# europe_brit018 - Loch Maree - 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/4512
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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_brit018 - Loch Maree - 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 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: Loch Maree
#	Location:
#	Country: United Kingdom
#	Northernmost_Latitude: 57.52
#	Southernmost_Latitude: 57.52
#	Easternmost_Longitude: -5.33
#	Westernmost_Longitude: -5.33
#	Elevation: 100 m
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# Data_Collection
#	Collection_Name: europe_brit018B
#	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":"4.94604191165","T2":"17.2228754121","M1":"0.0225165230979","M2":"0.366175171142"}}
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# Species
#	Species_Name: Scots pine
#	Species_Code: PISY
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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
1834	1.267
1835	1.151
1836	0.953
1837	0.822
1838	0.931
1839	0.759
1840	0.746
1841	0.7
1842	0.858
1843	1.054
1844	0.807
1845	1.015
1846	1.202
1847	0.954
1848	1.167
1849	1.245
1850	1.019
1851	1.003
1852	1.014
1853	0.937
1854	1.084
1855	0.913
1856	0.886
1857	0.95
1858	1.158
1859	1.327
1860	1.092
1861	1.062
1862	0.922
1863	0.945
1864	0.95
1865	1.026
1866	0.896
1867	0.773
1868	1.258
1869	1.205
1870	1.232
1871	1.047
1872	1.049
1873	1.05
1874	1.244
1875	1.106
1876	0.96
1877	0.846
1878	0.747
1879	0.743
1880	1.348
1881	0.977
1882	1.189
1883	1.056
1884	1.415
1885	1.233
1886	1.027
1887	1.094
1888	1.05
1889	0.961
1890	1.066
1891	0.979
1892	1.03
1893	1.328
1894	1.138
1895	0.926
1896	0.943
1897	0.968
1898	1.142
1899	1.18
1900	1.006
1901	1.078
1902	0.796
1903	0.998
1904	1.24
1905	1.098
1906	1.097
1907	0.839
1908	0.998
1909	0.779
1910	1.141
1911	1.066
1912	1.162
1913	1.217
1914	1.076
1915	0.888
1916	0.803
1917	0.795
1918	0.753
1919	0.849
1920	0.774
1921	1.014
1922	0.935
1923	0.704
1924	0.736
1925	0.891
1926	0.931
1927	0.85
1928	0.802
1929	0.663
1930	0.772
1931	0.762
1932	0.803
1933	0.898
1934	0.888
1935	1.035
1936	0.895
1937	0.87
1938	0.77
1939	0.605
1940	0.542
1941	0.565
1942	0.529
1943	0.786
1944	0.744
1945	0.725
1946	0.733
1947	1.001
1948	1.258
1949	1.503
1950	1.506
1951	1.457
1952	1.293
1953	1.228
1954	0.94
1955	1.129
1956	0.936
1957	1.042
1958	1.099
1959	1.171
1960	0.954
1961	0.863
1962	0.902
1963	0.973
1964	1.075
1965	0.928
1966	0.903
1967	1.115
1968	1.238
1969	0.932
1970	0.921
1971	0.973
1972	1.043
1973	1.026
1974	0.931
1975	1.065
1976	1.054
1977	1.033
1978	0.912