# europe_swit102 - Grindelwald BE - 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/4428
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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_swit102 - Grindelwald BE - 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 VaganovÃÂ¢ÃÂÃÂShashkin 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 4ÃÂ¢ÃÂÃÂ6 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 modelÃÂ¢ÃÂÃÂs 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: Grindelwald BE
#	Location:
#	Country: Switzerland
#	Northernmost_Latitude: 46.6
#	Southernmost_Latitude: 46.6
#	Easternmost_Longitude: 8.07
#	Westernmost_Longitude: 8.07
#	Elevation: 1370 m
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# Data_Collection
#	Collection_Name: europe_swit102B
#	Earliest_Year: 1812
#	Most_Recent_Year: 1977
#	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":"5.57882969609","T2":"17.3274783672","M1":"0.0224310881306","M2":"0.389353047562"}}
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# Species
#	Species_Name: Norway spruce
#	Species_Code: PCAB
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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
1812	0.655
1813	0.647
1814	0.864
1815	0.919
1816	0.665
1817	0.803
1818	1.019
1819	1.158
1820	0.778
1821	0.607
1822	0.928
1823	0.773
1824	0.841
1825	0.914
1826	0.932
1827	0.867
1828	1.098
1829	1.265
1830	1.021
1831	1.354
1832	1.134
1833	1.617
1834	1.553
1835	0.929
1836	1.056
1837	0.946
1838	0.609
1839	0.926
1840	0.998
1841	1.108
1842	1.505
1843	0.749
1844	0.822
1845	0.982
1846	1.108
1847	0.895
1848	0.918
1849	1.178
1850	1.13
1851	0.89
1852	0.797
1853	1.093
1854	1.191
1855	1.028
1856	0.772
1857	0.819
1858	0.658
1859	0.699
1860	0.763
1861	0.972
1862	0.897
1863	1.1
1864	1.164
1865	1.097
1866	1.013
1867	0.871
1868	0.999
1869	0.778
1870	0.841
1871	0.766
1872	0.989
1873	1.275
1874	1.009
1875	1.147
1876	0.98
1877	0.812
1878	1.036
1879	0.953
1880	1.235
1881	1.239
1882	1.207
1883	0.9
1884	1.112
1885	1.063
1886	0.97
1887	0.849
1888	0.916
1889	1.041
1890	1.145
1891	0.933
1892	1.149
1893	1.17
1894	1.168
1895	1.327
1896	1.146
1897	1.079
1898	0.928
1899	1.022
1900	0.913
1901	1.177
1902	0.829
1903	0.935
1904	0.987
1905	1.065
1906	0.867
1907	0.926
1908	1.159
1909	0.959
1910	1.114
1911	1.15
1912	0.773
1913	0.791
1914	0.919
1915	0.75
1916	0.986
1917	1.052
1918	0.915
1919	0.916
1920	0.846
1921	0.97
1922	0.959
1923	0.972
1924	1.289
1925	1.331
1926	1.026
1927	0.91
1928	0.982
1929	1.116
1930	1.055
1931	1.146
1932	1.127
1933	1.091
1934	1.31
1935	1.29
1936	1.127
1937	1.142
1938	0.941
1939	0.923
1940	0.896
1941	0.943
1942	0.836
1943	0.973
1944	0.967
1945	1.11
1946	1.072
1947	1.398
1948	0.751
1949	0.918
1950	0.847
1951	1.013
1952	1.132
1953	1.205
1954	0.887
1955	1.036
1956	0.788
1957	0.822
1958	0.745
1959	0.785
1960	0.748
1961	0.669
1962	0.623
1963	0.921
1964	0.906
1965	0.782
1966	1.114
1967	1.128
1968	1.142
1969	1.114
1970	1.083
1971	0.92
1972	0.869
1973	1.089
1974	0.681
1975	0.745
1976	0.477
1977	0.561