# europe_germ052w - Seehalde (D), EU-Pr. - 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/4632
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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
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# Title
#	Study_Name: europe_germ052w - Seehalde (D), EU-Pr. - 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 VaganovÃÂ¢ÃÂÃÂShashkin 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 4ÃÂ¢ÃÂÃÂ6 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 modelÃÂ¢ÃÂÃÂs 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: Seehalde (D), EU-Pr.
#	Location:
#	Country: Germany
#	Northernmost_Latitude: 47.85
#	Southernmost_Latitude: 47.85
#	Easternmost_Longitude: 8.03
#	Westernmost_Longitude: 8.03
#	Elevation: 1250 m
#--------------------
# Data_Collection
#	Collection_Name: europe_germ052wB
#	Earliest_Year: 1763
#	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":"6.16875346157","T2":"18.4037000076","M1":"0.0223425660729","M2":"0.502156107505"}}
#--------------------
# 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
1763	1.241
1764	1.019
1765	1.015
1766	1.07
1767	0.845
1768	0.978
1769	0.986
1770	0.987
1771	1.194
1772	1.021
1773	1.064
1774	1.094
1775	0.939
1776	0.974
1777	0.945
1778	1.243
1779	1.196
1780	1.004
1781	1.162
1782	0.803
1783	1.381
1784	1.332
1785	1.104
1786	1.062
1787	1.073
1788	1.152
1789	0.92
1790	0.956
1791	0.939
1792	0.85
1793	0.687
1794	1.035
1795	0.924
1796	0.869
1797	1.051
1798	1.184
1799	1.014
1800	1.026
1801	0.935
1802	0.921
1803	0.651
1804	0.815
1805	0.891
1806	0.985
1807	1.099
1808	1.032
1809	1.237
1810	1.074
1811	1.127
1812	1.089
1813	1.096
1814	1.084
1815	1.024
1816	0.898
1817	0.931
1818	1.188
1819	1.156
1820	1.118
1821	1.035
1822	1.125
1823	0.987
1824	1.075
1825	1.018
1826	0.741
1827	0.775
1828	0.877
1829	1.061
1830	0.816
1831	0.918
1832	0.865
1833	1.1
1834	0.978
1835	0.75
1836	0.693
1837	0.577
1838	0.652
1839	0.639
1840	0.645
1841	0.749
1842	0.924
1843	0.834
1844	1.014
1845	1.007
1846	1.09
1847	0.902
1848	1.026
1849	0.975
1850	1.103
1851	1.076
1852	0.979
1853	0.997
1854	0.947
1855	1.061
1856	0.923
1857	1.002
1858	0.933
1859	0.894
1860	0.89
1861	0.919
1862	0.757
1863	1.013
1864	0.413
1865	0.488
1866	0.496
1867	0.717
1868	0.696
1869	0.814
1870	0.971
1871	0.897
1872	1.046
1873	1.091
1874	0.927
1875	1.154
1876	0.847
1877	0.797
1878	0.989
1879	0.952
1880	0.931
1881	1.164
1882	1.14
1883	1.184
1884	1.221
1885	1.092
1886	1.027
1887	1.167
1888	1.088
1889	1.135
1890	0.968
1891	0.979
1892	1.026
1893	1.061
1894	0.924
1895	0.958
1896	0.743
1897	0.879
1898	0.598
1899	0.647
1900	0.63
1901	0.794
1902	0.763
1903	0.956
1904	1.006
1905	0.846
1906	0.752
1907	0.824
1908	1.005
1909	0.883
1910	0.969
1911	1.081
1912	0.892
1913	0.963
1914	0.823
1915	1.02
1916	1.053
1917	1.162
1918	1.034
1919	1.258
1920	1.014
1921	1.091
1922	0.907
1923	0.811
1924	1.057
1925	1.091
1926	0.956
1927	1.105
1928	1.181
1929	1.273
1930	1.285
1931	1.327
1932	1.347
1933	1.159
1934	1.57
1935	1.469
1936	1.16
1937	1.161
1938	0.999
1939	1.053
1940	1.345
1941	1.419
1942	1.398
1943	1.514
1944	1.31
1945	1.149
1946	1.015
1947	1.12
1948	0.61
1949	0.583
1950	0.753
1951	0.779
1952	0.796
1953	0.761
1954	0.769
1955	1.148
1956	1.076
1957	1.089
1958	1.12
1959	1.066
1960	1.07
1961	1.027
1962	1.011
1963	1.184
1964	1.358
1965	1.133
1966	1.315
1967	1.214
1968	1.102
1969	1.19
1970	1.121
1971	1.15
1972	1.078
1973	1.122
1974	0.806
1975	0.829
1976	0.756
1977	0.927
1978	0.882
1979	1.072
1980	0.754
1981	0.945
1982	1.178
1983	1.006
1984	0.86
1985	0.995
1986	0.919
1987	0.827
1988	0.927
1989	0.886
1990	0.908
1991	0.94
1992	0.957
1993	0.896
1994	0.924
1995	0.892