# asia_russ118w - Iremel Mountain - 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/4440
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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_russ118w - Iremel Mountain - 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: Iremel Mountain
#	Location:
#	Country: Russia
#	Northernmost_Latitude: 54.88
#	Southernmost_Latitude: 54.88
#	Easternmost_Longitude: 58.88
#	Westernmost_Longitude: 58.88
#	Elevation: 990 m
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# Data_Collection
#	Collection_Name: asia_russ118wB
#	Earliest_Year: 1703
#	Most_Recent_Year: 1993
#	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":"5.50281795477","T2":"19.6199980886","M1":"0.0227986220756","M2":"0.29035371128"}}
#--------------------
# 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
1703	0.797
1704	1.087
1705	1.207
1706	1.04
1707	1.272
1708	1.339
1709	1.34
1710	1.129
1711	1.302
1712	1.198
1713	1.208
1714	1.075
1715	0.766
1716	1.125
1717	0.921
1718	0.729
1719	0.704
1720	0.717
1721	0.717
1722	0.685
1723	0.757
1724	0.73
1725	0.805
1726	0.86
1727	0.81
1728	1.207
1729	1.079
1730	1.0
1731	1.088
1732	1.081
1733	0.871
1734	1.093
1735	0.869
1736	0.53
1737	0.575
1738	0.652
1739	0.816
1740	0.763
1741	0.623
1742	0.776
1743	0.656
1744	0.671
1745	0.723
1746	0.849
1747	0.835
1748	1.017
1749	0.833
1750	0.953
1751	0.82
1752	0.922
1753	0.966
1754	1.286
1755	0.851
1756	0.855
1757	1.141
1758	1.297
1759	1.195
1760	1.354
1761	1.324
1762	1.179
1763	1.218
1764	0.94
1765	1.166
1766	1.101
1767	1.262
1768	1.21
1769	0.659
1770	1.247
1771	1.281
1772	1.065
1773	0.91
1774	1.098
1775	1.028
1776	0.942
1777	1.069
1778	0.975
1779	0.948
1780	1.066
1781	1.119
1782	1.218
1783	1.121
1784	1.17
1785	0.918
1786	0.969
1787	0.968
1788	1.166
1789	1.143
1790	1.069
1791	1.183
1792	1.119
1793	1.179
1794	1.279
1795	1.065
1796	1.273
1797	1.139
1798	1.039
1799	1.2
1800	1.324
1801	1.253
1802	0.786
1803	0.951
1804	0.806
1805	0.979
1806	1.003
1807	0.952
1808	1.366
1809	1.284
1810	1.243
1811	1.12
1812	0.983
1813	0.961
1814	0.931
1815	1.013
1816	0.877
1817	0.926
1818	0.726
1819	0.927
1820	1.178
1821	1.29
1822	1.177
1823	1.209
1824	1.268
1825	1.144
1826	1.115
1827	1.148
1828	1.066
1829	1.009
1830	1.045
1831	1.042
1832	1.095
1833	1.007
1834	1.035
1835	0.888
1836	0.936
1837	0.994
1838	0.808
1839	0.949
1840	0.825
1841	0.81
1842	0.979
1843	0.83
1844	0.862
1845	0.748
1846	0.729
1847	0.893
1848	0.707
1849	0.698
1850	0.816
1851	0.598
1852	0.731
1853	0.75
1854	0.753
1855	0.785
1856	0.91
1857	0.841
1858	0.598
1859	0.653
1860	0.762
1861	0.569
1862	0.719
1863	0.637
1864	0.682
1865	0.46
1866	0.526
1867	0.708
1868	0.752
1869	0.487
1870	0.567
1871	0.722
1872	0.642
1873	0.648
1874	0.647
1875	0.67
1876	0.653
1877	0.774
1878	0.777
1879	0.64
1880	0.746
1881	0.545
1882	0.541
1883	0.527
1884	0.724
1885	0.479
1886	0.569
1887	0.488
1888	0.609
1889	0.749
1890	0.75
1891	0.743
1892	0.711
1893	0.79
1894	0.772
1895	0.818
1896	0.907
1897	0.882
1898	0.912
1899	0.87
1900	0.896
1901	0.972
1902	1.177
1903	1.048
1904	0.84
1905	0.914
1906	1.04
1907	1.303
1908	0.979
1909	1.165
1910	1.342
1911	1.01
1912	1.008
1913	1.078
1914	1.034
1915	1.093
1916	1.029
1917	1.305
1918	1.217
1919	1.005
1920	0.995
1921	0.681
1922	0.839
1923	0.762
1924	0.794
1925	0.963
1926	0.886
1927	0.925
1928	1.241
1929	1.075
1930	1.254
1931	1.415
1932	1.416
1933	1.309
1934	1.464
1935	1.569
1936	1.463
1937	1.442
1938	1.476
1939	1.649
1940	1.659
1941	1.367
1942	0.793
1943	1.409
1944	1.251
1945	1.048
1946	0.919
1947	1.029
1948	1.047
1949	1.286
1950	1.124
1951	1.403
1952	0.977
1953	1.131
1954	1.344
1955	1.13
1956	1.281
1957	1.244
1958	1.536
1959	1.136
1960	1.354
1961	1.145
1962	1.165
1963	1.161
1964	1.154
1965	1.273
1966	1.246
1967	1.066
1968	1.179
1969	0.905
1970	0.952
1971	1.096
1972	1.005
1973	0.981
1974	1.159
1975	0.827
1976	0.745
1977	0.666
1978	0.878
1979	0.806
1980	1.015
1981	1.05
1982	1.065
1983	1.037
1984	1.054
1985	0.885
1986	0.715
1987	0.912
1988	1.069
1989	0.844
1990	0.948
1991	0.75
1992	0.894
1993	0.948