# northamerica_usa_ar060 - Norfork Lake - 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/4909
#
# 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_ar060 - Norfork Lake - 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: Norfork Lake
#	Location:
#	Country: United States
#	Northernmost_Latitude: 36.3
#	Southernmost_Latitude: 36.3
#	Easternmost_Longitude: -92.2
#	Westernmost_Longitude: -92.2
#	Elevation: 200 m
#--------------------
# Data_Collection
#	Collection_Name: northamerica_usa_ar060B
#	Earliest_Year: 1737
#	Most_Recent_Year: 1993
#	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":"4.55713862305","T2":"17.0113080531","M1":"0.0234335501069","M2":"0.514956225109"}}
#--------------------
# Species
#	Species_Name: post oak
#	Species_Code: QUST
#--------------------
# 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
1737	0.719
1738	1.292
1739	1.116
1740	0.937
1741	0.799
1742	1.023
1743	1.04
1744	0.891
1745	1.145
1746	0.943
1747	1.415
1748	0.917
1749	0.779
1750	0.932
1751	0.748
1752	0.951
1753	0.686
1754	0.786
1755	0.914
1756	0.843
1757	0.889
1758	0.93
1759	0.912
1760	0.773
1761	0.791
1762	0.714
1763	0.74
1764	1.066
1765	0.896
1766	0.582
1767	0.832
1768	0.978
1769	1.217
1770	1.249
1771	1.116
1772	0.942
1773	1.049
1774	0.934
1775	0.922
1776	1.079
1777	1.301
1778	1.116
1779	0.905
1780	0.773
1781	0.792
1782	0.809
1783	0.607
1784	0.719
1785	0.766
1786	1.071
1787	1.115
1788	1.114
1789	1.137
1790	0.919
1791	0.964
1792	0.822
1793	0.885
1794	0.853
1795	1.003
1796	1.324
1797	1.239
1798	1.016
1799	0.916
1800	0.977
1801	0.597
1802	0.79
1803	0.798
1804	0.893
1805	1.129
1806	0.838
1807	1.075
1808	0.797
1809	0.925
1810	0.957
1811	1.159
1812	0.822
1813	0.844
1814	0.752
1815	0.829
1816	0.774
1817	0.848
1818	0.999
1819	1.073
1820	0.973
1821	1.1
1822	1.115
1823	1.206
1824	1.021
1825	0.835
1826	1.289
1827	1.213
1828	0.959
1829	0.868
1830	0.986
1831	0.972
1832	0.909
1833	1.216
1834	0.947
1835	1.014
1836	1.247
1837	1.189
1838	0.994
1839	0.8
1840	1.262
1841	0.817
1842	0.999
1843	1.189
1844	1.084
1845	0.968
1846	0.977
1847	0.844
1848	0.854
1849	0.998
1850	0.959
1851	0.749
1852	0.961
1853	0.878
1854	1.069
1855	0.706
1856	0.891
1857	0.969
1858	0.988
1859	0.749
1860	1.041
1861	0.928
1862	0.854
1863	0.9
1864	0.852
1865	0.886
1866	0.901
1867	0.897
1868	0.764
1869	1.047
1870	0.778
1871	0.92
1872	0.861
1873	1.013
1874	0.856
1875	0.798
1876	1.302
1877	1.054
1878	1.161
1879	0.876
1880	0.851
1881	0.844
1882	1.25
1883	1.281
1884	1.001
1885	0.827
1886	0.896
1887	1.009
1888	0.842
1889	0.939
1890	0.978
1891	1.006
1892	1.39
1893	1.294
1894	1.295
1895	1.177
1896	1.027
1897	1.078
1898	1.08
1899	1.005
1900	0.79
1901	0.752
1902	0.803
1903	1.062
1904	0.875
1905	0.957
1906	1.28
1907	0.893
1908	1.128
1909	1.261
1910	1.332
1911	0.799
1912	1.468
1913	0.978
1914	1.027
1915	1.481
1916	1.235
1917	1.526
1918	1.231
1919	1.228
1920	1.404
1921	1.18
1922	1.155
1923	1.38
1924	1.598
1925	1.062
1926	0.976
1927	0.864
1928	1.346
1929	1.268
1930	0.917
1931	0.937
1932	0.961
1933	0.834
1934	0.792
1935	1.114
1936	0.725
1937	0.908
1938	0.783
1939	0.88
1940	0.777
1941	0.716
1942	0.861
1943	0.84
1944	0.781
1945	1.058
1946	0.934
1947	0.899
1948	0.881
1949	0.901
1950	1.126
1951	1.21
1952	0.917
1953	0.947
1954	0.876
1955	1.301
1956	0.975
1957	0.82
1958	0.884
1959	0.823
1960	0.885
1961	0.853
1962	0.864
1963	0.779
1964	0.86
1965	1.016
1966	0.876
1967	0.982
1968	0.849
1969	0.907
1970	1.046
1971	1.032
1972	0.87
1973	0.924
1974	0.925
1975	0.928
1976	1.006
1977	0.939
1978	1.109
1979	1.017
1980	0.826
1981	0.778
1982	1.059
1983	1.187
1984	0.898
1985	1.226
1986	1.012
1987	1.083
1988	0.895
1989	1.003
1990	0.958
1991	0.801
1992	1.12
1993	1.013