# northamerica_usa_mi008 - Presque Isle River - 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/3014
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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_mi008 - Presque Isle River - 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: Presque Isle River
#	Location:
#	Country: United States
#	Northernmost_Latitude: 46.72
#	Southernmost_Latitude: 46.72
#	Easternmost_Longitude: -89.97
#	Westernmost_Longitude: -89.97
#	Elevation: 200 m
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# Data_Collection
#	Collection_Name: northamerica_usa_mi008B
#	Earliest_Year: 1730
#	Most_Recent_Year: 1983
#	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":"3.57288734222","T2":"13.7858536739","M1":"0.0228103052936","M2":"0.586966463592"}}
#--------------------
# Species
#	Species_Name: eastern white pine
#	Species_Code: PIST
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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
1730	0.709
1731	0.616
1732	0.684
1733	0.719
1734	0.963
1735	1.039
1736	0.78
1737	0.83
1738	0.933
1739	0.67
1740	0.772
1741	0.609
1742	0.567
1743	1.052
1744	0.902
1745	1.362
1746	1.642
1747	1.345
1748	1.275
1749	1.07
1750	1.399
1751	1.149
1752	1.018
1753	1.04
1754	0.968
1755	1.279
1756	1.136
1757	1.059
1758	1.232
1759	1.252
1760	1.176
1761	1.321
1762	1.496
1763	1.206
1764	1.223
1765	1.204
1766	1.08
1767	1.237
1768	0.979
1769	0.98
1770	1.025
1771	1.087
1772	0.851
1773	1.011
1774	0.896
1775	1.163
1776	0.652
1777	1.022
1778	1.079
1779	0.967
1780	1.043
1781	0.978
1782	1.117
1783	1.236
1784	1.266
1785	0.963
1786	1.044
1787	0.839
1788	0.844
1789	0.962
1790	0.964
1791	1.009
1792	1.016
1793	1.237
1794	1.121
1795	1.051
1796	1.219
1797	1.099
1798	0.923
1799	1.096
1800	0.981
1801	1.047
1802	1.211
1803	0.959
1804	0.76
1805	0.739
1806	0.833
1807	0.91
1808	0.71
1809	0.644
1810	0.883
1811	0.824
1812	1.24
1813	1.176
1814	1.006
1815	0.886
1816	1.12
1817	0.728
1818	0.949
1819	1.347
1820	1.373
1821	0.954
1822	1.336
1823	1.188
1824	1.056
1825	1.353
1826	0.727
1827	1.066
1828	1.074
1829	1.295
1830	1.102
1831	0.886
1832	0.74
1833	1.05
1834	1.117
1835	1.282
1836	1.24
1837	1.044
1838	1.154
1839	0.953
1840	0.885
1841	0.785
1842	0.72
1843	1.025
1844	0.957
1845	1.035
1846	1.041
1847	1.282
1848	1.282
1849	1.175
1850	1.259
1851	1.285
1852	0.906
1853	0.972
1854	1.091
1855	1.194
1856	1.274
1857	0.817
1858	1.127
1859	1.158
1860	0.958
1861	0.939
1862	0.909
1863	1.076
1864	1.074
1865	1.059
1866	0.761
1867	1.008
1868	0.913
1869	0.913
1870	0.886
1871	1.151
1872	1.026
1873	1.101
1874	1.018
1875	0.808
1876	1.036
1877	1.023
1878	1.073
1879	1.095
1880	0.755
1881	0.819
1882	1.152
1883	0.953
1884	0.964
1885	1.143
1886	1.029
1887	1.139
1888	0.939
1889	1.22
1890	1.243
1891	1.208
1892	1.105
1893	0.786
1894	0.646
1895	0.872
1896	0.915
1897	0.914
1898	1.051
1899	1.275
1900	1.242
1901	1.163
1902	1.409
1903	1.384
1904	1.145
1905	1.377
1906	1.457
1907	0.893
1908	1.486
1909	1.012
1910	0.885
1911	1.099
1912	1.061
1913	1.245
1914	1.308
1915	1.165
1916	1.153
1917	1.124
1918	1.082
1919	0.879
1920	0.904
1921	0.887
1922	0.862
1923	0.803
1924	0.626
1925	0.666
1926	0.737
1927	0.714
1928	0.973
1929	1.116
1930	1.061
1931	0.882
1932	1.231
1933	0.787
1934	0.622
1935	0.975
1936	0.594
1937	0.747
1938	0.983
1939	1.063
1940	1.258
1941	1.181
1942	1.691
1943	0.82
1944	1.115
1945	0.983
1946	0.926
1947	1.05
1948	0.546
1949	0.929
1950	0.872
1951	0.669
1952	0.609
1953	0.626
1954	0.668
1955	0.771
1956	0.664
1957	0.573
1958	0.85
1959	0.845
1960	0.808
1961	0.756
1962	0.679
1963	0.477
1964	0.674
1965	0.718
1966	0.446
1967	0.766
1968	0.826
1969	0.693
1970	0.644
1971	0.631
1972	0.583
1973	0.726
1974	0.664
1975	0.916
1976	0.645
1977	0.448
1978	0.678
1979	0.562
1980	0.826
1981	0.966
1982	0.777
1983	0.965