# northamerica_usa_mi020 - Mountain Lake Michigan - 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/6175
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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_mi020 - Mountain Lake Michigan - 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: Mountain Lake Michigan
#	Location:
#	Country: United States
#	Northernmost_Latitude: 46.87
#	Southernmost_Latitude: 46.87
#	Easternmost_Longitude: -87.9
#	Westernmost_Longitude: -87.9
#	Elevation: 258 m
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# Data_Collection
#	Collection_Name: northamerica_usa_mi020B
#	Earliest_Year: 1750
#	Most_Recent_Year: 2007
#	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":"3.72648360913","T2":"13.4077283278","M1":"0.0225726880699","M2":"0.549232220897"}}
#--------------------
# 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
1750	1.272
1751	0.965
1752	0.942
1753	0.984
1754	0.938
1755	1.045
1756	1.076
1757	0.937
1758	0.972
1759	1.06
1760	1.084
1761	0.949
1762	0.938
1763	0.875
1764	1.002
1765	1.055
1766	0.982
1767	0.992
1768	0.974
1769	0.922
1770	0.908
1771	0.902
1772	0.787
1773	0.789
1774	0.826
1775	0.854
1776	0.693
1777	0.861
1778	1.124
1779	1.057
1780	0.947
1781	1.021
1782	1.174
1783	1.127
1784	1.166
1785	1.254
1786	1.365
1787	1.04
1788	1.033
1789	1.095
1790	0.962
1791	0.756
1792	0.777
1793	0.953
1794	0.827
1795	0.694
1796	0.964
1797	0.899
1798	0.864
1799	0.886
1800	0.959
1801	1.082
1802	1.256
1803	1.016
1804	0.857
1805	0.927
1806	0.887
1807	0.998
1808	0.798
1809	0.745
1810	0.797
1811	0.817
1812	0.986
1813	1.128
1814	0.812
1815	0.901
1816	0.674
1817	0.649
1818	0.564
1819	0.838
1820	0.763
1821	0.626
1822	0.825
1823	0.851
1824	0.724
1825	0.867
1826	0.619
1827	0.82
1828	0.954
1829	0.856
1830	0.947
1831	0.954
1832	1.119
1833	1.238
1834	1.225
1835	1.112
1836	1.121
1837	0.864
1838	1.064
1839	1.095
1840	0.768
1841	0.856
1842	1.023
1843	1.059
1844	1.201
1845	1.065
1846	1.053
1847	1.043
1848	1.085
1849	0.869
1850	0.978
1851	1.064
1852	1.123
1853	1.262
1854	1.238
1855	1.097
1856	1.152
1857	0.946
1858	1.003
1859	1.117
1860	1.099
1861	1.117
1862	1.005
1863	1.061
1864	0.874
1865	1.037
1866	0.887
1867	0.871
1868	0.842
1869	0.903
1870	0.818
1871	0.85
1872	1.098
1873	1.119
1874	0.983
1875	0.784
1876	0.838
1877	0.785
1878	1.052
1879	0.793
1880	0.812
1881	0.764
1882	0.798
1883	0.796
1884	0.774
1885	0.884
1886	0.684
1887	0.72
1888	0.71
1889	0.889
1890	0.796
1891	0.794
1892	0.799
1893	0.719
1894	0.802
1895	0.833
1896	0.938
1897	0.797
1898	0.956
1899	1.122
1900	1.141
1901	1.228
1902	1.486
1903	1.434
1904	1.407
1905	1.439
1906	1.61
1907	1.039
1908	1.172
1909	0.912
1910	1.024
1911	0.964
1912	1.126
1913	1.082
1914	1.106
1915	1.362
1916	1.529
1917	1.302
1918	1.685
1919	1.081
1920	1.012
1921	0.876
1922	1.037
1923	0.915
1924	0.821
1925	1.077
1926	1.114
1927	1.138
1928	1.062
1929	1.312
1930	1.061
1931	1.109
1932	1.125
1933	0.831
1934	0.794
1935	1.043
1936	1.061
1937	0.698
1938	0.636
1939	0.733
1940	0.831
1941	0.738
1942	0.994
1943	0.899
1944	0.802
1945	0.995
1946	1.143
1947	0.951
1948	0.809
1949	0.744
1950	0.731
1951	0.78
1952	1.059
1953	1.128
1954	0.958
1955	1.173
1956	1.091
1957	0.79
1958	0.863
1959	1.09
1960	0.981
1961	0.951
1962	0.871
1963	0.893
1964	0.936
1965	1.127
1966	1.042
1967	1.14
1968	1.018
1969	0.891
1970	0.891
1971	0.996
1972	0.906
1973	0.769
1974	0.748
1975	0.813
1976	0.703
1977	0.704
1978	0.773
1979	0.938
1980	1.025
1981	1.031
1982	0.994
1983	1.063
1984	1.124
1985	1.133
1986	1.104
1987	1.08
1988	0.773
1989	0.808
1990	0.883
1991	0.965
1992	0.902
1993	0.81
1994	0.86
1995	1.021
1996	0.817
1997	0.679
1998	0.967
1999	1.002
2000	1.139
2001	1.323
2002	1.318
2003	1.005
2004	1.049
2005	1.14
2006	1.009
2007	0.863