# asia_russ028w - 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/4486
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# Description/Documentation lines begin with #
# Data lines have no #
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# Archive: Tree Rings
#--------------------
# Contribution_Date
#	Date: 2016-01-07
#--------------------
# Title
#	Study_Name: asia_russ028w - 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.
#--------------------
#	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
#--------------------
# Data_Collection
#	Collection_Name: asia_russ028wB
#	Earliest_Year: 1681
#	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":"5.68266776584","T2":"19.6274748381","M1":"0.0223663750867","M2":"0.316960094272"}}
#--------------------
# Species
#	Species_Name: Siberian larch
#	Species_Code: LASI
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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
#
#--------------------
# Data:
# Data lines follow (have no #)
# Data line format - tab-delimited text, variable short name as header
# Missing Values: nan
#
age	trsgi
1681	0.404
1682	0.683
1683	0.601
1684	0.713
1685	0.968
1686	0.906
1687	1.191
1688	1.483
1689	1.038
1690	1.021
1691	0.862
1692	0.707
1693	1.151
1694	0.278
1695	1.293
1696	0.626
1697	0.608
1698	0.776
1699	0.408
1700	1.06
1701	0.972
1702	0.667
1703	0.602
1704	0.543
1705	0.593
1706	0.503
1707	0.915
1708	0.601
1709	1.01
1710	0.72
1711	0.706
1712	0.735
1713	0.662
1714	0.549
1715	1.067
1716	0.898
1717	1.301
1718	0.667
1719	0.752
1720	0.715
1721	0.993
1722	0.88
1723	0.869
1724	1.212
1725	0.939
1726	0.823
1727	1.222
1728	0.95
1729	1.284
1730	1.353
1731	1.421
1732	0.481
1733	1.093
1734	0.863
1735	1.054
1736	0.909
1737	0.777
1738	0.424
1739	0.911
1740	1.267
1741	0.91
1742	0.283
1743	1.809
1744	1.583
1745	0.993
1746	0.993
1747	1.699
1748	1.411
1749	0.738
1750	0.642
1751	0.909
1752	0.415
1753	0.66
1754	0.905
1755	0.744
1756	1.131
1757	1.19
1758	1.476
1759	0.594
1760	0.772
1761	1.091
1762	1.499
1763	1.073
1764	1.44
1765	1.505
1766	1.693
1767	1.807
1768	0.85
1769	1.429
1770	0.762
1771	1.21
1772	0.817
1773	0.435
1774	0.833
1775	1.55
1776	1.008
1777	1.406
1778	1.136
1779	0.969
1780	0.944
1781	1.182
1782	1.56
1783	0.69
1784	1.202
1785	1.018
1786	1.005
1787	1.021
1788	0.651
1789	1.087
1790	1.292
1791	1.127
1792	1.014
1793	2.135
1794	1.878
1795	1.219
1796	1.248
1797	0.653
1798	0.835
1799	1.213
1800	0.896
1801	1.217
1802	0.991
1803	1.019
1804	1.293
1805	1.506
1806	1.665
1807	0.6
1808	0.982
1809	1.425
1810	1.253
1811	1.198
1812	0.685
1813	1.065
1814	1.331
1815	1.064
1816	0.786
1817	1.395
1818	0.813
1819	0.309
1820	0.862
1821	0.937
1822	1.008
1823	0.785
1824	0.641
1825	0.379
1826	0.583
1827	1.105
1828	0.369
1829	1.159
1830	0.28
1831	0.878
1832	0.454
1833	0.196
1834	0.586
1835	0.434
1836	0.328
1837	0.477
1838	0.551
1839	0.929
1840	1.069
1841	0.889
1842	1.194
1843	0.451
1844	1.131
1845	0.631
1846	0.621
1847	1.005
1848	0.863
1849	0.976
1850	1.184
1851	1.332
1852	1.074
1853	1.289
1854	1.154
1855	0.996
1856	0.82
1857	0.52
1858	0.582
1859	0.776
1860	0.912
1861	1.084
1862	0.822
1863	1.147
1864	1.109
1865	1.051
1866	0.675
1867	0.081
1868	1.132
1869	0.319
1870	1.148
1871	0.949
1872	0.947
1873	0.736
1874	0.427
1875	0.939
1876	0.849
1877	1.16
1878	1.019
1879	1.606
1880	1.29
1881	0.926
1882	0.69
1883	0.925
1884	0.66
1885	0.283
1886	0.998
1887	0.865
1888	0.829
1889	0.536
1890	0.722
1891	0.973
1892	1.077
1893	0.912
1894	1.105
1895	0.49
1896	1.532
1897	1.583
1898	1.323
1899	0.608
1900	0.735
1901	0.524
1902	0.836
1903	1.017
1904	0.94
1905	0.715
1906	0.776
1907	0.43
1908	1.497
1909	0.89
1910	0.693
1911	0.607
1912	1.037
1913	0.726
1914	0.871
1915	1.354
1916	0.765
1917	1.166
1918	1.253
1919	1.097
1920	1.18
1921	0.885
1922	1.302
1923	1.631
1924	1.638
1925	0.877
1926	1.228
1927	1.045
1928	1.375
1929	0.974
1930	1.42
1931	0.935
1932	1.045
1933	1.076
1934	1.208
1935	1.012
1936	1.247
1937	0.958
1938	1.078
1939	1.026
1940	0.943
1941	0.919
1942	1.34
1943	1.517
1944	1.508
1945	1.548
1946	1.228
1947	0.721
1948	1.046
1949	0.198
1950	0.879
1951	0.405
1952	0.894
1953	1.143
1954	1.057
1955	1.581
1956	1.264
1957	1.375
1958	1.349
1959	1.557
1960	1.275
1961	1.191
1962	1.411
1963	1.294
1964	1.301
1965	1.193
1966	0.888
1967	1.275
1968	0.657
1969	0.794
1970	0.863
1971	0.598
1972	1.064
1973	0.47
1974	0.468
1975	0.794
1976	1.127
1977	0.941
1978	0.877
1979	1.117
1980	0.815
1981	0.825
1982	0.765
1983	1.101
1984	1.476
1985	1.405
1986	1.562
1987	1.279
1988	1.178
1989	0.746
1990	1.121