# asia_russ036w - Pinega - Breitenmoser Tree Ring Chronology Data
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#		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/4592
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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_russ036w - Pinega - 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: Pinega
#	Location:
#	Country: Russia
#	Northernmost_Latitude: 64.92
#	Southernmost_Latitude: 64.92
#	Easternmost_Longitude: 42.5
#	Westernmost_Longitude: 42.5
#	Elevation: 230 m
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# Data_Collection
#	Collection_Name: asia_russ036wB
#	Earliest_Year: 1687
#	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":"6.19112671341","T2":"19.0392007708","M1":"0.0223474707375","M2":"0.313658759759"}}
#--------------------
# 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
#
#--------------------
# Data:
# Data lines follow (have no #)
# Data line format - tab-delimited text, variable short name as header
# Missing Values: nan
#
age	trsgi
1687	1.688
1688	1.441
1689	1.525
1690	1.315
1691	1.316
1692	1.462
1693	1.319
1694	1.563
1695	1.413
1696	1.059
1697	1.059
1698	0.89
1699	0.707
1700	0.541
1701	0.569
1702	0.575
1703	0.524
1704	0.694
1705	0.828
1706	0.932
1707	0.784
1708	0.909
1709	0.577
1710	0.599
1711	0.775
1712	0.69
1713	0.66
1714	0.692
1715	0.689
1716	0.549
1717	0.65
1718	0.821
1719	0.694
1720	0.794
1721	0.859
1722	0.546
1723	0.831
1724	1.076
1725	1.079
1726	1.531
1727	1.25
1728	1.159
1729	0.9
1730	0.834
1731	0.721
1732	0.738
1733	0.727
1734	0.731
1735	0.78
1736	0.794
1737	0.753
1738	0.875
1739	0.808
1740	0.805
1741	0.867
1742	1.01
1743	1.095
1744	1.084
1745	1.186
1746	1.0
1747	0.84
1748	0.81
1749	0.862
1750	0.942
1751	1.014
1752	0.904
1753	1.268
1754	1.361
1755	1.39
1756	1.393
1757	1.408
1758	1.34
1759	1.153
1760	1.35
1761	1.295
1762	1.468
1763	1.242
1764	1.195
1765	1.097
1766	1.109
1767	1.449
1768	1.348
1769	1.068
1770	0.834
1771	1.141
1772	0.853
1773	0.794
1774	1.208
1775	1.089
1776	1.002
1777	0.943
1778	0.814
1779	0.775
1780	0.932
1781	0.811
1782	1.002
1783	0.992
1784	0.975
1785	1.075
1786	0.906
1787	0.895
1788	0.98
1789	0.85
1790	0.901
1791	1.096
1792	1.113
1793	1.165
1794	1.017
1795	1.288
1796	1.473
1797	1.435
1798	1.102
1799	1.119
1800	1.087
1801	0.978
1802	1.174
1803	0.881
1804	1.02
1805	1.254
1806	0.809
1807	0.923
1808	0.943
1809	1.168
1810	0.731
1811	0.834
1812	1.011
1813	0.429
1814	0.572
1815	0.609
1816	0.405
1817	0.359
1818	0.5
1819	0.582
1820	0.51
1821	0.488
1822	0.543
1823	0.709
1824	0.689
1825	0.601
1826	0.776
1827	0.797
1828	0.795
1829	0.96
1830	1.071
1831	1.01
1832	1.026
1833	1.018
1834	0.878
1835	0.869
1836	0.592
1837	0.623
1838	0.505
1839	0.63
1840	0.526
1841	0.695
1842	1.05
1843	0.973
1844	1.039
1845	1.111
1846	1.214
1847	1.41
1848	1.319
1849	1.469
1850	1.626
1851	1.9
1852	1.446
1853	1.351
1854	1.117
1855	1.031
1856	1.078
1857	0.93
1858	0.773
1859	1.071
1860	1.084
1861	1.076
1862	0.762
1863	0.485
1864	1.22
1865	0.888
1866	0.87
1867	0.825
1868	0.697
1869	0.941
1870	0.875
1871	0.733
1872	0.613
1873	0.782
1874	0.783
1875	0.813
1876	0.89
1877	0.877
1878	1.152
1879	0.962
1880	0.878
1881	1.112
1882	1.08
1883	1.07
1884	1.238
1885	1.444
1886	1.216
1887	1.048
1888	1.222
1889	1.283
1890	1.831
1891	1.59
1892	0.896
1893	1.326
1894	0.885
1895	0.952
1896	1.15
1897	0.88
1898	1.191
1899	1.087
1900	0.901
1901	1.047
1902	1.407
1903	0.736
1904	1.199
1905	1.355
1906	1.229
1907	1.425
1908	1.198
1909	1.384
1910	1.147
1911	1.115
1912	1.213
1913	1.006
1914	1.345
1915	1.26
1916	1.15
1917	1.247
1918	1.042
1919	0.997
1920	1.068
1921	1.254
1922	1.343
1923	1.161
1924	0.922
1925	1.348
1926	0.945
1927	1.02
1928	0.842
1929	0.902
1930	0.884
1931	0.784
1932	1.163
1933	1.06
1934	1.103
1935	1.124
1936	1.028
1937	1.223
1938	1.187
1939	1.178
1940	1.293
1941	1.122
1942	0.895
1943	1.245
1944	1.07
1945	1.091
1946	0.954
1947	0.915
1948	1.096
1949	1.103
1950	1.115
1951	1.228
1952	1.1
1953	0.923
1954	1.244
1955	1.118
1956	1.075
1957	1.34
1958	1.055
1959	0.925
1960	0.882
1961	0.818
1962	0.532
1963	0.483
1964	0.9
1965	0.82
1966	0.879
1967	0.801
1968	0.781
1969	0.46
1970	0.787
1971	0.728
1972	0.572
1973	0.711
1974	0.976
1975	0.788
1976	0.711
1977	0.63
1978	0.711
1979	0.538
1980	0.785
1981	1.1
1982	0.932
1983	0.896
1984	1.027
1985	0.791
1986	0.676
1987	0.671
1988	0.852
1989	0.873
1990	0.882