# europe_brit021 - Dimmie Schottland - 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/4399
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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_brit021 - Dimmie Schottland - 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: Dimmie Schottland
#	Location:
#	Country: United Kingdom
#	Northernmost_Latitude: 56.12
#	Southernmost_Latitude: 56.12
#	Easternmost_Longitude: -3.33
#	Westernmost_Longitude: -3.33
#	Elevation: 200 m
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# Data_Collection
#	Collection_Name: europe_brit021B
#	Earliest_Year: 1843
#	Most_Recent_Year: 1976
#	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":"2.50859554834","T2":"17.0846918207","M1":"0.022227353974","M2":"0.225953855065"}}
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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
1843	1.061
1844	1.181
1845	1.278
1846	1.174
1847	0.837
1848	0.859
1849	0.898
1850	0.763
1851	0.88
1852	1.058
1853	1.014
1854	0.82
1855	0.876
1856	0.944
1857	0.944
1858	0.955
1859	0.885
1860	0.959
1861	0.869
1862	0.766
1863	0.824
1864	0.743
1865	0.792
1866	0.883
1867	0.92
1868	0.997
1869	0.86
1870	0.757
1871	0.95
1872	1.058
1873	1.04
1874	0.963
1875	1.051
1876	0.964
1877	0.831
1878	0.918
1879	0.671
1880	1.315
1881	0.984
1882	1.186
1883	0.77
1884	0.783
1885	0.754
1886	0.939
1887	1.056
1888	1.109
1889	1.032
1890	1.155
1891	1.177
1892	1.098
1893	1.176
1894	0.855
1895	0.362
1896	0.203
1897	0.43
1898	0.708
1899	0.864
1900	0.964
1901	0.946
1902	0.774
1903	1.057
1904	1.278
1905	1.122
1906	1.061
1907	0.874
1908	0.746
1909	0.699
1910	1.077
1911	1.374
1912	1.38
1913	1.548
1914	1.435
1915	1.32
1916	1.353
1917	1.017
1918	1.309
1919	1.227
1920	1.164
1921	1.213
1922	1.154
1923	1.234
1924	1.233
1925	1.217
1926	1.2
1927	1.27
1928	0.871
1929	0.943
1930	0.916
1931	0.938
1932	0.948
1933	0.825
1934	1.172
1935	1.271
1936	1.232
1937	1.251
1938	1.55
1939	1.535
1940	1.027
1941	1.267
1942	1.197
1943	1.523
1944	1.093
1945	1.224
1946	1.072
1947	0.615
1948	0.916
1949	1.199
1950	1.069
1951	0.942
1952	0.946
1953	1.347
1954	1.053
1955	0.961
1956	1.043
1957	1.05
1958	0.903
1959	0.846
1960	0.726
1961	0.673
1962	0.651
1963	0.507
1964	0.443
1965	0.483
1966	0.477
1967	0.727
1968	0.567
1969	0.366
1970	0.504
1971	0.756
1972	0.844
1973	0.712
1974	0.794
1975	0.916
1976	1.071