# europe_spai020 - Penota - 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/3255
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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_spai020 - Penota - 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: Penota
#	Location:
#	Country: Spain
#	Northernmost_Latitude: 40.67
#	Southernmost_Latitude: 40.67
#	Easternmost_Longitude: -0.33
#	Westernmost_Longitude: -0.33
#	Elevation: 1650 m
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# Data_Collection
#	Collection_Name: europe_spai020B
#	Earliest_Year: 1805
#	Most_Recent_Year: 1991
#	Time_Unit: y_ad
#	Core_Length:
#	Notes: {"database":{"database1":"LMR","database2":"Breits"}} {"climateInterpretation":{"basis":"", "climateVariable":"M", "climateVariableDetail":"air", "interpDirection":"positive", "seasonality":"[6, 7, 8]"}}{"VSLite_parameters":{"T1":"5.12460777694","T2":"16.6561493678","M1":"0.0221919671891","M2":"0.48552444562"}}
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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
#
age	trsgi
1805	0.923
1806	0.587
1807	0.895
1808	0.803
1809	0.807
1810	0.821
1811	1.128
1812	0.968
1813	1.067
1814	1.077
1815	0.968
1816	0.848
1817	0.827
1818	0.751
1819	0.768
1820	0.814
1821	0.722
1822	0.838
1823	0.931
1824	0.734
1825	0.995
1826	1.042
1827	0.915
1828	0.84
1829	0.78
1830	1.055
1831	0.977
1832	0.721
1833	0.66
1834	0.988
1835	1.374
1836	1.447
1837	1.23
1838	0.935
1839	1.095
1840	0.991
1841	1.291
1842	0.949
1843	1.292
1844	1.105
1845	1.013
1846	1.351
1847	1.316
1848	1.04
1849	1.171
1850	1.454
1851	0.93
1852	0.699
1853	0.99
1854	1.165
1855	0.731
1856	0.733
1857	0.968
1858	1.129
1859	1.029
1860	0.77
1861	0.695
1862	0.709
1863	0.817
1864	0.987
1865	0.772
1866	0.614
1867	0.856
1868	0.954
1869	1.011
1870	0.908
1871	1.028
1872	0.748
1873	0.555
1874	0.683
1875	0.875
1876	1.195
1877	1.022
1878	0.9
1879	0.559
1880	0.778
1881	0.688
1882	0.868
1883	0.72
1884	0.838
1885	0.906
1886	1.155
1887	0.903
1888	0.88
1889	0.78
1890	0.973
1891	0.833
1892	0.816
1893	1.146
1894	0.781
1895	0.842
1896	1.192
1897	1.183
1898	0.927
1899	0.989
1900	0.607
1901	0.955
1902	1.29
1903	1.589
1904	1.237
1905	1.203
1906	1.022
1907	1.184
1908	0.85
1909	0.922
1910	0.988
1911	0.886
1912	1.322
1913	1.115
1914	1.498
1915	1.249
1916	1.076
1917	0.932
1918	1.243
1919	0.986
1920	1.073
1921	0.857
1922	0.971
1923	1.256
1924	0.874
1925	1.102
1926	1.244
1927	0.94
1928	0.822
1929	1.004
1930	1.064
1931	1.13
1932	1.125
1933	1.309
1934	0.729
1935	0.673
1936	0.921
1937	1.216
1938	1.118
1939	0.751
1940	0.917
1941	0.563
1942	0.637
1943	0.852
1944	1.032
1945	0.944
1946	0.943
1947	1.128
1948	1.022
1949	0.951
1950	0.959
1951	0.647
1952	0.67
1953	0.844
1954	0.675
1955	1.054
1956	1.031
1957	0.999
1958	0.986
1959	1.405
1960	0.886
1961	0.998
1962	0.912
1963	0.701
1964	1.031
1965	0.871
1966	0.942
1967	1.014
1968	1.075
1969	0.88
1970	0.872
1971	1.084
1972	1.032
1973	0.971
1974	0.976
1975	1.058
1976	1.347
1977	1.377
1978	0.833
1979	0.842
1980	1.377
1981	1.183
1982	1.223
1983	1.386
1984	1.198
1985	1.239
1986	0.947
1987	1.064
1988	1.037
1989	1.153
1990	1.224
1991	0.862