# europe_spai022 - Albarracin Bezas - 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/4236
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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_spai022 - Albarracin Bezas - 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: Albarracin Bezas
#	Location:
#	Country: Spain
#	Northernmost_Latitude: 40.3
#	Southernmost_Latitude: 40.3
#	Easternmost_Longitude: -1.33
#	Westernmost_Longitude: -1.33
#	Elevation: 1225 m
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# Data_Collection
#	Collection_Name: europe_spai022B
#	Earliest_Year: 1855
#	Most_Recent_Year: 1985
#	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":"3.99521662412","T2":"15.4447112971","M1":"0.0228574093867","M2":"0.543081314301"}}
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# Species
#	Species_Name: maritime pine
#	Species_Code: PIPI
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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
1855	0.828
1856	0.668
1857	0.553
1858	0.363
1859	0.508
1860	0.645
1861	0.687
1862	0.81
1863	0.688
1864	0.678
1865	0.928
1866	0.786
1867	0.274
1868	0.504
1869	0.156
1870	0.531
1871	0.602
1872	0.83
1873	1.095
1874	1.04
1875	1.202
1876	0.908
1877	1.165
1878	1.118
1879	0.66
1880	0.944
1881	0.968
1882	0.637
1883	0.82
1884	1.005
1885	1.418
1886	1.402
1887	1.255
1888	1.896
1889	1.48
1890	1.026
1891	0.972
1892	1.464
1893	0.831
1894	1.246
1895	1.205
1896	1.208
1897	0.956
1898	1.157
1899	1.038
1900	1.157
1901	1.338
1902	1.594
1903	1.416
1904	1.381
1905	1.115
1906	1.317
1907	1.093
1908	1.628
1909	0.989
1910	0.822
1911	1.227
1912	0.666
1913	0.972
1914	1.149
1915	1.181
1916	0.592
1917	1.394
1918	0.977
1919	1.395
1920	1.246
1921	1.116
1922	1.118
1923	0.812
1924	0.675
1925	0.804
1926	1.304
1927	1.26
1928	1.189
1929	1.057
1930	0.74
1931	0.261
1932	0.702
1933	0.976
1934	1.032
1935	1.151
1936	1.284
1937	0.981
1938	0.975
1939	0.387
1940	0.938
1941	0.777
1942	0.799
1943	0.72
1944	0.849
1945	1.114
1946	0.903
1947	0.882
1948	0.8
1949	0.572
1950	0.509
1951	0.868
1952	1.048
1953	0.252
1954	0.913
1955	0.919
1956	1.375
1957	1.427
1958	1.165
1959	1.379
1960	1.378
1961	0.308
1962	1.191
1963	0.615
1964	0.775
1965	0.523
1966	1.078
1967	0.655
1968	0.732
1969	1.03
1970	0.378
1971	1.016
1972	1.157
1973	0.99
1974	0.995
1975	1.08
1976	1.187
1977	1.432
1978	0.866
1979	1.195
1980	1.151
1981	0.504
1982	1.041
1983	0.394
1984	0.87
1985	0.605