# asia_russ180w - Muzhy-Settlement - 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/4548
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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: asia_russ180w - Muzhy-Settlement - 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: Muzhy-Settlement
#	Location:
#	Country: Russia
#	Northernmost_Latitude: 65.32
#	Southernmost_Latitude: 65.32
#	Easternmost_Longitude: 64.65
#	Westernmost_Longitude: 64.65
#	Elevation: 30 m
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# Data_Collection
#	Collection_Name: asia_russ180wB
#	Earliest_Year: 1847
#	Most_Recent_Year: 1994
#	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":"6.24175693411","T2":"19.0065335406","M1":"0.0224506353807","M2":"0.226025039444"}}
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# Species
#	Species_Name: Siberian larch
#	Species_Code: LASI
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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
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age	trsgi
1847	1.212
1848	0.97
1849	1.239
1850	1.382
1851	1.411
1852	0.914
1853	1.127
1854	1.098
1855	0.753
1856	0.871
1857	0.706
1858	0.565
1859	0.55
1860	0.654
1861	0.784
1862	0.571
1863	0.319
1864	0.705
1865	0.752
1866	0.576
1867	0.647
1868	0.843
1869	0.896
1870	1.137
1871	0.813
1872	0.686
1873	0.577
1874	0.693
1875	1.081
1876	0.974
1877	1.231
1878	1.406
1879	0.939
1880	1.09
1881	0.673
1882	0.547
1883	0.53
1884	0.77
1885	0.724
1886	0.784
1887	0.963
1888	0.92
1889	0.615
1890	1.053
1891	0.764
1892	1.05
1893	0.805
1894	0.766
1895	1.191
1896	1.417
1897	1.585
1898	1.42
1899	0.77
1900	1.196
1901	1.345
1902	1.424
1903	0.829
1904	1.141
1905	0.832
1906	1.155
1907	1.133
1908	0.985
1909	1.201
1910	1.368
1911	1.521
1912	0.842
1913	1.31
1914	0.933
1915	1.541
1916	0.925
1917	0.965
1918	1.227
1919	0.775
1920	1.265
1921	1.548
1922	1.998
1923	2.036
1924	1.383
1925	1.409
1926	1.443
1927	1.171
1928	1.266
1929	0.714
1930	0.646
1931	0.726
1932	0.497
1933	0.78
1934	0.934
1935	1.063
1936	0.969
1937	1.332
1938	1.49
1939	1.551
1940	1.36
1941	1.377
1942	1.645
1943	0.945
1944	1.284
1945	1.188
1946	0.713
1947	0.542
1948	1.227
1949	0.733
1950	1.343
1951	0.955
1952	1.485
1953	1.338
1954	1.121
1955	0.945
1956	1.281
1957	0.804
1958	0.736
1959	0.805
1960	0.774
1961	0.781
1962	0.82
1963	1.368
1964	1.352
1965	1.126
1966	0.771
1967	0.442
1968	0.675
1969	0.684
1970	0.321
1971	0.328
1972	0.534
1973	0.575
1974	0.631
1975	0.511
1976	0.681
1977	0.813
1978	0.769
1979	0.636
1980	0.685
1981	0.815
1982	0.805
1983	1.117
1984	1.116
1985	0.859
1986	0.728
1987	0.678
1988	0.7
1989	0.81
1990	0.752
1991	1.148
1992	1.026
1993	1.193
1994	1.232