# northamerica_usa_mn017 - Itasca - 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/4977
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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_mn017 - Itasca - 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: Itasca
#	Location:
#	Country: United States
#	Northernmost_Latitude: 47.22
#	Southernmost_Latitude: 47.22
#	Easternmost_Longitude: -95.22
#	Westernmost_Longitude: -95.22
#	Elevation: 503 m
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# Data_Collection
#	Collection_Name: northamerica_usa_mn017B
#	Earliest_Year: 1714
#	Most_Recent_Year: 1982
#	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":"3.64862755375","T2":"15.2614213853","M1":"0.0223708536886","M2":"0.548070629974"}}
#--------------------
# 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
1714	1.187
1715	1.142
1716	1.061
1717	0.984
1718	0.62
1719	1.034
1720	0.977
1721	0.909
1722	0.928
1723	1.211
1724	1.025
1725	0.889
1726	1.008
1727	1.22
1728	1.044
1729	1.339
1730	1.123
1731	0.982
1732	1.064
1733	1.105
1734	1.212
1735	1.008
1736	0.758
1737	0.729
1738	0.967
1739	0.77
1740	1.068
1741	0.975
1742	1.053
1743	0.799
1744	1.079
1745	1.115
1746	1.155
1747	1.153
1748	1.22
1749	1.063
1750	1.038
1751	0.87
1752	0.923
1753	0.959
1754	1.037
1755	1.11
1756	0.841
1757	0.739
1758	0.769
1759	0.899
1760	0.913
1761	1.085
1762	1.034
1763	1.02
1764	1.074
1765	1.243
1766	0.933
1767	1.045
1768	1.002
1769	0.824
1770	0.783
1771	0.918
1772	0.73
1773	0.636
1774	0.736
1775	1.003
1776	0.834
1777	0.812
1778	1.09
1779	1.044
1780	1.079
1781	1.161
1782	1.156
1783	1.174
1784	1.204
1785	1.269
1786	1.303
1787	1.264
1788	1.181
1789	1.082
1790	0.969
1791	0.876
1792	0.982
1793	1.079
1794	0.919
1795	0.81
1796	0.937
1797	0.913
1798	0.742
1799	0.844
1800	0.781
1801	1.046
1802	1.289
1803	1.417
1804	1.47
1805	1.157
1806	0.923
1807	1.045
1808	0.964
1809	0.836
1810	0.867
1811	0.846
1812	0.946
1813	1.009
1814	1.047
1815	1.042
1816	1.119
1817	0.801
1818	0.829
1819	0.889
1820	0.922
1821	0.886
1822	1.06
1823	0.987
1824	1.034
1825	0.935
1826	0.977
1827	1.1
1828	1.249
1829	1.36
1830	1.23
1831	1.183
1832	1.058
1833	1.259
1834	1.477
1835	1.29
1836	1.023
1837	0.996
1838	0.964
1839	0.95
1840	0.862
1841	0.748
1842	0.866
1843	0.761
1844	0.783
1845	0.797
1846	0.809
1847	0.727
1848	0.923
1849	0.922
1850	0.826
1851	0.689
1852	0.775
1853	0.852
1854	0.794
1855	0.92
1856	0.984
1857	0.937
1858	0.983
1859	0.864
1860	1.004
1861	0.986
1862	0.834
1863	0.33
1864	0.597
1865	0.592
1866	0.57
1867	0.69
1868	0.897
1869	1.048
1870	1.285
1871	1.273
1872	1.609
1873	1.46
1874	1.469
1875	1.222
1876	1.003
1877	1.122
1878	1.205
1879	0.844
1880	0.765
1881	0.9
1882	0.852
1883	0.792
1884	0.769
1885	0.924
1886	0.765
1887	1.001
1888	0.919
1889	0.87
1890	0.988
1891	1.012
1892	0.886
1893	0.784
1894	0.974
1895	1.043
1896	1.028
1897	1.118
1898	0.936
1899	0.974
1900	0.938
1901	0.815
1902	0.92
1903	0.919
1904	0.881
1905	0.949
1906	1.075
1907	0.964
1908	0.823
1909	0.757
1910	0.59
1911	0.565
1912	0.828
1913	0.91
1914	0.837
1915	1.026
1916	1.165
1917	0.942
1918	1.079
1919	1.07
1920	0.975
1921	0.926
1922	0.986
1923	0.822
1924	0.726
1925	0.819
1926	0.755
1927	0.864
1928	0.887
1929	0.888
1930	0.906
1931	0.959
1932	0.923
1933	0.793
1934	0.616
1935	0.944
1936	0.656
1937	0.607
1938	0.758
1939	0.563
1940	0.578
1941	0.691
1942	0.96
1943	0.607
1944	0.731
1945	1.147
1946	1.175
1947	1.238
1948	1.088
1949	1.173
1950	1.009
1951	1.193
1952	1.388
1953	1.126
1954	1.135
1955	1.2
1956	1.009
1957	1.102
1958	0.898
1959	1.193
1960	1.083
1961	0.985
1962	0.993
1963	1.014
1964	1.007
1965	1.34
1966	1.318
1967	1.236
1968	1.11
1969	1.241
1970	0.845
1971	1.075
1972	1.357
1973	1.253
1974	0.999
1975	1.264
1976	1.017
1977	0.993
1978	1.047
1979	0.824
1980	0.706
1981	1.105
1982	0.984