# asia_russ071w - Sidorovsk - 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/4643
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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_russ071w - Sidorovsk - 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: Sidorovsk
#	Location:
#	Country: Russia
#	Northernmost_Latitude: 66.67
#	Southernmost_Latitude: 66.67
#	Easternmost_Longitude: 82.33
#	Westernmost_Longitude: 82.33
#	Elevation: 15 m
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# Data_Collection
#	Collection_Name: asia_russ071wB
#	Earliest_Year: 1694
#	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":"5.42175540186","T2":"19.1000547336","M1":"0.0225977829842","M2":"0.241372265401"}}
#--------------------
# 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
1694	1.05
1695	1.54
1696	1.421
1697	0.937
1698	0.921
1699	0.518
1700	0.768
1701	0.662
1702	0.695
1703	0.813
1704	0.812
1705	1.079
1706	0.925
1707	0.912
1708	1.105
1709	1.202
1710	1.073
1711	0.906
1712	1.068
1713	0.964
1714	0.694
1715	0.792
1716	1.028
1717	0.986
1718	0.918
1719	1.33
1720	0.777
1721	0.987
1722	1.001
1723	0.926
1724	0.964
1725	0.962
1726	0.684
1727	1.249
1728	1.147
1729	1.199
1730	1.285
1731	1.195
1732	0.835
1733	0.991
1734	0.808
1735	0.947
1736	0.706
1737	0.976
1738	0.81
1739	0.69
1740	0.564
1741	0.593
1742	0.542
1743	0.712
1744	0.8
1745	0.683
1746	1.042
1747	0.904
1748	1.129
1749	1.225
1750	0.986
1751	0.767
1752	0.748
1753	0.861
1754	1.024
1755	0.764
1756	0.805
1757	0.987
1758	0.858
1759	0.838
1760	0.54
1761	0.938
1762	1.078
1763	1.15
1764	0.913
1765	0.994
1766	1.109
1767	1.056
1768	0.808
1769	1.004
1770	1.002
1771	1.078
1772	0.897
1773	1.187
1774	1.082
1775	1.119
1776	0.867
1777	0.901
1778	0.888
1779	0.584
1780	0.819
1781	0.834
1782	0.862
1783	0.649
1784	1.526
1785	0.889
1786	1.238
1787	0.881
1788	0.682
1789	0.929
1790	1.054
1791	0.855
1792	0.682
1793	0.962
1794	1.078
1795	1.156
1796	1.329
1797	1.086
1798	1.039
1799	0.989
1800	0.852
1801	0.912
1802	0.942
1803	0.94
1804	0.977
1805	0.994
1806	0.851
1807	0.686
1808	0.787
1809	1.326
1810	1.225
1811	0.774
1812	0.81
1813	0.898
1814	1.086
1815	0.932
1816	0.906
1817	0.951
1818	0.745
1819	0.591
1820	0.629
1821	0.651
1822	0.819
1823	1.389
1824	0.773
1825	0.655
1826	1.002
1827	0.952
1828	0.925
1829	1.209
1830	0.64
1831	0.941
1832	1.21
1833	0.75
1834	0.979
1835	1.233
1836	1.05
1837	1.051
1838	1.325
1839	0.85
1840	0.948
1841	0.822
1842	1.34
1843	0.929
1844	1.194
1845	1.177
1846	1.101
1847	0.863
1848	1.04
1849	0.84
1850	0.823
1851	0.979
1852	0.896
1853	1.142
1854	0.962
1855	0.941
1856	1.274
1857	1.065
1858	1.256
1859	1.253
1860	1.125
1861	1.313
1862	0.909
1863	1.191
1864	0.892
1865	1.059
1866	0.897
1867	0.345
1868	1.127
1869	0.615
1870	1.108
1871	0.777
1872	0.951
1873	0.988
1874	0.882
1875	0.88
1876	0.867
1877	1.068
1878	1.385
1879	1.183
1880	1.177
1881	0.897
1882	0.716
1883	0.951
1884	0.769
1885	0.75
1886	1.182
1887	0.661
1888	0.617
1889	0.683
1890	0.872
1891	0.82
1892	1.181
1893	1.066
1894	1.335
1895	1.114
1896	1.134
1897	1.461
1898	1.386
1899	1.04
1900	1.337
1901	0.917
1902	1.124
1903	1.181
1904	1.067
1905	1.052
1906	1.134
1907	0.658
1908	1.277
1909	1.259
1910	1.169
1911	1.316
1912	1.064
1913	1.208
1914	1.001
1915	1.366
1916	0.809
1917	1.027
1918	1.243
1919	0.895
1920	1.15
1921	1.23
1922	1.278
1923	1.226
1924	1.075
1925	0.988
1926	1.443
1927	1.348
1928	1.47
1929	1.242
1930	1.166
1931	1.016
1932	0.805
1933	0.886
1934	0.732
1935	1.208
1936	1.273
1937	1.193
1938	1.159
1939	1.153
1940	1.171
1941	0.955
1942	1.489
1943	1.152
1944	1.244
1945	1.266
1946	1.173
1947	0.976
1948	1.476
1949	0.952
1950	1.301
1951	0.58
1952	0.943
1953	1.181
1954	1.081
1955	1.187
1956	1.212
1957	1.006
1958	0.934
1959	1.098
1960	0.734
1961	0.826
1962	0.846
1963	0.892
1964	0.821
1965	1.044
1966	0.641
1967	1.044
1968	0.832
1969	1.207
1970	1.061
1971	0.705
1972	0.767
1973	0.588
1974	0.559
1975	0.582
1976	0.734
1977	0.722
1978	0.734
1979	0.826
1980	0.628
1981	0.738
1982	0.722
1983	0.933
1984	0.926
1985	0.862
1986	0.764
1987	0.703
1988	0.66
1989	0.817
1990	0.742