# europe_brit003 - Cappoquin - 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/4210
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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_brit003 - Cappoquin - 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: Cappoquin
#	Location:
#	Country: Ireland
#	Northernmost_Latitude: 52.13
#	Southernmost_Latitude: 52.13
#	Easternmost_Longitude: -7.9
#	Westernmost_Longitude: -7.9
#	Elevation: 150 m
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# Data_Collection
#	Collection_Name: europe_brit003B
#	Earliest_Year: 1842
#	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":"4.21014576449","T2":"17.5100074978","M1":"0.0223405045105","M2":"0.366258521404"}}
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# Species
#	Species_Name: durmast oak
#	Species_Code: QUPE
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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
1842	0.68
1843	0.752
1844	0.571
1845	0.944
1846	0.88
1847	1.034
1848	1.038
1849	1.05
1850	1.233
1851	1.361
1852	1.37
1853	1.137
1854	1.071
1855	1.283
1856	0.88
1857	1.052
1858	0.924
1859	0.928
1860	0.959
1861	0.987
1862	0.887
1863	0.701
1864	0.72
1865	0.856
1866	0.892
1867	1.053
1868	0.811
1869	1.039
1870	1.142
1871	0.889
1872	0.975
1873	1.05
1874	1.049
1875	1.197
1876	0.935
1877	0.971
1878	1.041
1879	0.994
1880	0.998
1881	1.072
1882	0.888
1883	1.057
1884	1.14
1885	0.968
1886	1.038
1887	0.729
1888	1.025
1889	1.009
1890	1.108
1891	1.023
1892	1.069
1893	0.923
1894	0.985
1895	0.945
1896	0.946
1897	1.321
1898	0.875
1899	1.16
1900	1.095
1901	0.905
1902	0.959
1903	0.909
1904	1.06
1905	0.867
1906	0.662
1907	0.551
1908	0.677
1909	0.767
1910	1.165
1911	1.114
1912	1.098
1913	0.945
1914	0.79
1915	0.618
1916	0.676
1917	0.894
1918	0.657
1919	0.6
1920	0.742
1921	0.589
1922	0.855
1923	0.61
1924	0.752
1925	0.844
1926	0.843
1927	1.044
1928	0.85
1929	0.906
1930	0.989
1931	0.982
1932	1.151
1933	0.948
1934	1.07
1935	1.535
1936	1.783
1937	1.466
1938	1.394
1939	1.452
1940	1.267
1941	1.661
1942	1.735
1943	1.221
1944	1.256
1945	1.664
1946	1.468
1947	1.447
1948	1.401
1949	1.625
1950	1.523
1951	1.344
1952	0.981
1953	1.16
1954	0.805
1955	0.719
1956	0.81
1957	0.883
1958	0.964
1959	0.944
1960	1.019
1961	0.867
1962	1.284
1963	0.918
1964	0.741
1965	0.841
1966	0.868
1967	0.878
1968	0.774
1969	0.612
1970	0.537
1971	0.569
1972	0.496
1973	0.46
1974	0.527
1975	0.688
1976	0.543
1977	0.568
1978	0.454