# europe_germ034 - Steinach - 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/5273
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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_germ034 - Steinach - 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: Steinach
#	Location:
#	Country: Germany
#	Northernmost_Latitude: 48.92
#	Southernmost_Latitude: 48.92
#	Easternmost_Longitude: 12.58
#	Westernmost_Longitude: 12.58
#	Elevation: 370 m
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# Data_Collection
#	Collection_Name: europe_germ034B
#	Earliest_Year: 1853
#	Most_Recent_Year: 1998
#	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":"2.92803906147","T2":"13.0467641452","M1":"0.0224805370564","M2":"0.595510724635"}}
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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
1853	0.713
1854	0.569
1855	0.423
1856	0.587
1857	0.227
1858	0.432
1859	0.505
1860	0.461
1861	0.495
1862	0.189
1863	0.483
1864	0.6
1865	0.488
1866	0.637
1867	0.73
1868	0.533
1869	0.693
1870	0.449
1871	0.776
1872	1.033
1873	1.008
1874	0.853
1875	0.938
1876	0.978
1877	0.878
1878	1.188
1879	1.082
1880	1.023
1881	1.016
1882	1.068
1883	0.903
1884	0.833
1885	0.734
1886	0.85
1887	0.964
1888	1.029
1889	0.837
1890	1.385
1891	1.33
1892	1.018
1893	0.788
1894	1.219
1895	1.36
1896	1.412
1897	1.525
1898	1.259
1899	0.847
1900	0.798
1901	0.922
1902	1.177
1903	0.802
1904	0.777
1905	0.649
1906	1.051
1907	1.008
1908	0.829
1909	0.809
1910	0.958
1911	0.772
1912	1.248
1913	1.451
1914	1.734
1915	0.897
1916	0.934
1917	0.673
1918	0.836
1919	1.11
1920	0.99
1921	0.397
1922	0.402
1923	0.784
1924	1.129
1925	1.155
1926	1.834
1927	1.609
1928	1.104
1929	0.871
1930	0.804
1931	0.705
1932	1.006
1933	1.403
1934	0.497
1935	0.675
1936	1.088
1937	1.155
1938	0.786
1939	1.034
1940	1.287
1941	1.223
1942	0.633
1943	0.935
1944	0.986
1945	0.907
1946	0.447
1947	0.519
1948	0.369
1949	0.81
1950	0.511
1951	0.508
1952	0.496
1953	0.741
1954	0.711
1955	1.513
1956	2.072
1957	2.18
1958	1.353
1959	1.219
1960	0.937
1961	1.116
1962	0.754
1963	0.851
1964	0.482
1965	0.923
1966	1.333
1967	1.3
1968	1.042
1969	1.033
1970	0.789
1971	0.631
1972	0.766
1973	0.655
1974	0.592
1975	0.838
1976	0.367
1977	0.911
1978	1.0
1979	0.829
1980	0.556
1981	0.831
1982	0.472
1983	0.584
1984	0.669
1985	1.097
1986	1.024
1987	1.335
1988	1.301
1989	1.663
1990	1.397
1991	1.432
1992	0.781
1993	0.848
1994	0.831
1995	0.95
1996	1.143
1997	1.399
1998	0.952