# europe_brit010 - Ludlow - 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/4222
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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_brit010 - Ludlow - 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 VaganovÃÂ¢ÃÂÃÂShashkin 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 4ÃÂ¢ÃÂÃÂ6 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 modelÃÂ¢ÃÂÃÂs 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: Ludlow
#	Location:
#	Country: United Kingdom
#	Northernmost_Latitude: 52.35
#	Southernmost_Latitude: 52.35
#	Easternmost_Longitude: -2.73
#	Westernmost_Longitude: -2.73
#	Elevation: 185 m
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# Data_Collection
#	Collection_Name: europe_brit010B
#	Earliest_Year: 1832
#	Most_Recent_Year: 1978
#	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":"4.72358367583","T2":"14.3477637566","M1":"0.0223760400893","M2":"0.564066818257"}}
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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
1832	1.005
1833	1.24
1834	1.258
1835	1.113
1836	0.946
1837	1.154
1838	0.707
1839	0.921
1840	0.627
1841	0.93
1842	1.093
1843	0.98
1844	0.542
1845	0.895
1846	0.91
1847	0.601
1848	0.547
1849	0.963
1850	1.145
1851	1.457
1852	1.334
1853	1.253
1854	0.976
1855	1.172
1856	0.912
1857	1.458
1858	1.213
1859	1.381
1860	1.053
1861	1.607
1862	1.107
1863	0.704
1864	0.497
1865	0.714
1866	0.733
1867	0.913
1868	0.974
1869	0.769
1870	0.831
1871	0.991
1872	1.019
1873	1.094
1874	0.786
1875	1.245
1876	0.757
1877	0.905
1878	1.114
1879	0.952
1880	1.015
1881	0.677
1882	0.666
1883	0.783
1884	0.85
1885	0.848
1886	0.791
1887	0.698
1888	0.791
1889	0.732
1890	0.933
1891	1.3
1892	1.54
1893	1.38
1894	0.877
1895	1.319
1896	0.942
1897	1.182
1898	0.948
1899	0.992
1900	1.252
1901	1.184
1902	1.059
1903	1.294
1904	1.242
1905	0.978
1906	1.008
1907	1.065
1908	1.347
1909	0.924
1910	1.302
1911	1.002
1912	1.215
1913	1.241
1914	1.133
1915	1.018
1916	0.984
1917	1.027
1918	1.238
1919	1.041
1920	1.192
1921	0.908
1922	1.089
1923	1.098
1924	1.258
1925	1.127
1926	1.072
1927	1.019
1928	1.011
1929	1.199
1930	1.33
1931	1.257
1932	1.016
1933	0.784
1934	0.817
1935	0.855
1936	0.886
1937	0.897
1938	0.955
1939	1.294
1940	0.77
1941	0.593
1942	0.613
1943	0.799
1944	0.583
1945	1.007
1946	0.771
1947	1.188
1948	0.742
1949	0.603
1950	0.716
1951	0.746
1952	0.906
1953	0.89
1954	0.827
1955	0.948
1956	0.688
1957	0.625
1958	1.063
1959	0.992
1960	1.093
1961	0.76
1962	1.005
1963	1.188
1964	1.288
1965	0.938
1966	1.202
1967	1.095
1968	0.951
1969	0.955
1970	0.98
1971	1.071
1972	0.839
1973	0.919
1974	0.631
1975	0.734
1976	0.692
1977	0.961
1978	1.069