# asia_nepa017 - Dobini Danda - 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/3774
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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_nepa017 - Dobini Danda - 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: Dobini Danda
#	Location:
#	Country: Nepal
#	Northernmost_Latitude: 27.43
#	Southernmost_Latitude: 27.43
#	Easternmost_Longitude: 86.2
#	Westernmost_Longitude: 86.2
#	Elevation: 3500 m
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# Data_Collection
#	Collection_Name: asia_nepa017B
#	Earliest_Year: 1810
#	Most_Recent_Year: 1998
#	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":"5.07658439836","T2":"16.1531141433","M1":"0.0224262120745","M2":"0.538943324756"}}
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# Species
#	Species_Name: silver fir
#	Species_Code: ABSB
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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
1810	0.92
1811	1.092
1812	0.815
1813	0.97
1814	0.938
1815	0.96
1816	1.123
1817	0.765
1818	0.717
1819	0.792
1820	0.906
1821	0.857
1822	0.81
1823	1.03
1824	1.128
1825	0.908
1826	0.903
1827	1.001
1828	0.785
1829	0.694
1830	0.803
1831	0.945
1832	0.946
1833	1.108
1834	0.785
1835	0.824
1836	0.926
1837	1.121
1838	0.928
1839	1.029
1840	1.027
1841	0.848
1842	0.801
1843	0.869
1844	1.056
1845	1.08
1846	1.239
1847	0.919
1848	1.088
1849	0.926
1850	0.991
1851	1.011
1852	0.852
1853	0.957
1854	0.913
1855	0.965
1856	1.122
1857	1.139
1858	1.064
1859	0.852
1860	1.07
1861	1.0
1862	1.071
1863	1.048
1864	0.896
1865	0.943
1866	0.997
1867	0.866
1868	0.906
1869	1.066
1870	0.866
1871	1.206
1872	0.997
1873	1.24
1874	0.957
1875	1.027
1876	0.997
1877	1.036
1878	1.231
1879	0.927
1880	0.95
1881	1.11
1882	1.237
1883	0.99
1884	0.864
1885	0.98
1886	0.784
1887	0.598
1888	0.752
1889	0.989
1890	1.04
1891	1.044
1892	1.101
1893	1.015
1894	1.122
1895	0.768
1896	0.934
1897	0.886
1898	0.642
1899	0.837
1900	1.075
1901	0.967
1902	0.975
1903	0.906
1904	0.962
1905	0.913
1906	0.791
1907	0.824
1908	1.288
1909	0.921
1910	1.1
1911	1.413
1912	1.433
1913	1.305
1914	1.352
1915	1.097
1916	0.878
1917	1.041
1918	1.011
1919	1.044
1920	1.082
1921	1.158
1922	1.154
1923	1.192
1924	1.489
1925	1.079
1926	0.961
1927	1.118
1928	0.966
1929	1.11
1930	1.307
1931	1.182
1932	0.866
1933	0.903
1934	1.014
1935	1.138
1936	1.15
1937	1.17
1938	0.96
1939	0.782
1940	0.947
1941	0.917
1942	0.94
1943	0.795
1944	1.137
1945	1.122
1946	1.092
1947	1.057
1948	0.832
1949	0.778
1950	0.864
1951	1.386
1952	1.171
1953	0.756
1954	0.688
1955	0.69
1956	0.773
1957	1.054
1958	1.126
1959	0.829
1960	0.867
1961	0.729
1962	0.731
1963	0.751
1964	0.766
1965	0.519
1966	0.678
1967	0.437
1968	0.404
1969	0.532
1970	0.653
1971	0.733
1972	0.887
1973	0.726
1974	0.863
1975	1.141
1976	1.009
1977	1.561
1978	0.782
1979	0.607
1980	0.792
1981	0.699
1982	0.964
1983	1.18
1984	0.89
1985	0.832
1986	1.028
1987	1.042
1988	1.24
1989	1.15
1990	1.009
1991	1.091
1992	1.291
1993	1.144
1994	0.866
1995	0.798
1996	1.047
1997	0.86
1998	0.877