# northamerica_usa_mi004 - Alger County - 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/2955
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# Description/Documentation lines begin with #
# Data lines have no #
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# Archive: Tree Rings
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# Contribution_Date
#	Date: 2016-01-07
#--------------------
# Title
#	Study_Name: northamerica_usa_mi004 - Alger County - 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: Alger County
#	Location:
#	Country: United States
#	Northernmost_Latitude: 46.32
#	Southernmost_Latitude: 46.32
#	Easternmost_Longitude: -86.62
#	Westernmost_Longitude: -86.62
#	Elevation: 250 m
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# Data_Collection
#	Collection_Name: northamerica_usa_mi004B
#	Earliest_Year: 1743
#	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":"3.03537670854","T2":"12.0433640711","M1":"0.0225469684408","M2":"0.578962727149"}}
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# Species
#	Species_Name: eastern hemlock
#	Species_Code: TSCA
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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
1743	0.625
1744	0.56
1745	0.686
1746	0.605
1747	0.907
1748	0.903
1749	1.027
1750	1.277
1751	0.95
1752	1.219
1753	1.025
1754	1.169
1755	0.985
1756	1.456
1757	0.7
1758	1.099
1759	1.185
1760	0.833
1761	0.92
1762	1.04
1763	0.808
1764	1.032
1765	0.999
1766	1.142
1767	0.93
1768	1.017
1769	1.008
1770	0.866
1771	0.951
1772	0.891
1773	1.128
1774	0.964
1775	1.386
1776	0.858
1777	1.275
1778	1.095
1779	1.261
1780	1.183
1781	1.084
1782	1.102
1783	1.032
1784	1.039
1785	0.941
1786	1.189
1787	1.089
1788	1.102
1789	0.761
1790	0.759
1791	0.748
1792	0.661
1793	0.897
1794	0.795
1795	0.984
1796	1.018
1797	0.843
1798	0.741
1799	0.848
1800	1.251
1801	1.254
1802	1.192
1803	1.385
1804	1.388
1805	1.47
1806	0.994
1807	1.156
1808	1.116
1809	0.975
1810	0.949
1811	0.982
1812	1.117
1813	1.016
1814	0.885
1815	1.329
1816	0.877
1817	1.207
1818	0.718
1819	0.921
1820	0.743
1821	0.6
1822	0.804
1823	1.251
1824	1.307
1825	1.349
1826	0.701
1827	0.622
1828	0.985
1829	1.292
1830	1.603
1831	1.287
1832	1.114
1833	1.189
1834	1.149
1835	1.321
1836	1.328
1837	0.893
1838	0.704
1839	0.573
1840	0.771
1841	0.623
1842	0.81
1843	0.755
1844	0.793
1845	0.806
1846	0.665
1847	0.599
1848	0.962
1849	1.04
1850	1.235
1851	1.262
1852	0.972
1853	0.721
1854	0.658
1855	0.751
1856	1.004
1857	1.038
1858	1.122
1859	1.143
1860	1.028
1861	1.26
1862	0.798
1863	0.907
1864	0.57
1865	0.546
1866	0.45
1867	0.646
1868	0.667
1869	0.551
1870	0.457
1871	0.608
1872	0.787
1873	0.558
1874	0.819
1875	0.599
1876	0.945
1877	0.776
1878	0.889
1879	0.762
1880	0.731
1881	0.529
1882	0.987
1883	0.989
1884	0.88
1885	0.934
1886	0.921
1887	0.548
1888	0.573
1889	0.871
1890	0.888
1891	0.848
1892	0.701
1893	0.17
1894	0.594
1895	0.65
1896	0.891
1897	1.157
1898	1.164
1899	0.771
1900	1.058
1901	1.406
1902	2.08
1903	2.531
1904	1.431
1905	2.219
1906	1.693
1907	1.175
1908	1.611
1909	1.048
1910	1.171
1911	0.957
1912	1.389
1913	1.718
1914	1.507
1915	1.432
1916	1.613
1917	0.945
1918	0.621
1919	0.814
1920	0.613
1921	0.792
1922	0.364
1923	0.781
1924	0.937
1925	1.076
1926	0.959
1927	0.753
1928	0.938
1929	1.219
1930	1.233
1931	0.9
1932	0.774
1933	0.937
1934	0.645
1935	0.852
1936	0.547
1937	0.568
1938	0.864
1939	0.906
1940	0.825
1941	0.886
1942	0.88
1943	0.99
1944	0.921
1945	1.197
1946	1.562
1947	1.13
1948	0.616
1949	0.909
1950	0.939
1951	1.319
1952	1.232
1953	1.286
1954	1.206
1955	1.185
1956	0.659
1957	1.073
1958	1.068
1959	1.093
1960	0.618
1961	1.239
1962	1.024
1963	1.169
1964	0.719
1965	0.76
1966	0.928
1967	0.759
1968	0.769
1969	0.754
1970	0.696
1971	0.731
1972	0.85
1973	1.146
1974	1.193
1975	1.227
1976	1.0
1977	0.717
1978	0.834
1979	0.818
1980	1.06
1981	1.206
1982	1.113
1983	1.202