# europe_pola012 - Poznan - 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/5220
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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_pola012 - Poznan - 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: Poznan
#	Location:
#	Country: Poland
#	Northernmost_Latitude: 52.27
#	Southernmost_Latitude: 52.27
#	Easternmost_Longitude: 16.8
#	Westernmost_Longitude: 16.8
#	Elevation: 70 m
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# Data_Collection
#	Collection_Name: europe_pola012B
#	Earliest_Year: 1848
#	Most_Recent_Year: 1986
#	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":"4.7505379581","T2":"16.9564202307","M1":"0.0230801687221","M2":"0.448982314288"}}
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# Species
#	Species_Name: English oak
#	Species_Code: QURO
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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
1848	0.589
1849	1.285
1850	1.337
1851	1.201
1852	0.88
1853	1.43
1854	1.486
1855	1.194
1856	0.858
1857	0.993
1858	0.894
1859	0.991
1860	1.007
1861	1.317
1862	1.456
1863	1.23
1864	0.832
1865	0.939
1866	0.731
1867	1.191
1868	0.848
1869	1.251
1870	1.155
1871	0.988
1872	1.013
1873	0.739
1874	0.811
1875	0.925
1876	0.581
1877	0.856
1878	1.033
1879	0.924
1880	0.84
1881	0.85
1882	0.828
1883	0.777
1884	0.601
1885	0.756
1886	0.802
1887	0.752
1888	0.74
1889	0.802
1890	0.942
1891	0.962
1892	0.854
1893	0.785
1894	0.946
1895	0.786
1896	0.836
1897	0.861
1898	0.897
1899	0.734
1900	0.664
1901	0.761
1902	1.133
1903	1.227
1904	1.103
1905	0.95
1906	1.108
1907	1.087
1908	1.134
1909	1.112
1910	1.046
1911	0.992
1912	0.899
1913	1.062
1914	0.77
1915	0.926
1916	1.127
1917	0.902
1918	0.98
1919	1.048
1920	1.037
1921	0.904
1922	0.949
1923	1.049
1924	1.22
1925	1.05
1926	1.079
1927	1.286
1928	1.135
1929	1.123
1930	1.035
1931	1.218
1932	1.183
1933	0.858
1934	0.802
1935	1.025
1936	1.017
1937	1.033
1938	1.245
1939	1.128
1940	0.733
1941	0.911
1942	0.927
1943	0.883
1944	0.856
1945	0.983
1946	1.033
1947	1.016
1948	1.186
1949	1.369
1950	1.073
1951	1.142
1952	0.84
1953	0.757
1954	0.927
1955	0.915
1956	0.864
1957	0.929
1958	0.863
1959	0.687
1960	0.655
1961	0.788
1962	0.964
1963	0.929
1964	0.964
1965	1.125
1966	1.108
1967	1.303
1968	1.198
1969	0.887
1970	0.774
1971	0.876
1972	0.938
1973	1.154
1974	1.148
1975	1.034
1976	0.947
1977	0.991
1978	0.786
1979	1.031
1980	0.996
1981	1.376
1982	1.215
1983	0.977
1984	1.358
1985	1.037
1986	1.092