# asia_indi007 - Thijwas A - 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/3578
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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_indi007 - Thijwas A - 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: Thijwas A
#	Location:
#	Country: India
#	Northernmost_Latitude: 34.65
#	Southernmost_Latitude: 34.65
#	Easternmost_Longitude: 75.47
#	Westernmost_Longitude: 75.47
#	Elevation: 3200 m
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# Data_Collection
#	Collection_Name: asia_indi007B
#	Earliest_Year: 1805
#	Most_Recent_Year: 1981
#	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":"2.45640434222","T2":"15.4754676721","M1":"0.0229017107851","M2":"0.496373137052"}}
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# Species
#	Species_Name: Himalayan silver fir
#	Species_Code: ABPI
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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
1805	0.908
1806	0.783
1807	0.966
1808	0.98
1809	0.996
1810	1.198
1811	1.051
1812	0.966
1813	1.107
1814	1.164
1815	1.095
1816	1.246
1817	0.934
1818	1.137
1819	1.118
1820	1.019
1821	0.733
1822	0.76
1823	0.678
1824	0.89
1825	0.806
1826	1.057
1827	0.78
1828	0.821
1829	0.91
1830	0.938
1831	0.844
1832	0.951
1833	0.737
1834	0.923
1835	0.747
1836	0.857
1837	0.813
1838	1.127
1839	1.069
1840	0.91
1841	0.81
1842	0.849
1843	0.826
1844	0.806
1845	0.648
1846	0.728
1847	0.635
1848	0.998
1849	1.015
1850	0.985
1851	1.015
1852	1.011
1853	1.092
1854	0.92
1855	0.957
1856	1.259
1857	1.539
1858	1.337
1859	1.207
1860	1.359
1861	1.015
1862	0.966
1863	1.034
1864	1.053
1865	1.042
1866	0.835
1867	0.933
1868	1.033
1869	1.027
1870	1.253
1871	1.201
1872	1.068
1873	1.146
1874	1.312
1875	1.262
1876	1.152
1877	0.993
1878	1.201
1879	1.017
1880	1.025
1881	0.965
1882	1.034
1883	0.874
1884	0.963
1885	0.672
1886	0.952
1887	0.908
1888	0.91
1889	1.041
1890	0.938
1891	1.085
1892	1.083
1893	1.292
1894	1.578
1895	1.015
1896	1.06
1897	0.755
1898	0.899
1899	0.727
1900	1.014
1901	1.081
1902	0.938
1903	1.108
1904	1.151
1905	0.837
1906	0.75
1907	0.875
1908	1.101
1909	1.0
1910	1.023
1911	0.732
1912	0.739
1913	0.887
1914	0.913
1915	0.647
1916	0.637
1917	0.66
1918	0.571
1919	0.821
1920	0.751
1921	1.319
1922	1.393
1923	1.153
1924	1.131
1925	0.839
1926	0.82
1927	0.828
1928	0.996
1929	1.185
1930	1.293
1931	1.236
1932	1.321
1933	1.286
1934	0.975
1935	1.033
1936	1.113
1937	0.792
1938	0.96
1939	0.969
1940	0.932
1941	0.904
1942	1.061
1943	1.072
1944	1.093
1945	1.325
1946	1.167
1947	1.054
1948	1.375
1949	1.34
1950	0.948
1951	1.204
1952	1.151
1953	1.048
1954	0.806
1955	0.642
1956	0.91
1957	0.697
1958	0.785
1959	0.814
1960	0.938
1961	1.047
1962	0.716
1963	0.757
1964	0.703
1965	0.766
1966	0.804
1967	0.734
1968	0.645
1969	0.937
1970	0.912
1971	0.865
1972	0.948
1973	1.093
1974	0.9
1975	0.797
1976	0.913
1977	0.88
1978	0.975
1979	0.865
1980	1.193
1981	1.239