# europe_germ036 - Sinzing - 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/5272
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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_germ036 - Sinzing - Breitenmoser Tree Ring Chronology Data
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# Investigators
#	Investigators:  Breitenmoser, P.; Bronnimann, S.; Frank, D.
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# 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: Sinzing
#	Location:
#	Country: Germany
#	Northernmost_Latitude: 48.97
#	Southernmost_Latitude: 48.97
#	Easternmost_Longitude: 11.98
#	Westernmost_Longitude: 11.98
#	Elevation: 425 m
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# Data_Collection
#	Collection_Name: europe_germ036B
#	Earliest_Year: 1857
#	Most_Recent_Year: 1996
#	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":"3.91157419253","T2":"14.387187304","M1":"0.0226211612606","M2":"0.543878240019"}}
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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
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age	trsgi
1857	0.636
1858	0.486
1859	0.564
1860	0.509
1861	0.87
1862	0.633
1863	1.078
1864	1.159
1865	0.604
1866	1.097
1867	1.168
1868	0.825
1869	0.939
1870	0.447
1871	0.776
1872	1.081
1873	1.386
1874	1.148
1875	1.14
1876	1.043
1877	0.856
1878	1.336
1879	1.518
1880	1.424
1881	1.275
1882	1.428
1883	1.45
1884	1.109
1885	0.831
1886	0.618
1887	0.571
1888	0.988
1889	0.863
1890	1.115
1891	1.144
1892	1.008
1893	1.064
1894	1.011
1895	1.088
1896	1.045
1897	1.546
1898	1.318
1899	0.839
1900	0.801
1901	0.885
1902	0.93
1903	0.718
1904	0.714
1905	0.719
1906	0.967
1907	0.837
1908	0.656
1909	0.943
1910	1.049
1911	0.924
1912	1.176
1913	1.085
1914	1.079
1915	0.794
1916	1.075
1917	0.767
1918	0.862
1919	1.0
1920	1.123
1921	0.241
1922	0.448
1923	0.869
1924	1.112
1925	1.259
1926	1.908
1927	1.838
1928	1.212
1929	0.476
1930	0.64
1931	0.887
1932	0.997
1933	0.987
1934	0.502
1935	0.413
1936	0.664
1937	1.011
1938	0.984
1939	1.148
1940	0.897
1941	1.169
1942	1.137
1943	1.373
1944	1.174
1945	1.014
1946	1.047
1947	1.165
1948	0.921
1949	1.133
1950	1.342
1951	0.736
1952	0.83
1953	0.953
1954	0.803
1955	1.014
1956	0.787
1957	0.929
1958	1.053
1959	1.042
1960	0.768
1961	1.091
1962	0.658
1963	1.033
1964	0.763
1965	0.791
1966	0.883
1967	0.814
1968	0.895
1969	0.93
1970	0.971
1971	0.676
1972	0.756
1973	0.632
1974	0.885
1975	1.004
1976	0.321
1977	0.892
1978	1.087
1979	0.9
1980	0.819
1981	1.091
1982	0.765
1983	1.247
1984	1.167
1985	1.37
1986	1.092
1987	1.099
1988	1.424
1989	1.814
1990	1.127
1991	1.104
1992	0.791
1993	0.64
1994	0.61
1995	0.579
1996	0.657