# europe_germ057 - Woody-Happy-Berg - 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/5275
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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_germ057 - Woody-Happy-Berg - 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
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# 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: Woody-Happy-Berg
#	Location:
#	Country: Germany
#	Northernmost_Latitude: 49.2
#	Southernmost_Latitude: 49.2
#	Easternmost_Longitude: 12.38
#	Westernmost_Longitude: 12.38
#	Elevation: 450 m
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# Data_Collection
#	Collection_Name: europe_germ057B
#	Earliest_Year: 1868
#	Most_Recent_Year: 2001
#	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":"3.35553815236","T2":"13.8117927193","M1":"0.0227236031665","M2":"0.555112201892"}}
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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
1868	0.692
1869	1.069
1870	0.787
1871	1.167
1872	1.21
1873	1.128
1874	0.862
1875	1.139
1876	0.866
1877	0.914
1878	1.268
1879	1.347
1880	1.262
1881	1.013
1882	1.288
1883	1.183
1884	0.897
1885	0.709
1886	1.023
1887	0.821
1888	1.133
1889	0.993
1890	1.066
1891	1.213
1892	0.783
1893	0.663
1894	0.868
1895	0.986
1896	1.027
1897	1.211
1898	1.101
1899	0.61
1900	0.754
1901	0.834
1902	0.798
1903	0.606
1904	0.731
1905	0.544
1906	1.014
1907	0.861
1908	0.936
1909	1.059
1910	1.005
1911	0.711
1912	1.062
1913	1.284
1914	1.72
1915	0.957
1916	1.497
1917	1.137
1918	1.423
1919	1.083
1920	1.144
1921	0.335
1922	0.638
1923	1.017
1924	1.274
1925	1.114
1926	1.756
1927	1.695
1928	1.128
1929	0.963
1930	0.873
1931	0.909
1932	1.107
1933	1.039
1934	0.62
1935	0.661
1936	0.776
1937	1.044
1938	0.795
1939	0.952
1940	1.044
1941	1.35
1942	0.913
1943	1.096
1944	1.093
1945	1.035
1946	0.694
1947	0.781
1948	0.51
1949	0.801
1950	0.55
1951	0.522
1952	0.549
1953	0.458
1954	0.666
1955	0.924
1956	1.12
1957	1.262
1958	1.415
1959	1.349
1960	0.823
1961	1.016
1962	0.816
1963	0.981
1964	0.652
1965	0.82
1966	0.999
1967	0.817
1968	0.826
1969	1.01
1970	1.069
1971	1.088
1972	1.319
1973	1.148
1974	1.177
1975	1.194
1976	0.662
1977	0.909
1978	1.135
1979	0.803
1980	1.018
1981	0.782
1982	0.611
1983	0.933
1984	0.788
1985	1.168
1986	1.228
1987	1.383
1988	1.244
1989	1.591
1990	1.032
1991	0.888
1992	0.454
1993	0.743
1994	0.742
1995	1.012
1996	1.237
1997	1.721
1998	0.803
1999	1.454
2000	0.767
2001	1.011