# europe_swit170w - Crete de la Neige, GE - 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/4393
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# Description/Documentation lines begin with #
# Data lines have no #
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# Archive: Tree Rings
#--------------------
# Contribution_Date
#	Date: 2016-01-07
#--------------------
# Title
#	Study_Name: europe_swit170w - Crete de la Neige, GE - Breitenmoser Tree Ring Chronology Data
#--------------------
# 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:
#--------------------
#	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: Crete de la Neige, GE
#	Location:
#	Country: Switzerland
#	Northernmost_Latitude: 46.27
#	Southernmost_Latitude: 46.27
#	Easternmost_Longitude: 5.93
#	Westernmost_Longitude: 5.93
#	Elevation: 1700 m
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# Data_Collection
#	Collection_Name: europe_swit170wB
#	Earliest_Year: 1788
#	Most_Recent_Year: 1987
#	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":"5.19898935466","T2":"16.678145856","M1":"0.0223448948421","M2":"0.53473097495"}}
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# Species
#	Species_Name: krummholz pine
#	Species_Code: PIMU
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# Chronology:
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# Variables
#
# 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
1788	1.161
1789	1.101
1790	1.041
1791	1.285
1792	0.984
1793	0.773
1794	1.136
1795	0.994
1796	1.032
1797	0.971
1798	1.248
1799	1.178
1800	1.292
1801	1.038
1802	1.164
1803	0.98
1804	1.004
1805	1.053
1806	1.104
1807	1.293
1808	1.588
1809	1.246
1810	1.123
1811	1.141
1812	1.103
1813	0.768
1814	0.949
1815	0.962
1816	0.728
1817	0.41
1818	0.461
1819	0.581
1820	0.636
1821	0.596
1822	0.896
1823	1.005
1824	0.958
1825	1.116
1826	1.023
1827	0.94
1828	1.178
1829	1.17
1830	0.618
1831	0.976
1832	0.523
1833	0.678
1834	0.954
1835	0.745
1836	0.46
1837	0.714
1838	0.767
1839	0.713
1840	1.069
1841	1.157
1842	1.22
1843	1.048
1844	1.378
1845	1.244
1846	1.265
1847	1.06
1848	1.148
1849	1.097
1850	0.949
1851	0.933
1852	1.12
1853	0.959
1854	0.896
1855	0.747
1856	0.727
1857	0.9
1858	0.896
1859	0.916
1860	0.768
1861	1.047
1862	1.138
1863	0.997
1864	0.911
1865	1.054
1866	1.142
1867	0.954
1868	1.053
1869	1.095
1870	0.718
1871	0.997
1872	1.053
1873	1.067
1874	1.317
1875	1.487
1876	0.963
1877	1.027
1878	0.85
1879	0.898
1880	0.868
1881	1.332
1882	1.286
1883	1.042
1884	1.451
1885	1.331
1886	1.035
1887	1.155
1888	0.758
1889	1.077
1890	0.856
1891	0.837
1892	1.222
1893	1.344
1894	1.089
1895	0.816
1896	1.009
1897	0.918
1898	1.176
1899	1.04
1900	0.845
1901	0.85
1902	0.676
1903	1.257
1904	1.104
1905	1.144
1906	1.051
1907	1.138
1908	1.092
1909	1.073
1910	0.805
1911	0.655
1912	0.708
1913	0.621
1914	0.891
1915	0.857
1916	0.678
1917	0.845
1918	0.731
1919	0.818
1920	0.769
1921	0.948
1922	0.729
1923	0.94
1924	0.816
1925	0.954
1926	0.763
1927	0.751
1928	0.601
1929	0.692
1930	0.827
1931	0.81
1932	0.877
1933	0.858
1934	1.062
1935	0.862
1936	0.883
1937	0.648
1938	0.905
1939	0.902
1940	0.554
1941	0.528
1942	0.853
1943	0.971
1944	1.086
1945	0.483
1946	0.927
1947	0.889
1948	0.737
1949	0.519
1950	0.705
1951	1.079
1952	0.893
1953	0.737
1954	1.108
1955	1.193
1956	0.928
1957	0.851
1958	1.405
1959	1.485
1960	1.182
1961	0.806
1962	0.599
1963	0.702
1964	0.825
1965	1.006
1966	1.097
1967	1.287
1968	1.443
1969	1.556
1970	1.747
1971	1.57
1972	1.404
1973	1.125
1974	1.246
1975	0.984
1976	0.955
1977	1.203
1978	0.97
1979	1.019
1980	0.994
1981	0.967
1982	1.218
1983	1.263
1984	0.931
1985	1.508
1986	1.157
1987	1.389