# asia_russ082w - Yevoyakha River - 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/4744
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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_russ082w - Yevoyakha River - 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:
#--------------------
#	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: Yevoyakha River
#	Location:
#	Country: Russia
#	Northernmost_Latitude: 66.08
#	Southernmost_Latitude: 66.08
#	Easternmost_Longitude: 77.68
#	Westernmost_Longitude: 77.68
#	Elevation: 30 m
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# Data_Collection
#	Collection_Name: asia_russ082wB
#	Earliest_Year: 1844
#	Most_Recent_Year: 1990
#	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":"6.5882721833","T2":"19.3594220238","M1":"0.0226639640256","M2":"0.308593655313"}}
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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
#
age	trsgi
1844	1.526
1845	1.762
1846	1.617
1847	1.232
1848	1.056
1849	1.221
1850	1.185
1851	1.191
1852	1.065
1853	1.037
1854	0.801
1855	0.603
1856	1.011
1857	0.977
1858	1.023
1859	1.052
1860	0.934
1861	1.315
1862	0.777
1863	1.009
1864	0.616
1865	0.879
1866	0.987
1867	0.207
1868	1.307
1869	1.072
1870	1.989
1871	1.508
1872	1.402
1873	0.981
1874	1.232
1875	1.384
1876	1.185
1877	1.504
1878	1.733
1879	1.473
1880	0.858
1881	0.441
1882	0.202
1883	0.497
1884	0.245
1885	0.274
1886	0.569
1887	0.578
1888	0.55
1889	0.625
1890	1.009
1891	0.61
1892	1.219
1893	0.97
1894	1.178
1895	0.87
1896	0.879
1897	0.958
1898	1.706
1899	0.734
1900	1.455
1901	0.863
1902	1.41
1903	1.144
1904	1.368
1905	0.928
1906	1.373
1907	0.594
1908	0.755
1909	1.106
1910	0.971
1911	1.162
1912	0.716
1913	0.935
1914	0.462
1915	0.958
1916	0.282
1917	0.718
1918	0.957
1919	0.872
1920	0.982
1921	1.207
1922	1.111
1923	1.589
1924	1.328
1925	1.106
1926	1.395
1927	0.79
1928	1.035
1929	1.098
1930	0.537
1931	0.437
1932	0.535
1933	0.648
1934	0.428
1935	0.631
1936	0.531
1937	0.688
1938	0.907
1939	1.294
1940	1.089
1941	0.684
1942	1.186
1943	1.208
1944	1.36
1945	1.779
1946	1.259
1947	0.616
1948	1.126
1949	0.666
1950	1.034
1951	0.671
1952	0.868
1953	1.043
1954	0.783
1955	1.352
1956	1.282
1957	1.05
1958	1.41
1959	1.418
1960	1.235
1961	1.279
1962	1.171
1963	1.08
1964	1.36
1965	1.17
1966	0.707
1967	1.048
1968	0.694
1969	1.121
1970	0.706
1971	0.655
1972	0.728
1973	0.508
1974	0.761
1975	0.523
1976	0.736
1977	0.821
1978	0.95
1979	1.074
1980	0.897
1981	1.094
1982	1.059
1983	1.228
1984	1.249
1985	1.486
1986	1.365
1987	0.919
1988	0.748
1989	1.167
1990	0.915