# asia_russ154w - Jama 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/4445
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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_russ154w - Jama 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
#--------------------
# 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: Jama river
#	Location:
#	Country: Russia
#	Northernmost_Latitude: 59.78
#	Southernmost_Latitude: 59.78
#	Easternmost_Longitude: 154.0
#	Westernmost_Longitude: 154.0
#	Elevation: 80 m
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# Data_Collection
#	Collection_Name: asia_russ154wB
#	Earliest_Year: 1858
#	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":"4.77551949885","T2":"17.0918029549","M1":"0.0229445547704","M2":"0.423174843054"}}
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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
1858	0.981
1859	0.932
1860	0.682
1861	0.669
1862	0.667
1863	0.851
1864	0.255
1865	0.377
1866	0.361
1867	0.258
1868	0.688
1869	0.771
1870	1.108
1871	1.175
1872	1.497
1873	0.828
1874	1.028
1875	0.768
1876	0.446
1877	0.755
1878	0.998
1879	0.77
1880	0.919
1881	1.056
1882	1.298
1883	0.918
1884	1.212
1885	1.276
1886	0.993
1887	0.918
1888	0.958
1889	1.423
1890	1.476
1891	1.081
1892	1.201
1893	1.185
1894	1.157
1895	0.951
1896	1.275
1897	1.143
1898	1.281
1899	1.16
1900	1.274
1901	1.218
1902	0.931
1903	0.957
1904	0.716
1905	1.137
1906	1.123
1907	1.365
1908	1.345
1909	1.259
1910	1.019
1911	0.655
1912	0.841
1913	1.306
1914	0.841
1915	1.178
1916	1.594
1917	1.535
1918	0.428
1919	0.391
1920	0.618
1921	1.172
1922	1.018
1923	0.892
1924	0.905
1925	0.862
1926	1.187
1927	1.495
1928	1.225
1929	1.71
1930	0.898
1931	1.163
1932	1.277
1933	1.595
1934	0.743
1935	0.881
1936	0.971
1937	1.005
1938	1.155
1939	0.991
1940	0.616
1941	0.991
1942	0.787
1943	0.589
1944	0.889
1945	1.137
1946	1.011
1947	0.718
1948	0.952
1949	0.759
1950	0.887
1951	1.262
1952	0.764
1953	0.879
1954	1.421
1955	0.837
1956	1.034
1957	0.898
1958	0.582
1959	1.231
1960	1.095
1961	0.762
1962	0.725
1963	1.033
1964	1.462
1965	0.906
1966	1.098
1967	1.441
1968	1.116
1969	0.697
1970	0.579
1971	0.676
1972	0.697
1973	1.014
1974	0.75
1975	0.847
1976	0.447
1977	0.68
1978	0.611
1979	0.558
1980	0.397
1981	0.655
1982	0.771
1983	1.413
1984	0.79
1985	0.904
1986	0.94
1987	1.018
1988	1.128
1989	1.54
1990	1.34
1991	1.261
1992	1.442
1993	1.721
1994	0.7