# europe_germ033 - Arber - 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/5263
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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_germ033 - Arber - Breitenmoser Tree Ring Chronology Data
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# 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: Arber
#	Location:
#	Country: Germany
#	Northernmost_Latitude: 49.12
#	Southernmost_Latitude: 49.12
#	Easternmost_Longitude: 13.13
#	Westernmost_Longitude: 13.13
#	Elevation: 1420 m
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# Data_Collection
#	Collection_Name: europe_germ033B
#	Earliest_Year: 1850
#	Most_Recent_Year: 1997
#	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":"3.92100501967","T2":"19.3624691557","M1":"0.0226152603756","M2":"0.27562210193"}}
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# Species
#	Species_Name: Norway spruce
#	Species_Code: PCAB
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# Chronology:
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# Variables
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# 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
1850	0.907
1851	0.662
1852	0.836
1853	0.983
1854	0.95
1855	0.885
1856	0.888
1857	1.285
1858	1.267
1859	1.06
1860	0.796
1861	0.815
1862	0.951
1863	1.476
1864	1.126
1865	1.038
1866	1.019
1867	1.028
1868	0.915
1869	1.083
1870	1.1
1871	1.07
1872	1.038
1873	1.291
1874	1.312
1875	1.442
1876	1.258
1877	1.093
1878	1.236
1879	1.015
1880	1.081
1881	1.336
1882	1.011
1883	0.878
1884	1.15
1885	1.027
1886	0.871
1887	1.01
1888	0.987
1889	1.044
1890	0.828
1891	0.764
1892	0.861
1893	0.91
1894	0.999
1895	1.058
1896	0.765
1897	0.898
1898	0.987
1899	1.089
1900	0.957
1901	1.205
1902	1.037
1903	1.182
1904	1.11
1905	0.844
1906	0.808
1907	1.083
1908	1.224
1909	1.19
1910	1.16
1911	1.307
1912	1.144
1913	0.91
1914	0.863
1915	0.682
1916	0.916
1917	0.867
1918	0.672
1919	0.77
1920	0.669
1921	0.641
1922	0.578
1923	0.589
1924	0.72
1925	0.809
1926	0.692
1927	0.897
1928	0.807
1929	0.935
1930	0.958
1931	1.198
1932	1.038
1933	0.968
1934	1.253
1935	1.172
1936	1.103
1937	0.962
1938	0.886
1939	1.079
1940	1.141
1941	0.96
1942	0.887
1943	1.017
1944	1.111
1945	1.236
1946	1.24
1947	1.167
1948	0.777
1949	0.795
1950	0.864
1951	0.852
1952	1.083
1953	1.102
1954	0.864
1955	1.005
1956	0.866
1957	1.11
1958	1.042
1959	1.533
1960	1.499
1961	1.42
1962	1.441
1963	1.752
1964	1.256
1965	0.896
1966	1.246
1967	1.188
1968	1.047
1969	1.274
1970	1.158
1971	1.187
1972	0.993
1973	1.136
1974	0.753
1975	0.926
1976	0.639
1977	1.044
1978	0.616
1979	0.932
1980	0.395
1981	0.788
1982	0.562
1983	0.708
1984	0.683
1985	0.716
1986	0.918
1987	0.566
1988	0.777
1989	0.803
1990	0.846
1991	0.823
1992	1.102
1993	1.011
1994	1.105
1995	0.805
1996	0.792
1997	1.051