# asia_indi016 - Narkhanda - Breitenmoser Tree Ring Chronology Data
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#		World Data Center for Paleoclimatology, Boulder
#				and
#		NOAA Paleoclimatology Program
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# 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/2798
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# Description/Documentation lines begin with #
# Data lines have no #
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# Archive: Tree Rings
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# Contribution_Date
#	Date: 2016-01-07
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# Title
#	Study_Name: asia_indi016 - Narkhanda - Breitenmoser Tree Ring Chronology Data
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# Investigators
#	Investigators:  Breitenmoser, P.; Bronnimann, S.; Frank, D.
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# Description_and_Notes
#	Description: Data from Breitenmoser 2014 Journal of past Climate supplementary, see publication for ARSTAN standardization details
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# 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.
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#	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:
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#	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: Narkhanda
#	Location:
#	Country: India
#	Northernmost_Latitude: 31.2
#	Southernmost_Latitude: 31.2
#	Easternmost_Longitude: 77.23
#	Westernmost_Longitude: 77.23
#	Elevation: 3000 m
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# Data_Collection
#	Collection_Name: asia_indi016B
#	Earliest_Year: 1783
#	Most_Recent_Year: 1989
#	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":"3.86878395344","T2":"13.9892495714","M1":"0.0226272444656","M2":"0.321025162401"}}
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# Species
#	Species_Name: Himalayan spruce
#	Species_Code: PCSM
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# Chronology:
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# Variables
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# 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)
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##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
1783	1.066
1784	1.074
1785	1.06
1786	1.122
1787	1.242
1788	1.127
1789	1.205
1790	0.867
1791	1.279
1792	1.105
1793	0.947
1794	1.015
1795	0.729
1796	0.71
1797	0.648
1798	1.105
1799	1.034
1800	0.785
1801	0.723
1802	0.892
1803	0.995
1804	0.899
1805	1.021
1806	1.047
1807	1.075
1808	1.116
1809	1.05
1810	1.025
1811	0.779
1812	0.707
1813	0.775
1814	0.871
1815	0.941
1816	0.457
1817	0.756
1818	0.916
1819	1.005
1820	0.973
1821	0.939
1822	1.132
1823	1.061
1824	1.066
1825	1.239
1826	1.219
1827	1.411
1828	1.282
1829	1.285
1830	1.174
1831	1.209
1832	1.107
1833	1.108
1834	1.004
1835	1.114
1836	1.148
1837	1.005
1838	1.04
1839	0.988
1840	1.126
1841	1.15
1842	1.083
1843	1.157
1844	1.337
1845	1.133
1846	1.337
1847	1.151
1848	1.099
1849	0.803
1850	0.748
1851	0.96
1852	1.104
1853	1.042
1854	1.062
1855	1.217
1856	1.007
1857	0.774
1858	0.878
1859	0.933
1860	0.948
1861	0.887
1862	0.947
1863	0.875
1864	0.872
1865	0.926
1866	1.165
1867	0.915
1868	0.924
1869	1.027
1870	0.807
1871	0.729
1872	0.836
1873	0.864
1874	0.591
1875	0.848
1876	0.548
1877	0.61
1878	0.822
1879	0.968
1880	0.641
1881	0.782
1882	1.08
1883	1.049
1884	1.064
1885	0.962
1886	0.632
1887	0.829
1888	0.538
1889	0.674
1890	0.887
1891	0.884
1892	0.483
1893	0.801
1894	0.854
1895	0.983
1896	0.973
1897	1.033
1898	0.825
1899	0.803
1900	0.807
1901	0.909
1902	0.879
1903	0.954
1904	0.888
1905	0.96
1906	0.965
1907	0.877
1908	0.559
1909	0.72
1910	0.662
1911	0.804
1912	0.918
1913	1.096
1914	1.284
1915	1.232
1916	1.05
1917	1.228
1918	1.313
1919	1.241
1920	1.028
1921	0.423
1922	0.661
1923	0.519
1924	0.7
1925	1.007
1926	0.917
1927	0.619
1928	0.836
1929	0.545
1930	0.752
1931	0.915
1932	0.587
1933	0.737
1934	0.732
1935	0.736
1936	0.859
1937	0.94
1938	1.0
1939	1.014
1940	0.857
1941	0.475
1942	0.624
1943	0.73
1944	1.036
1945	1.054
1946	1.111
1947	0.864
1948	0.992
1949	0.768
1950	0.997
1951	0.975
1952	0.943
1953	0.728
1954	0.681
1955	0.763
1956	0.802
1957	0.714
1958	1.157
1959	1.2
1960	1.303
1961	1.468
1962	1.533
1963	1.383
1964	1.619
1965	1.402
1966	1.067
1967	1.168
1968	0.892
1969	1.181
1970	0.946
1971	1.091
1972	1.232
1973	1.152
1974	1.112
1975	1.123
1976	1.07
1977	0.924
1978	1.174
1979	0.971
1980	1.089
1981	1.142
1982	1.081
1983	0.875
1984	0.939
1985	0.446
1986	1.17
1987	1.33
1988	1.405
1989	1.755