# europe_gree012 - Zagradeniye Forest - 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/3817
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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: europe_gree012 - Zagradeniye Forest - 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.
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#	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: Zagradeniye Forest
#	Location:
#	Country: Greece
#	Northernmost_Latitude: 41.67
#	Southernmost_Latitude: 41.67
#	Easternmost_Longitude: 24.88
#	Westernmost_Longitude: 24.88
#	Elevation: 1320 m
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# Data_Collection
#	Collection_Name: europe_gree012B
#	Earliest_Year: 1717
#	Most_Recent_Year: 1976
#	Time_Unit: y_ad
#	Core_Length:
#	Notes: {"database":{"database1":"LMR","database2":"Breits"}} {"climateInterpretation":{"basis":"", "climateVariable":"T", "climateVariableDetail":"air", "interpDirection":"positive", "seasonality":"[6, 7, 8]"}}{"VSLite_parameters":{"T1":"4.55728267166","T2":"17.4188338474","M1":"0.0224082134411","M2":"0.364020652962"}}
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# Species
#	Species_Name: Norway spruce
#	Species_Code: PCAB
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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
1717	0.89
1718	0.908
1719	0.939
1720	1.189
1721	1.174
1722	1.152
1723	1.011
1724	1.089
1725	0.874
1726	0.879
1727	1.061
1728	1.272
1729	1.146
1730	1.207
1731	1.136
1732	1.081
1733	1.152
1734	0.968
1735	1.055
1736	1.083
1737	1.063
1738	1.096
1739	1.14
1740	0.857
1741	0.92
1742	1.021
1743	0.991
1744	1.06
1745	1.09
1746	1.139
1747	1.233
1748	1.067
1749	1.093
1750	1.026
1751	0.909
1752	0.948
1753	0.929
1754	1.137
1755	1.103
1756	1.091
1757	1.117
1758	1.178
1759	1.113
1760	1.107
1761	1.119
1762	1.131
1763	0.967
1764	0.864
1765	0.969
1766	0.946
1767	1.037
1768	0.874
1769	0.885
1770	0.929
1771	0.978
1772	1.018
1773	0.89
1774	1.062
1775	1.176
1776	1.095
1777	0.98
1778	1.034
1779	1.015
1780	1.146
1781	1.038
1782	0.925
1783	0.775
1784	0.987
1785	1.086
1786	1.111
1787	1.07
1788	0.899
1789	0.874
1790	0.913
1791	0.946
1792	1.056
1793	1.001
1794	1.102
1795	1.039
1796	0.926
1797	0.922
1798	0.896
1799	1.007
1800	0.997
1801	1.071
1802	1.114
1803	1.043
1804	1.002
1805	0.86
1806	0.926
1807	0.996
1808	0.83
1809	0.871
1810	1.03
1811	1.004
1812	0.867
1813	0.793
1814	1.135
1815	1.032
1816	1.004
1817	1.024
1818	1.047
1819	1.166
1820	1.245
1821	1.145
1822	1.378
1823	1.284
1824	1.386
1825	1.024
1826	1.215
1827	1.083
1828	1.151
1829	0.883
1830	1.007
1831	0.944
1832	0.868
1833	0.834
1834	0.737
1835	0.707
1836	0.749
1837	0.704
1838	0.774
1839	0.837
1840	0.897
1841	0.947
1842	0.968
1843	0.967
1844	0.981
1845	0.856
1846	0.91
1847	0.939
1848	0.988
1849	0.875
1850	1.065
1851	1.031
1852	1.091
1853	1.069
1854	1.036
1855	1.139
1856	1.2
1857	0.896
1858	0.893
1859	0.844
1860	1.141
1861	1.019
1862	1.279
1863	1.137
1864	1.049
1865	1.025
1866	1.135
1867	0.99
1868	0.844
1869	1.078
1870	0.961
1871	1.106
1872	1.078
1873	1.235
1874	1.128
1875	1.059
1876	1.222
1877	1.439
1878	1.275
1879	1.267
1880	1.07
1881	1.263
1882	1.107
1883	1.107
1884	0.988
1885	1.265
1886	1.15
1887	1.051
1888	0.947
1889	0.87
1890	0.835
1891	0.875
1892	0.964
1893	0.882
1894	0.869
1895	0.948
1896	0.92
1897	0.861
1898	0.891
1899	1.097
1900	1.138
1901	1.239
1902	1.409
1903	1.235
1904	1.42
1905	1.149
1906	1.157
1907	1.176
1908	1.131
1909	1.09
1910	1.102
1911	0.923
1912	0.997
1913	1.036
1914	1.16
1915	1.112
1916	1.002
1917	0.924
1918	0.821
1919	0.866
1920	0.959
1921	0.831
1922	0.996
1923	0.898
1924	1.029
1925	1.071
1926	1.11
1927	1.269
1928	0.879
1929	0.64
1930	0.819
1931	0.882
1932	0.685
1933	0.646
1934	0.751
1935	0.88
1936	0.783
1937	0.909
1938	0.889
1939	0.953
1940	0.689
1941	1.082
1942	1.022
1943	0.685
1944	0.915
1945	1.044
1946	0.989
1947	0.726
1948	0.95
1949	0.73
1950	1.023
1951	0.724
1952	0.898
1953	0.849
1954	0.942
1955	0.785
1956	0.959
1957	0.781
1958	0.847
1959	0.75
1960	0.902
1961	0.869
1962	1.082
1963	0.897
1964	0.859
1965	0.915
1966	0.683
1967	0.719
1968	0.819
1969	0.927
1970	0.934
1971	0.763
1972	0.803
1973	0.809
1974	0.934
1975	0.859
1976	0.764