# asia_russ074w - Nyuchpas - 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/4571
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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
#--------------------
# Title
#	Study_Name: asia_russ074w - Nyuchpas - 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: Nyuchpas
#	Location:
#	Country: Russia
#	Northernmost_Latitude: 60.7
#	Southernmost_Latitude: 60.7
#	Easternmost_Longitude: 51.38
#	Westernmost_Longitude: 51.38
#	Elevation: 160 m
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# Data_Collection
#	Collection_Name: asia_russ074wB
#	Earliest_Year: 1728
#	Most_Recent_Year: 1991
#	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":"3.95893087874","T2":"19.5194152466","M1":"0.0217280868092","M2":"0.2139506689"}}
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# Species
#	Species_Name: Scots pine
#	Species_Code: PISY
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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)
#
##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
1728	0.699
1729	0.91
1730	0.911
1731	0.911
1732	1.159
1733	1.08
1734	0.94
1735	0.765
1736	0.824
1737	0.932
1738	1.086
1739	1.142
1740	0.727
1741	0.648
1742	0.886
1743	1.089
1744	0.849
1745	0.935
1746	0.707
1747	0.741
1748	0.767
1749	0.642
1750	0.697
1751	0.79
1752	0.952
1753	0.814
1754	0.917
1755	0.962
1756	0.936
1757	1.071
1758	1.153
1759	1.262
1760	0.975
1761	1.319
1762	1.344
1763	1.032
1764	0.984
1765	1.012
1766	1.06
1767	1.073
1768	1.093
1769	0.877
1770	0.914
1771	0.999
1772	1.022
1773	0.95
1774	1.021
1775	1.037
1776	0.929
1777	1.039
1778	1.024
1779	0.985
1780	1.077
1781	1.127
1782	1.069
1783	0.903
1784	1.137
1785	1.06
1786	0.905
1787	0.848
1788	0.977
1789	0.855
1790	1.113
1791	0.983
1792	0.91
1793	0.962
1794	1.191
1795	1.162
1796	1.738
1797	1.388
1798	1.449
1799	1.24
1800	1.129
1801	1.199
1802	1.078
1803	0.812
1804	0.902
1805	0.927
1806	0.653
1807	0.773
1808	0.955
1809	0.977
1810	0.647
1811	0.614
1812	0.767
1813	0.797
1814	0.91
1815	0.851
1816	0.615
1817	0.64
1818	0.675
1819	0.599
1820	0.741
1821	1.266
1822	1.024
1823	1.056
1824	1.054
1825	1.02
1826	1.058
1827	1.111
1828	0.96
1829	1.065
1830	1.258
1831	1.186
1832	1.466
1833	1.22
1834	1.272
1835	1.238
1836	0.947
1837	0.958
1838	0.981
1839	1.084
1840	0.93
1841	1.109
1842	1.163
1843	0.972
1844	1.036
1845	0.824
1846	0.891
1847	0.972
1848	0.969
1849	1.191
1850	1.272
1851	1.048
1852	1.037
1853	0.934
1854	1.203
1855	1.017
1856	1.169
1857	1.024
1858	0.867
1859	0.984
1860	0.931
1861	0.915
1862	0.803
1863	0.717
1864	1.039
1865	0.857
1866	0.951
1867	0.638
1868	0.749
1869	0.819
1870	0.762
1871	0.747
1872	0.636
1873	0.628
1874	0.706
1875	0.857
1876	0.984
1877	1.118
1878	1.186
1879	1.147
1880	1.133
1881	1.111
1882	0.985
1883	0.891
1884	1.034
1885	0.99
1886	0.768
1887	0.696
1888	0.855
1889	0.937
1890	1.378
1891	1.48
1892	1.315
1893	1.52
1894	1.062
1895	0.873
1896	0.815
1897	0.759
1898	1.007
1899	1.033
1900	1.113
1901	1.143
1902	1.397
1903	0.658
1904	0.952
1905	1.112
1906	1.275
1907	1.171
1908	0.853
1909	1.135
1910	1.202
1911	1.09
1912	1.061
1913	1.037
1914	1.066
1915	1.158
1916	0.937
1917	0.949
1918	0.984
1919	0.954
1920	0.866
1921	0.687
1922	0.712
1923	0.513
1924	0.452
1925	0.541
1926	0.501
1927	0.739
1928	0.701
1929	0.734
1930	0.707
1931	0.715
1932	0.84
1933	0.815
1934	0.927
1935	0.937
1936	0.882
1937	0.895
1938	0.78
1939	0.504
1940	0.336
1941	0.231
1942	0.319
1943	0.552
1944	0.607
1945	0.661
1946	0.847
1947	0.957
1948	0.957
1949	1.14
1950	1.051
1951	1.179
1952	1.131
1953	1.137
1954	1.321
1955	1.132
1956	1.259
1957	1.343
1958	1.149
1959	1.062
1960	1.438
1961	1.52
1962	1.121
1963	1.029
1964	1.379
1965	1.308
1966	1.427
1967	1.552
1968	1.469
1969	0.787
1970	1.045
1971	1.126
1972	0.908
1973	1.103
1974	1.173
1975	1.098
1976	1.008
1977	1.031
1978	1.077
1979	0.93
1980	1.117
1981	1.471
1982	1.319
1983	1.029
1984	1.308
1985	1.097
1986	0.879
1987	0.866
1988	0.943
1989	0.754
1990	0.853
1991	0.82