# europe_germ040 - Falkenstein - 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/5266
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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_germ040 - Falkenstein - 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:
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#	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: Falkenstein
#	Location:
#	Country: Germany
#	Northernmost_Latitude: 49.1
#	Southernmost_Latitude: 49.1
#	Easternmost_Longitude: 13.33
#	Westernmost_Longitude: 13.33
#	Elevation: 1325 m
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# Data_Collection
#	Collection_Name: europe_germ040B
#	Earliest_Year: 1755
#	Most_Recent_Year: 1995
#	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":"6.41345525268","T2":"20.1016992266","M1":"0.0222399142755","M2":"0.256514270145"}}
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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)
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##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
1755	1.086
1756	1.168
1757	1.231
1758	0.908
1759	1.135
1760	1.184
1761	1.315
1762	1.393
1763	1.124
1764	1.101
1765	0.993
1766	1.204
1767	1.349
1768	1.209
1769	1.399
1770	1.214
1771	0.853
1772	0.969
1773	0.823
1774	0.933
1775	0.832
1776	0.993
1777	1.191
1778	1.265
1779	1.092
1780	1.085
1781	1.253
1782	0.891
1783	1.478
1784	1.162
1785	1.303
1786	1.297
1787	1.223
1788	1.222
1789	1.019
1790	1.04
1791	1.326
1792	1.291
1793	1.111
1794	1.439
1795	1.127
1796	1.022
1797	0.895
1798	1.457
1799	1.283
1800	1.313
1801	1.162
1802	0.973
1803	0.793
1804	0.947
1805	0.783
1806	0.81
1807	1.357
1808	0.987
1809	0.98
1810	1.039
1811	1.152
1812	0.75
1813	0.748
1814	0.932
1815	0.836
1816	0.68
1817	0.76
1818	0.588
1819	0.785
1820	0.515
1821	0.339
1822	0.753
1823	0.584
1824	0.765
1825	0.877
1826	0.758
1827	0.821
1828	1.005
1829	0.912
1830	0.699
1831	0.847
1832	0.745
1833	1.043
1834	1.116
1835	0.849
1836	0.907
1837	0.968
1838	0.808
1839	1.03
1840	0.922
1841	0.88
1842	1.113
1843	0.616
1844	0.841
1845	0.954
1846	1.121
1847	1.047
1848	0.907
1849	0.987
1850	1.044
1851	0.71
1852	1.055
1853	1.082
1854	0.985
1855	1.092
1856	0.973
1857	1.176
1858	1.261
1859	1.052
1860	0.963
1861	0.946
1862	0.998
1863	1.174
1864	1.048
1865	1.042
1866	1.292
1867	1.218
1868	1.194
1869	1.053
1870	1.262
1871	1.164
1872	1.156
1873	1.495
1874	1.438
1875	1.5
1876	1.177
1877	1.083
1878	1.179
1879	1.138
1880	1.195
1881	1.413
1882	0.989
1883	1.087
1884	1.284
1885	1.078
1886	0.943
1887	1.193
1888	1.097
1889	1.218
1890	0.963
1891	0.87
1892	1.044
1893	1.023
1894	1.034
1895	1.244
1896	1.045
1897	1.07
1898	0.944
1899	0.977
1900	0.863
1901	1.093
1902	0.988
1903	1.109
1904	1.202
1905	0.836
1906	0.739
1907	0.861
1908	1.101
1909	0.958
1910	1.009
1911	1.304
1912	1.046
1913	0.819
1914	0.981
1915	0.972
1916	1.07
1917	1.138
1918	0.752
1919	0.978
1920	0.855
1921	0.925
1922	0.92
1923	0.75
1924	1.05
1925	1.021
1926	1.008
1927	1.181
1928	1.169
1929	1.019
1930	0.945
1931	1.375
1932	1.148
1933	0.974
1934	1.249
1935	1.399
1936	1.148
1937	1.088
1938	1.148
1939	1.175
1940	1.066
1941	1.037
1942	0.723
1943	0.684
1944	0.721
1945	0.827
1946	1.238
1947	1.455
1948	0.724
1949	0.88
1950	1.098
1951	1.083
1952	1.164
1953	1.022
1954	0.299
1955	0.371
1956	0.305
1957	0.587
1958	0.547
1959	0.628
1960	0.806
1961	0.777
1962	0.94
1963	1.151
1964	0.903
1965	0.594
1966	1.051
1967	1.096
1968	1.041
1969	1.256
1970	1.157
1971	0.907
1972	0.927
1973	1.06
1974	0.518
1975	0.822
1976	0.464
1977	0.906
1978	0.664
1979	0.982
1980	0.454
1981	0.764
1982	0.922
1983	1.123
1984	0.836
1985	0.82
1986	1.041
1987	0.969
1988	1.216
1989	1.256
1990	1.144
1991	1.043
1992	1.187
1993	0.945
1994	1.146
1995	0.849