# asia_russ030w - Kulyumbe River - Breitenmoser Tree Ring Chronology Data
#-----------------------------------------------------------------------
#		World Data Center for Paleoclimatology, Boulder
#				and
#		NOAA Paleoclimatology Program
#-----------------------------------------------------------------------
# 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/4487
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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_russ030w - Kulyumbe River - 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: Kulyumbe River
#	Location:
#	Country: Russia
#	Northernmost_Latitude: 67.97
#	Southernmost_Latitude: 67.97
#	Easternmost_Longitude: 88.92
#	Westernmost_Longitude: 88.92
#	Elevation: 160 m
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# Data_Collection
#	Collection_Name: asia_russ030wB
#	Earliest_Year: 1727
#	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":"5.66230286173","T2":"18.9900773136","M1":"0.0222379313529","M2":"0.328265064593"}}
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# Species
#	Species_Name: Siberian spruce
#	Species_Code: PCOB
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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
1727	0.943
1728	1.337
1729	1.491
1730	1.69
1731	1.289
1732	0.716
1733	1.025
1734	0.69
1735	0.69
1736	0.584
1737	0.851
1738	0.781
1739	1.3
1740	0.853
1741	0.705
1742	0.552
1743	1.04
1744	1.092
1745	0.725
1746	1.131
1747	1.351
1748	1.233
1749	1.309
1750	1.312
1751	1.039
1752	1.099
1753	1.11
1754	1.074
1755	0.813
1756	1.048
1757	0.992
1758	1.207
1759	0.756
1760	0.78
1761	1.092
1762	1.075
1763	1.403
1764	1.315
1765	1.588
1766	1.477
1767	1.48
1768	0.94
1769	1.216
1770	0.98
1771	0.993
1772	0.709
1773	0.64
1774	0.756
1775	1.233
1776	0.82
1777	1.143
1778	1.095
1779	0.944
1780	0.92
1781	0.904
1782	0.966
1783	0.754
1784	1.401
1785	1.102
1786	0.871
1787	1.249
1788	0.623
1789	0.952
1790	0.704
1791	0.635
1792	0.533
1793	0.983
1794	0.828
1795	0.935
1796	1.008
1797	0.715
1798	0.679
1799	0.926
1800	0.924
1801	1.243
1802	0.963
1803	0.915
1804	0.867
1805	1.353
1806	1.063
1807	0.453
1808	0.748
1809	1.028
1810	0.969
1811	0.915
1812	0.861
1813	1.229
1814	1.321
1815	1.101
1816	1.02
1817	0.895
1818	0.637
1819	0.357
1820	0.73
1821	0.784
1822	0.572
1823	0.686
1824	0.612
1825	0.477
1826	0.875
1827	0.969
1828	0.361
1829	0.796
1830	0.208
1831	0.791
1832	0.7
1833	0.412
1834	0.939
1835	1.028
1836	0.679
1837	0.725
1838	1.055
1839	0.801
1840	0.986
1841	0.918
1842	1.191
1843	0.876
1844	1.269
1845	1.174
1846	1.072
1847	0.842
1848	1.085
1849	0.856
1850	0.848
1851	0.994
1852	0.891
1853	0.928
1854	0.634
1855	0.539
1856	0.852
1857	1.049
1858	1.352
1859	0.897
1860	1.009
1861	1.4
1862	1.153
1863	1.57
1864	1.444
1865	1.425
1866	1.009
1867	0.237
1868	1.411
1869	0.744
1870	1.34
1871	0.929
1872	1.105
1873	1.041
1874	0.811
1875	1.056
1876	1.118
1877	1.31
1878	1.171
1879	1.221
1880	1.074
1881	0.795
1882	0.78
1883	0.945
1884	0.856
1885	0.704
1886	1.03
1887	0.716
1888	0.812
1889	0.635
1890	0.703
1891	1.023
1892	1.29
1893	1.222
1894	1.289
1895	0.67
1896	1.022
1897	1.337
1898	1.094
1899	1.024
1900	0.823
1901	0.932
1902	0.908
1903	1.127
1904	0.965
1905	0.998
1906	1.074
1907	0.64
1908	1.538
1909	1.355
1910	0.739
1911	0.854
1912	0.712
1913	1.03
1914	0.895
1915	1.398
1916	0.925
1917	1.189
1918	1.397
1919	1.127
1920	1.739
1921	1.214
1922	1.36
1923	1.22
1924	1.447
1925	1.159
1926	1.59
1927	1.145
1928	1.36
1929	0.873
1930	1.269
1931	0.825
1932	0.99
1933	1.165
1934	1.421
1935	1.13
1936	1.478
1937	1.227
1938	1.257
1939	1.267
1940	1.236
1941	0.907
1942	1.177
1943	1.052
1944	0.832
1945	1.147
1946	1.388
1947	1.176
1948	1.463
1949	1.139
1950	1.581
1951	0.976
1952	1.171
1953	1.376
1954	1.052
1955	1.095
1956	1.207
1957	1.098
1958	1.079
1959	1.404
1960	0.616
1961	0.68
1962	0.939
1963	0.747
1964	0.702
1965	0.963
1966	0.651
1967	0.989
1968	0.772
1969	1.177
1970	0.857
1971	0.584
1972	0.855
1973	0.514
1974	0.364
1975	0.877
1976	0.881
1977	0.647
1978	0.689
1979	0.976
1980	0.382
1981	0.561
1982	0.506
1983	0.804
1984	0.816
1985	0.669
1986	0.641
1987	0.407
1988	0.495
1989	0.355
1990	0.618