# asia_russ090w - Ust Nera - 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/4708
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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_russ090w - Ust Nera - 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: Ust Nera
#	Location:
#	Country: Russia
#	Northernmost_Latitude: 64.53
#	Southernmost_Latitude: 64.53
#	Easternmost_Longitude: 143.12
#	Westernmost_Longitude: 143.12
#	Elevation: 600 m
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# Data_Collection
#	Collection_Name: asia_russ090wB
#	Earliest_Year: 1719
#	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":"3.50317190075","T2":"15.6030608054","M1":"0.0229827671838","M2":"0.479059721539"}}
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# Species
#	Species_Name: Dahurian larch
#	Species_Code: LAGM
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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
1719	1.024
1720	0.852
1721	0.978
1722	1.287
1723	1.417
1724	0.912
1725	0.89
1726	0.759
1727	1.193
1728	0.596
1729	1.147
1730	0.902
1731	1.161
1732	1.31
1733	1.184
1734	1.327
1735	1.105
1736	0.83
1737	1.052
1738	0.69
1739	0.877
1740	0.73
1741	1.214
1742	1.563
1743	1.549
1744	1.145
1745	1.388
1746	1.347
1747	1.293
1748	1.031
1749	1.12
1750	1.147
1751	1.234
1752	0.954
1753	0.725
1754	0.883
1755	1.22
1756	1.035
1757	0.994
1758	1.138
1759	1.09
1760	1.104
1761	0.681
1762	0.553
1763	0.809
1764	0.329
1765	0.55
1766	0.509
1767	0.592
1768	0.52
1769	0.817
1770	0.549
1771	0.466
1772	0.491
1773	0.57
1774	0.49
1775	0.483
1776	0.514
1777	0.215
1778	0.452
1779	0.468
1780	0.357
1781	0.432
1782	0.516
1783	0.485
1784	0.399
1785	0.457
1786	0.524
1787	0.529
1788	0.297
1789	0.504
1790	0.605
1791	0.489
1792	0.545
1793	0.587
1794	0.601
1795	0.592
1796	0.338
1797	0.157
1798	0.507
1799	0.499
1800	0.622
1801	0.809
1802	1.202
1803	1.206
1804	1.196
1805	1.606
1806	1.806
1807	1.512
1808	1.198
1809	1.555
1810	1.762
1811	2.263
1812	1.677
1813	1.877
1814	1.839
1815	1.984
1816	2.375
1817	1.688
1818	0.598
1819	1.586
1820	1.359
1821	1.64
1822	1.684
1823	1.137
1824	1.599
1825	1.817
1826	1.706
1827	1.775
1828	1.589
1829	1.599
1830	1.9
1831	1.268
1832	1.103
1833	1.377
1834	1.378
1835	1.374
1836	1.346
1837	1.253
1838	1.146
1839	0.935
1840	1.06
1841	1.217
1842	0.793
1843	0.746
1844	0.939
1845	0.821
1846	0.783
1847	0.901
1848	0.759
1849	0.825
1850	0.781
1851	0.614
1852	0.746
1853	0.801
1854	0.733
1855	0.704
1856	0.716
1857	0.73
1858	0.975
1859	0.994
1860	0.707
1861	1.046
1862	0.748
1863	0.667
1864	0.7
1865	0.74
1866	0.986
1867	0.981
1868	0.821
1869	0.943
1870	0.899
1871	0.506
1872	0.907
1873	0.887
1874	0.837
1875	0.859
1876	0.953
1877	0.725
1878	0.963
1879	0.851
1880	0.877
1881	0.805
1882	0.386
1883	0.815
1884	0.965
1885	0.623
1886	0.685
1887	1.014
1888	0.941
1889	0.795
1890	1.243
1891	1.343
1892	1.132
1893	1.44
1894	0.808
1895	1.379
1896	1.059
1897	1.051
1898	1.373
1899	1.65
1900	1.407
1901	1.564
1902	1.689
1903	1.55
1904	1.604
1905	1.447
1906	1.935
1907	1.643
1908	1.45
1909	0.898
1910	0.919
1911	1.104
1912	1.251
1913	1.162
1914	0.904
1915	0.984
1916	1.157
1917	0.924
1918	1.096
1919	1.248
1920	1.365
1921	1.161
1922	1.307
1923	1.099
1924	0.887
1925	0.831
1926	0.843
1927	0.918
1928	0.899
1929	1.137
1930	1.098
1931	0.569
1932	0.983
1933	0.938
1934	0.785
1935	0.966
1936	0.924
1937	0.95
1938	1.067
1939	1.004
1940	1.005
1941	0.816
1942	0.993
1943	0.951
1944	1.036
1945	0.713
1946	1.072
1947	0.959
1948	1.126
1949	0.718
1950	0.742
1951	0.969
1952	0.671
1953	0.473
1954	0.828
1955	0.687
1956	0.764
1957	0.692
1958	0.691
1959	0.754
1960	0.875
1961	0.632
1962	0.704
1963	0.707
1964	0.757
1965	0.639
1966	0.703
1967	0.71
1968	0.528
1969	0.749
1970	0.686
1971	0.718
1972	0.439
1973	0.63
1974	0.776
1975	0.754
1976	0.621
1977	0.648
1978	0.971
1979	0.586
1980	0.579
1981	0.653
1982	0.468
1983	0.592
1984	0.725
1985	0.714
1986	0.779
1987	0.737
1988	0.729
1989	0.704
1990	0.621
1991	0.925