# europe_germ039 - Hochzell - 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/5268
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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_germ039 - Hochzell - 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: Hochzell
#	Location:
#	Country: Germany
#	Northernmost_Latitude: 49.08
#	Southernmost_Latitude: 49.08
#	Easternmost_Longitude: 13.1
#	Westernmost_Longitude: 13.1
#	Elevation: 1208 m
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# Data_Collection
#	Collection_Name: europe_germ039B
#	Earliest_Year: 1846
#	Most_Recent_Year: 1996
#	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":"4.89122086211","T2":"19.9317334592","M1":"0.0221587393821","M2":"0.290894522659"}}
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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
1846	1.283
1847	1.18
1848	1.11
1849	1.011
1850	1.081
1851	0.921
1852	0.869
1853	0.973
1854	0.903
1855	0.909
1856	0.878
1857	1.015
1858	0.975
1859	0.938
1860	0.878
1861	0.921
1862	0.984
1863	1.174
1864	1.073
1865	1.146
1866	1.068
1867	1.236
1868	1.069
1869	0.987
1870	1.161
1871	1.014
1872	1.019
1873	1.053
1874	0.985
1875	1.072
1876	1.065
1877	0.903
1878	1.099
1879	1.014
1880	1.254
1881	1.237
1882	1.179
1883	1.085
1884	1.248
1885	0.917
1886	0.858
1887	0.906
1888	0.837
1889	0.926
1890	0.937
1891	0.812
1892	0.941
1893	0.913
1894	0.942
1895	1.002
1896	0.741
1897	1.003
1898	1.09
1899	0.933
1900	0.827
1901	1.157
1902	0.933
1903	1.082
1904	1.131
1905	0.853
1906	0.717
1907	0.755
1908	0.891
1909	0.889
1910	0.953
1911	1.162
1912	0.796
1913	0.724
1914	0.933
1915	0.942
1916	1.052
1917	0.946
1918	0.805
1919	0.907
1920	0.931
1921	0.869
1922	0.84
1923	0.943
1924	0.948
1925	1.06
1926	1.036
1927	1.055
1928	0.951
1929	0.776
1930	0.831
1931	1.013
1932	1.063
1933	0.976
1934	1.317
1935	1.211
1936	0.989
1937	1.105
1938	0.965
1939	1.12
1940	1.194
1941	1.187
1942	0.847
1943	0.946
1944	1.009
1945	1.019
1946	1.329
1947	1.421
1948	0.745
1949	0.95
1950	1.12
1951	0.952
1952	1.217
1953	1.084
1954	0.787
1955	1.034
1956	0.984
1957	1.167
1958	0.886
1959	1.027
1960	0.979
1961	0.909
1962	0.947
1963	1.309
1964	1.139
1965	0.861
1966	1.233
1967	1.338
1968	1.247
1969	1.379
1970	1.164
1971	0.942
1972	0.847
1973	1.026
1974	0.572
1975	0.942
1976	0.75
1977	1.024
1978	0.827
1979	1.006
1980	0.598
1981	1.004
1982	0.92
1983	0.984
1984	0.702
1985	0.792
1986	0.964
1987	0.879
1988	1.1
1989	1.203
1990	1.097
1991	1.006
1992	1.15
1993	0.817
1994	0.982
1995	0.826
1996	0.606