# europe_neth030 - Mattemburgh Sub-dominant Trees - 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/3916
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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_neth030 - Mattemburgh Sub-dominant Trees - 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:
#--------------------
#	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: Mattemburgh Sub-dominant Trees
#	Location:
#	Country: Netherlands
#	Northernmost_Latitude: 51.45
#	Southernmost_Latitude: 51.45
#	Easternmost_Longitude: 4.32
#	Westernmost_Longitude: 4.32
#	Elevation: 5 m
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# Data_Collection
#	Collection_Name: europe_neth030B
#	Earliest_Year: 1849
#	Most_Recent_Year: 1991
#	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":"5.47230616868","T2":"18.7764101114","M1":"0.0220219632326","M2":"0.291232182585"}}
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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
#
age	trsgi
1849	1.214
1850	1.19
1851	1.138
1852	1.014
1853	0.928
1854	0.901
1855	0.978
1856	0.859
1857	0.885
1858	0.834
1859	0.898
1860	0.988
1861	1.046
1862	1.117
1863	1.116
1864	1.141
1865	1.128
1866	1.037
1867	1.121
1868	1.116
1869	1.136
1870	1.033
1871	1.023
1872	1.023
1873	0.93
1874	0.966
1875	0.954
1876	1.005
1877	0.91
1878	0.982
1879	1.028
1880	1.062
1881	0.959
1882	0.954
1883	0.922
1884	0.942
1885	0.946
1886	1.052
1887	0.981
1888	0.926
1889	0.958
1890	0.939
1891	0.934
1892	0.93
1893	0.962
1894	0.937
1895	0.914
1896	1.017
1897	0.936
1898	0.965
1899	0.884
1900	0.884
1901	0.88
1902	0.826
1903	0.805
1904	0.759
1905	0.782
1906	0.797
1907	0.857
1908	0.882
1909	0.936
1910	0.998
1911	1.011
1912	0.923
1913	0.92
1914	0.917
1915	0.924
1916	0.947
1917	0.929
1918	0.897
1919	0.866
1920	0.855
1921	0.853
1922	0.878
1923	0.931
1924	0.946
1925	0.925
1926	0.914
1927	0.921
1928	0.874
1929	0.885
1930	0.949
1931	0.995
1932	1.048
1933	1.082
1934	0.987
1935	0.945
1936	1.022
1937	1.114
1938	1.08
1939	1.037
1940	0.966
1941	0.911
1942	0.995
1943	1.032
1944	1.061
1945	1.05
1946	1.192
1947	1.202
1948	1.195
1949	1.173
1950	1.104
1951	1.234
1952	1.117
1953	1.229
1954	1.106
1955	1.061
1956	1.126
1957	1.015
1958	1.174
1959	1.189
1960	1.13
1961	1.026
1962	1.023
1963	0.976
1964	0.878
1965	0.814
1966	0.78
1967	0.886
1968	0.932
1969	0.965
1970	0.909
1971	1.014
1972	0.982
1973	0.968
1974	0.959
1975	0.906
1976	0.927
1977	0.901
1978	0.93
1979	0.923
1980	0.868
1981	0.957
1982	0.95
1983	0.803
1984	0.696
1985	0.765
1986	0.863
1987	0.902
1988	0.922
1989	1.246
1990	1.225
1991	1.211