# asia_nepa013 - Chardung - 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/3770
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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_nepa013 - Chardung - 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: Chardung
#	Location:
#	Country: Nepal
#	Northernmost_Latitude: 27.17
#	Southernmost_Latitude: 27.17
#	Easternmost_Longitude: 86.42
#	Westernmost_Longitude: 86.42
#	Elevation: 3300 m
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# Data_Collection
#	Collection_Name: asia_nepa013B
#	Earliest_Year: 1800
#	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":"5.45616832948","T2":"17.7361398571","M1":"0.0225720308652","M2":"0.201668539344"}}
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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
1800	1.39
1801	1.001
1802	1.132
1803	1.144
1804	1.269
1805	0.882
1806	1.011
1807	0.961
1808	0.857
1809	0.851
1810	0.979
1811	0.947
1812	0.938
1813	0.67
1814	0.688
1815	0.794
1816	0.882
1817	0.745
1818	0.585
1819	0.618
1820	0.705
1821	0.905
1822	0.62
1823	0.737
1824	1.015
1825	1.026
1826	0.899
1827	1.136
1828	0.663
1829	0.577
1830	0.563
1831	0.661
1832	0.773
1833	0.718
1834	0.511
1835	0.38
1836	0.625
1837	0.989
1838	0.951
1839	0.896
1840	1.019
1841	0.923
1842	1.064
1843	0.922
1844	0.966
1845	1.039
1846	1.506
1847	1.167
1848	1.232
1849	0.931
1850	1.033
1851	0.986
1852	0.76
1853	0.805
1854	0.743
1855	0.879
1856	1.178
1857	1.238
1858	1.28
1859	0.993
1860	0.995
1861	1.272
1862	1.128
1863	1.115
1864	1.159
1865	1.25
1866	1.042
1867	1.079
1868	1.073
1869	1.031
1870	0.972
1871	1.253
1872	1.154
1873	1.188
1874	1.054
1875	1.349
1876	1.177
1877	1.015
1878	1.171
1879	0.965
1880	0.79
1881	0.937
1882	0.964
1883	0.985
1884	0.989
1885	1.066
1886	0.738
1887	0.48
1888	0.714
1889	1.199
1890	1.15
1891	1.174
1892	1.534
1893	1.272
1894	1.242
1895	0.789
1896	1.137
1897	1.33
1898	1.247
1899	1.197
1900	1.357
1901	1.244
1902	1.416
1903	1.34
1904	1.498
1905	1.26
1906	0.943
1907	0.723
1908	1.186
1909	0.938
1910	1.076
1911	1.109
1912	1.014
1913	0.929
1914	1.044
1915	0.948
1916	0.652
1917	0.866
1918	0.941
1919	0.992
1920	1.252
1921	1.41
1922	0.887
1923	0.681
1924	1.222
1925	1.0
1926	0.887
1927	0.948
1928	0.712
1929	0.425
1930	0.688
1931	1.24
1932	1.101
1933	1.095
1934	1.243
1935	1.103
1936	0.842
1937	0.882
1938	0.762
1939	0.659
1940	1.0
1941	0.927
1942	0.832
1943	0.956
1944	0.98
1945	1.141
1946	0.987
1947	0.901
1948	0.785
1949	0.672
1950	1.045
1951	1.42
1952	1.393
1953	0.956
1954	1.087
1955	0.906
1956	0.957
1957	1.001
1958	1.042
1959	0.859
1960	0.835
1961	0.77
1962	0.75
1963	1.074
1964	0.897
1965	0.404
1966	0.429
1967	0.484
1968	0.581
1969	0.967
1970	0.776
1971	0.469
1972	0.495
1973	0.7
1974	0.725
1975	0.376
1976	0.39
1977	1.006
1978	0.828
1979	0.965
1980	0.798
1981	0.61
1982	0.871
1983	1.095
1984	0.731
1985	0.794
1986	1.098
1987	1.361
1988	1.148
1989	1.173
1990	1.218
1991	1.472
1992	1.292
1993	1.272
1994	1.089
1995	1.001
1996	1.264
1997	1.089
1998	1.086