# europe_germ009 - Schaumburg - 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/4291
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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_germ009 - Schaumburg - 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: Schaumburg
#	Location:
#	Country: Germany
#	Northernmost_Latitude: 52.32
#	Southernmost_Latitude: 52.32
#	Easternmost_Longitude: 9.03
#	Westernmost_Longitude: 9.03
#	Elevation: 50 m
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# Data_Collection
#	Collection_Name: europe_germ009B
#	Earliest_Year: 1839
#	Most_Recent_Year: 1971
#	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":"4.65495291697","T2":"16.1821040084","M1":"0.0228171769279","M2":"0.552715862814"}}
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# Species
#	Species_Name: English oak
#	Species_Code: QURO
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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
1839	0.761
1840	0.664
1841	0.631
1842	0.773
1843	1.079
1844	0.81
1845	0.745
1846	0.723
1847	0.812
1848	0.77
1849	0.724
1850	0.9
1851	0.955
1852	0.939
1853	1.016
1854	1.119
1855	1.12
1856	1.182
1857	0.781
1858	0.837
1859	0.839
1860	0.946
1861	1.476
1862	1.296
1863	1.06
1864	1.067
1865	0.699
1866	1.046
1867	1.2
1868	0.93
1869	0.652
1870	1.161
1871	0.923
1872	0.523
1873	0.696
1874	0.87
1875	1.305
1876	1.361
1877	1.48
1878	1.752
1879	1.304
1880	1.312
1881	0.85
1882	0.862
1883	0.824
1884	1.356
1885	1.112
1886	0.963
1887	0.815
1888	0.988
1889	0.915
1890	1.01
1891	1.039
1892	1.107
1893	0.694
1894	0.904
1895	1.097
1896	1.139
1897	1.059
1898	1.282
1899	1.179
1900	1.245
1901	0.933
1902	1.055
1903	1.407
1904	1.093
1905	1.142
1906	1.209
1907	1.146
1908	1.214
1909	0.65
1910	0.763
1911	0.668
1912	0.957
1913	1.125
1914	1.249
1915	0.877
1916	0.632
1917	1.049
1918	0.981
1919	0.765
1920	0.855
1921	0.609
1922	0.882
1923	0.866
1924	1.212
1925	0.776
1926	0.889
1927	1.103
1928	0.783
1929	0.683
1930	0.6
1931	1.025
1932	1.053
1933	0.986
1934	0.62
1935	0.855
1936	1.012
1937	0.916
1938	0.939
1939	0.921
1940	0.779
1941	0.72
1942	0.958
1943	0.972
1944	0.754
1945	0.92
1946	0.871
1947	0.638
1948	0.904
1949	1.207
1950	1.326
1951	0.937
1952	0.879
1953	0.902
1954	0.778
1955	1.07
1956	0.884
1957	0.851
1958	0.924
1959	0.517
1960	0.758
1961	1.156
1962	0.902
1963	0.885
1964	0.871
1965	1.19
1966	1.49
1967	1.304
1968	1.051
1969	1.228
1970	1.212
1971	1.3