789
1816	0.758
1817	0.636
1818	0.624
1819	0.651
1820	0.901
1821	0.824
1822	1.096
1823	0.973
1824	0.905
1825	0.853
1826	0.871
1827	0.996
1828	1.248
1829	1.299
1830	1.316
1831	1.303
1832	1.255
1833	1.483
1834	1.492
1835	1.064
1836	0.84
1837	0.812
1838	0.788
1839	0.934
1840	0.795
1841	0.736
1842	0.852
1843	0.849
1844	0.814
1845	0.812
1846	0.857
1847	0.801
1848	0.859
1849	0.879
1850	0.739
1851	0.688
1852	0.95
1853	0.954
1854	0.94
1855	1.035
1856	1.188
1857	1.089
1858	1.002
1859	0.875
1860	1.009
1861	1.005
1862	0.907
1863	0.441
1864	0.661
1865	0.773
1866	0.829
1867	0.89
1868	0.862
1869	0.898
1870	1.157
1871	1.118
1872	1.382
1873	1.169
1874	1.348
1875	1.269
1876	1.178
1877	1.217
1878	1.374
1879	0.886
1880	0.833
1881	0.936
1882	0.903
1883	0.763
1884	0.734
1885	0.914
1886	0.778
1887	1.044
1888	0.958
1889	1.15
1890	0.974
1891	0.974
1892	0.917
1893	0.846
1894	0.977
1895	1.154
1896	1.242
1897	1.244
1898	1.138
1899	1.071
1900	1.107
1901	0.822
1902	1.038
1903	1.14
1904	1.171
1905	1.304
1906	1.33
1907	1.037
1908	0.902
1909	0.83
1910	0.613
1911	0.62
1912	0.834
1913	1.017
1914	0.987
1915	1.224
1916	1.261
1917	1.031
1918	1.179
1919	1.091
1920	0.953
1921	0.975
1922	0.995
1923	0.749
1924	0.584
1925	0.769
1926	0.715
1927	0.799
1928	0.932
1929	0.972
1930	0.947
1931	0.994
1932	0.962
1933	0.76
1934	0.727
1935	0.943
1936	0.623
1937	0.508
1938	0.602
1939	0.507
1940	0.561
1941	0.71
1942	1.0
1943	0.621
1944	0.713
1945	1.167
1946	1.245
1947	1.146
1948	1.082
1949	1.056
1950	0.859
1951	1.07
1952	1.396
1953	1.17
1954	1.068
1955	1.352
1956	0.981
1957	0.962
1958	1.0
1959	1.444
1960	1.269
1961	1.159
1962	1.025
1963	1.051
1964	0.94
1965	1.24
1966	1.267
1967	1.177
1968	1.068
1969	1.057
1970	0.809
1971	0.97