# europe_brit007 - Killarney - 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/4220
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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
#--------------------
# Title
#	Study_Name: europe_brit007 - Killarney - 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: Killarney
#	Location:
#	Country: Ireland
#	Northernmost_Latitude: 52.0
#	Southernmost_Latitude: 52.0
#	Easternmost_Longitude: -9.55
#	Westernmost_Longitude: -9.55
#	Elevation: 30 m
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# Data_Collection
#	Collection_Name: europe_brit007B
#	Earliest_Year: 1834
#	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":"5.91245807091","T2":"12.836498909","M1":"0.0229507063235","M2":"0.586333721318"}}
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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
1834	1.049
1835	1.004
1836	0.742
1837	1.084
1838	1.059
1839	0.751
1840	0.391
1841	0.54
1842	0.472
1843	0.438
1844	0.619
1845	0.967
1846	0.773
1847	0.804
1848	1.18
1849	1.296
1850	0.847
1851	0.711
1852	0.969
1853	1.062
1854	0.915
1855	1.087
1856	0.68
1857	0.724
1858	0.519
1859	0.554
1860	0.932
1861	1.116
1862	0.663
1863	0.695
1864	0.575
1865	0.659
1866	0.902
1867	1.036
1868	0.803
1869	0.704
1870	0.955
1871	1.6
1872	1.508
1873	1.293
1874	1.017
1875	1.099
1876	1.073
1877	0.838
1878	0.992
1879	0.841
1880	0.781
1881	0.915
1882	1.184
1883	1.139
1884	0.933
1885	0.902
1886	1.001
1887	0.801
1888	1.166
1889	0.841
1890	1.45
1891	1.337
1892	1.345
1893	0.66
1894	0.692
1895	0.992
1896	0.857
1897	1.48
1898	0.965
1899	0.869
1900	1.446
1901	1.163
1902	1.258
1903	1.342
1904	1.747
1905	1.148
1906	0.858
1907	0.779
1908	0.715
1909	0.742
1910	0.864
1911	1.107
1912	1.139
1913	0.882
1914	1.173
1915	1.35
1916	1.318
1917	1.396
1918	1.044
1919	0.806
1920	0.709
1921	0.665
1922	0.967
1923	0.909
1924	1.113
1925	0.761
1926	1.239
1927	1.325
1928	1.598
1929	1.211
1930	0.937
1931	1.02
1932	0.931
1933	0.814
1934	0.609
1935	1.03
1936	0.899
1937	0.993
1938	1.039
1939	1.215
1940	0.936
1941	1.015
1942	1.031
1943	1.24
1944	0.878
1945	1.295
1946	1.249
1947	1.634
1948	1.175
1949	0.882
1950	1.024
1951	1.298
1952	0.872
1953	1.088
1954	1.012
1955	0.777
1956	0.767
1957	0.854
1958	1.061
1959	0.875
1960	1.232
1961	0.725
1962	1.416
1963	1.115
1964	1.113
1965	0.97
1966	0.871
1967	0.733
1968	0.956
1969	1.15
1970	0.729
1971	0.656
1972	0.52
1973	0.73
1974	0.783
1975	0.583
1976	0.767
1977	0.552
1978	0.534