# northamerica_usa_tn010 - Reelfoot Lake (Quake Effects After 1811) - Breitenmoser Tree Ring Chronology Data
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#		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/4932
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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_tn010 - Reelfoot Lake (Quake Effects After 1811) - 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: Reelfoot Lake (Quake Effects After 1811)
#	Location:
#	Country: United States
#	Northernmost_Latitude: 36.42
#	Southernmost_Latitude: 36.42
#	Easternmost_Longitude: -89.37
#	Westernmost_Longitude: -89.37
#	Elevation: 87 m
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# Data_Collection
#	Collection_Name: northamerica_usa_tn010B
#	Earliest_Year: 1689
#	Most_Recent_Year: 1990
#	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":"4.81299896232","T2":"17.8915502743","M1":"0.0226375193137","M2":"0.60989588856"}}
#--------------------
# Species
#	Species_Name: baldcypress
#	Species_Code: TADI
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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
1689	2.237
1690	2.012
1691	1.297
1692	1.127
1693	0.623
1694	0.852
1695	0.745
1696	0.748
1697	0.331
1698	0.626
1699	0.289
1700	0.895
1701	1.196
1702	1.154
1703	0.513
1704	0.701
1705	0.355
1706	0.782
1707	0.949
1708	0.491
1709	0.739
1710	1.517
1711	2.37
1712	1.098
1713	1.056
1714	0.774
1715	0.54
1716	0.368
1717	0.552
1718	0.499
1719	0.372
1720	0.301
1721	0.482
1722	0.374
1723	0.637
1724	0.893
1725	0.641
1726	1.363
1727	1.261
1728	1.138
1729	1.56
1730	1.462
1731	1.735
1732	1.347
1733	1.344
1734	1.425
1735	0.783
1736	0.478
1737	0.601
1738	0.876
1739	1.505
1740	1.351
1741	1.321
1742	0.817
1743	0.967
1744	0.704
1745	0.655
1746	0.65
1747	0.456
1748	0.547
1749	0.393
1750	0.658
1751	0.526
1752	0.467
1753	0.898
1754	0.934
1755	1.059
1756	0.785
1757	1.179
1758	1.448
1759	1.191
1760	0.914
1761	0.856
1762	0.335
1763	0.294
1764	0.44
1765	0.224
1766	0.343
1767	0.677
1768	1.354
1769	1.435
1770	1.43
1771	1.486
1772	1.258
1773	1.036
1774	1.542
1775	0.994
1776	1.296
1777	1.586
1778	1.061
1779	0.921
1780	0.403
1781	0.807
1782	1.029
1783	0.9
1784	0.603
1785	0.928
1786	0.627
1787	0.645
1788	0.725
1789	0.421
1790	0.476
1791	0.711
1792	0.461
1793	0.626
1794	1.025
1795	0.835
1796	0.895
1797	1.317
1798	1.077
1799	0.601
1800	0.702
1801	0.482
1802	1.032
1803	1.126
1804	1.215
1805	1.32
1806	1.302
1807	1.17
1808	1.322
1809	1.45
1810	1.171
1811	1.38
1812	2.074
1813	2.979
1814	3.972
1815	1.486
1816	1.724
1817	1.121
1818	0.708
1819	0.804
1820	0.516
1821	0.617
1822	0.421
1823	0.83
1824	0.841
1825	0.315
1826	1.05
1827	0.384
1828	0.832
1829	0.357
1830	0.464
1831	0.631
1832	0.671
1833	0.566
1834	0.329
1835	0.592
1836	0.606
1837	0.475
1838	0.351
1839	0.449
1840	0.482
1841	0.474
1842	0.663
1843	0.933
1844	0.503
1845	0.673
1846	0.815
1847	0.977
1848	1.053
1849	1.134
1850	0.92
1851	0.871
1852	0.778
1853	0.712
1854	0.804
1855	0.503
1856	0.821
1857	0.365
1858	0.719
1859	0.71
1860	0.682
1861	1.053
1862	1.384
1863	0.914
1864	0.841
1865	0.934
1866	1.317
1867	1.372
1868	0.565
1869	0.768
1870	0.858
1871	0.323
1872	0.571
1873	0.563
1874	0.543
1875	0.663
1876	1.482
1877	0.75
1878	0.899
1879	0.545
1880	1.008
1881	1.006
1882	2.364
1883	1.597
1884	1.217
1885	0.738
1886	1.196
1887	0.75
1888	1.125
1889	1.029
1890	1.382
1891	1.167
1892	1.466
1893	1.141
1894	0.911
1895	0.346
1896	0.781
1897	1.128
1898	1.006
1899	1.096
1900	0.758
1901	1.032
1902	0.684
1903	2.233
1904	0.902
1905	0.607
1906	1.2
1907	1.441
1908	1.013
1909	1.105
1910	0.774
1911	0.387
1912	1.423
1913	0.722
1914	0.815
1915	0.896
1916	0.831
1917	0.794
1918	0.422
1919	0.967
1920	1.304
1921	0.457
1922	1.53
1923	1.962
1924	0.879
1925	0.484
1926	0.865
1927	1.644
1928	1.224
1929	1.153
1930	0.65
1931	0.531
1932	1.415
1933	1.232
1934	1.071
1935	1.445
1936	0.611
1937	1.412
1938	1.034
1939	1.674
1940	0.922
1941	0.525
1942	1.093
1943	1.272
1944	0.898
1945	2.017
1946	1.03
1947	1.179
1948	0.984
1949	1.103
1950	0.838
1951	1.153
1952	0.838
1953	0.8
1954	0.774
1955	1.242
1956	0.51
1957	1.579
1958	0.739
1959	0.621
1960	0.78
1961	0.733
1962	0.557
1963	0.759
1964	0.722
1965	1.245
1966	0.719
1967	1.039
1968	0.692
1969	0.734
1970	1.073
1971	0.874
1972	0.806
1973	1.03
1974	0.914
1975	0.725
1976	1.119
1977	0.55
1978	0.892
1979	0.94
1980	0.831
1981	1.429
1982	0.719
1983	1.232
1984	1.207
1985	1.14
1986	1.618
1987	1.152
1988	1.236
1989	1.931
1990	0.925