# asia_russ178w - Markovo - 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/4526
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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_russ178w - Markovo - 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: Markovo
#	Location:
#	Country: Russia
#	Northernmost_Latitude: 64.83
#	Southernmost_Latitude: 64.83
#	Easternmost_Longitude: 169.0
#	Westernmost_Longitude: 169.0
#	Elevation: nan m
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# Data_Collection
#	Collection_Name: asia_russ178wB
#	Earliest_Year: 1849
#	Most_Recent_Year: 1998
#	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":"5.09299888798","T2":"17.8505996516","M1":"0.0225298768911","M2":"0.297086345211"}}
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# Species
#	Species_Name: Dahurian larch
#	Species_Code: LAGM
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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
1849	0.578
1850	0.796
1851	0.673
1852	0.749
1853	0.848
1854	0.894
1855	0.948
1856	0.767
1857	0.627
1858	1.08
1859	0.982
1860	1.132
1861	1.276
1862	0.575
1863	0.958
1864	0.963
1865	0.63
1866	0.982
1867	0.506
1868	0.807
1869	1.029
1870	1.236
1871	0.897
1872	0.782
1873	0.999
1874	1.166
1875	1.057
1876	1.348
1877	1.378
1878	1.652
1879	1.237
1880	1.324
1881	0.956
1882	1.203
1883	0.764
1884	1.422
1885	0.745
1886	1.088
1887	1.172
1888	1.314
1889	1.267
1890	0.94
1891	1.026
1892	0.615
1893	1.355
1894	1.512
1895	1.124
1896	1.249
1897	0.839
1898	0.913
1899	1.126
1900	1.368
1901	1.158
1902	1.57
1903	1.078
1904	1.164
1905	0.84
1906	1.088
1907	1.017
1908	1.196
1909	0.751
1910	0.847
1911	0.833
1912	0.603
1913	0.584
1914	0.874
1915	1.012
1916	1.111
1917	0.534
1918	0.735
1919	0.969
1920	0.802
1921	0.684
1922	0.867
1923	0.653
1924	0.926
1925	0.935
1926	0.712
1927	0.831
1928	0.717
1929	0.508
1930	0.556
1931	0.702
1932	0.825
1933	0.646
1934	0.809
1935	0.505
1936	0.54
1937	0.87
1938	0.936
1939	0.829
1940	0.707
1941	0.873
1942	0.805
1943	1.005
1944	0.813
1945	0.945
1946	0.77
1947	0.988
1948	1.304
1949	0.872
1950	0.377
1951	0.874
1952	0.537
1953	0.774
1954	0.756
1955	0.872
1956	0.908
1957	0.8
1958	1.341
1959	0.815
1960	1.339
1961	1.203
1962	0.761
1963	1.076
1964	1.647
1965	0.975
1966	1.133
1967	0.929
1968	1.217
1969	0.454
1970	1.543
1971	1.042
1972	0.948
1973	1.07
1974	0.824
1975	1.083
1976	1.213
1977	0.988
1978	0.528
1979	1.355
1980	0.769
1981	0.97
1982	0.655
1983	1.386
1984	0.744
1985	1.247
1986	1.089
1987	0.907
1988	1.118
1989	1.518
1990	1.399
1991	2.223
1992	1.204
1993	1.142
1994	1.293
1995	1.807
1996	1.178
1997	1.966
1998	1.513