# northamerica_usa_il014 - Giant City State Park - 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.
#
#
# 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/3159
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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_il014 - Giant City 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 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: Giant City State Park
#	Location:
#	Country: United States
#	Northernmost_Latitude: 37.6
#	Southernmost_Latitude: 37.6
#	Easternmost_Longitude: -89.2
#	Westernmost_Longitude: -89.2
#	Elevation: 160 m
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# Data_Collection
#	Collection_Name: northamerica_usa_il014B
#	Earliest_Year: 1719
#	Most_Recent_Year: 1981
#	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":"5.3471012123","T2":"17.9134219894","M1":"0.0225175528994","M2":"0.539449707525"}}
#--------------------
# Species
#	Species_Name: white oak
#	Species_Code: QUAL
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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
#
#--------------------
# Data:
# Data lines follow (have no #)
# Data line format - tab-delimited text, variable short name as header
# Missing Values: nan
#
age	trsgi
1719	0.644
1720	0.928
1721	0.8
1722	0.881
1723	0.682
1724	0.647
1725	0.819
1726	0.795
1727	0.855
1728	0.658
1729	1.116
1730	0.995
1731	0.75
1732	0.924
1733	0.86
1734	0.887
1735	0.835
1736	0.472
1737	0.717
1738	0.78
1739	1.145
1740	1.088
1741	1.369
1742	1.398
1743	0.963
1744	0.825
1745	1.339
1746	1.093
1747	1.259
1748	1.133
1749	0.77
1750	1.096
1751	0.849
1752	0.87
1753	0.781
1754	1.138
1755	0.875
1756	1.276
1757	0.816
1758	0.83
1759	1.291
1760	0.669
1761	1.058
1762	0.779
1763	0.862
1764	0.976
1765	1.141
1766	1.062
1767	0.797
1768	1.264
1769	1.221
1770	0.939
1771	0.912
1772	0.964
1773	0.741
1774	0.437
1775	1.315
1776	1.392
1777	1.017
1778	1.752
1779	1.604
1780	1.524
1781	1.492
1782	1.221
1783	1.266
1784	0.983
1785	0.909
1786	0.838
1787	1.291
1788	1.255
1789	1.148
1790	1.273
1791	1.444
1792	1.104
1793	0.996
1794	0.956
1795	1.078
1796	0.9
1797	1.221
1798	1.272
1799	0.745
1800	0.961
1801	0.712
1802	0.978
1803	0.677
1804	0.794
1805	0.739
1806	0.695
1807	0.98
1808	0.954
1809	0.908
1810	0.893
1811	0.939
1812	0.976
1813	0.884
1814	0.846
1815	0.437
1816	0.484
1817	0.838
1818	0.964
1819	1.252
1820	0.82
1821	1.019
1822	1.036
1823	1.041
1824	0.831
1825	0.815
1826	0.682
1827	0.913
1828	0.93
1829	0.731
1830	0.809
1831	0.863
1832	0.911
1833	0.834
1834	0.582
1835	0.827
1836	0.952
1837	1.027
1838	0.713
1839	0.776
1840	0.813
1841	0.669
1842	0.893
1843	0.775
1844	0.892
1845	1.015
1846	0.816
1847	0.782
1848	0.764
1849	0.788
1850	0.756
1851	0.731
1852	0.808
1853	0.571
1854	0.859
1855	0.834
1856	0.937
1857	0.842
1858	0.8
1859	0.827
1860	1.046
1861	0.853
1862	0.91
1863	0.957
1864	0.722
1865	0.86
1866	1.042
1867	0.864
1868	0.889
1869	1.176
1870	1.076
1871	0.975
1872	0.907
1873	0.947
1874	0.666
1875	1.209
1876	1.3
1877	0.978
1878	0.973
1879	0.774
1880	1.189
1881	1.21
1882	1.634
1883	1.521
1884	1.266
1885	0.896
1886	0.998
1887	0.873
1888	0.997
1889	1.336
1890	1.001
1891	1.255
1892	1.368
1893	1.218
1894	1.025
1895	1.143
1896	1.147
1897	1.191
1898	1.148
1899	1.056
1900	1.085
1901	0.852
1902	0.922
1903	1.173
1904	1.135
1905	1.062
1906	0.993
1907	1.292
1908	1.117
1909	1.44
1910	1.519
1911	0.847
1912	1.802
1913	1.08
1914	0.736
1915	1.447
1916	1.4
1917	1.169
1918	0.782
1919	1.221
1920	1.1
1921	0.968
1922	1.117
1923	1.114
1924	1.394
1925	1.0
1926	0.854
1927	1.311
1928	1.278
1929	1.09
1930	0.933
1931	0.89
1932	0.96
1933	1.029
1934	0.846
1935	1.076
1936	0.702
1937	1.009
1938	1.261
1939	0.901
1940	0.835
1941	0.667
1942	0.901
1943	0.875
1944	0.773
1945	1.14
1946	0.994
1947	1.033
1948	1.031
1949	0.978
1950	0.967
1951	1.339
1952	0.814
1953	0.808
1954	0.782
1955	1.151
1956	0.788
1957	1.022
1958	0.986
1959	0.861
1960	0.939
1961	0.848
1962	0.839
1963	0.854
1964	0.709
1965	0.938
1966	0.878
1967	0.874
1968	0.986
1969	0.99
1970	0.922
1971	0.884
1972	0.799
1973	1.003
1974	0.964
1975	0.955
1976	1.069
1977	0.836
1978	0.875
1979	0.879
1980	0.746
1981	0.598