# asia_indi021 - Jageswar - 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/2792
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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_indi021 - Jageswar - 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
#--------------------
# 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: Jageswar
#	Location:
#	Country: India
#	Northernmost_Latitude: 29.77
#	Southernmost_Latitude: 29.77
#	Easternmost_Longitude: 79.17
#	Westernmost_Longitude: 79.17
#	Elevation: 2000 m
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# Data_Collection
#	Collection_Name: asia_indi021B
#	Earliest_Year: 1767
#	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":"4.56974770897","T2":"17.968052545","M1":"0.0223171464321","M2":"0.467452946436"}}
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# Species
#	Species_Name: deodar cedar
#	Species_Code: CDDE
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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
1767	0.835
1768	0.701
1769	0.983
1770	1.031
1771	1.052
1772	1.094
1773	1.342
1774	0.835
1775	1.322
1776	1.193
1777	0.815
1778	1.12
1779	0.724
1780	0.669
1781	0.739
1782	0.458
1783	0.708
1784	0.514
1785	0.692
1786	0.959
1787	0.82
1788	0.975
1789	0.884
1790	0.765
1791	1.054
1792	0.964
1793	0.914
1794	0.994
1795	0.79
1796	1.056
1797	0.778
1798	1.212
1799	1.164
1800	1.247
1801	1.089
1802	0.967
1803	1.011
1804	0.794
1805	0.737
1806	1.123
1807	0.995
1808	1.186
1809	0.646
1810	0.787
1811	0.943
1812	0.898
1813	0.593
1814	1.041
1815	0.955
1816	0.461
1817	0.923
1818	0.927
1819	0.95
1820	0.786
1821	0.71
1822	1.132
1823	0.807
1824	1.204
1825	1.304
1826	1.215
1827	1.32
1828	0.949
1829	1.159
1830	1.189
1831	0.91
1832	1.138
1833	0.911
1834	1.209
1835	1.16
1836	1.125
1837	0.845
1838	0.94
1839	1.175
1840	0.841
1841	1.057
1842	1.076
1843	0.921
1844	0.798
1845	1.088
1846	0.592
1847	0.694
1848	0.634
1849	0.746
1850	1.09
1851	0.905
1852	1.324
1853	1.105
1854	1.058
1855	0.971
1856	0.96
1857	0.849
1858	1.192
1859	1.604
1860	0.731
1861	1.292
1862	1.2
1863	1.152
1864	1.029
1865	1.206
1866	0.62
1867	0.911
1868	1.338
1869	0.587
1870	0.931
1871	1.012
1872	0.901
1873	0.574
1874	0.731
1875	0.894
1876	0.324
1877	0.709
1878	0.675
1879	0.286
1880	0.619
1881	0.722
1882	0.768
1883	0.704
1884	0.469
1885	0.735
1886	0.97
1887	0.597
1888	0.556
1889	0.808
1890	0.396
1891	0.841
1892	0.209
1893	1.146
1894	0.758
1895	1.072
1896	0.523
1897	0.567
1898	0.616
1899	0.625
1900	0.715
1901	0.512
1902	0.527
1903	0.49
1904	0.531
1905	0.719
1906	0.653
1907	0.733
1908	0.373
1909	0.57
1910	0.456
1911	0.592
1912	0.814
1913	1.004
1914	1.226
1915	1.081
1916	0.86
1917	1.019
1918	0.664
1919	0.823
1920	0.816
1921	0.282
1922	0.529
1923	0.565
1924	0.637
1925	0.892
1926	0.947
1927	1.133
1928	1.156
1929	0.627
1930	0.837
1931	0.345
1932	0.664
1933	1.343
1934	0.586
1935	0.554
1936	1.165
1937	1.207
1938	0.963
1939	0.798
1940	1.16
1941	0.603
1942	0.769
1943	0.789
1944	0.836
1945	0.605
1946	1.097
1947	0.586
1948	0.651
1949	1.303
1950	0.938
1951	0.886
1952	0.978
1953	0.689
1954	1.26
1955	1.133
1956	1.121
1957	1.549
1958	0.999
1959	1.419
1960	1.343
1961	1.36
1962	1.32
1963	1.501
1964	0.8
1965	0.921
1966	0.397
1967	0.476
1968	0.987
1969	0.963
1970	1.051
1971	1.603
1972	0.758
1973	1.337
1974	0.825
1975	1.364
1976	1.656
1977	1.793
1978	1.696
1979	2.213
1980	1.326
1981	1.574
1982	1.553
1983	1.584
1984	1.374
1985	0.857
1986	1.599
1987	1.543
1988	1.49
1989	0.84