# asia_nepa006 - Bagarchap - 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/3760
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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_nepa006 - Bagarchap - Breitenmoser Tree Ring Chronology Data
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# Investigators
#	Investigators:  Breitenmoser, P.; Bronnimann, S.; Frank, D.
#--------------------
# 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:
#--------------------
#	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: Bagarchap
#	Location:
#	Country: Nepal
#	Northernmost_Latitude: 28.3
#	Southernmost_Latitude: 28.3
#	Easternmost_Longitude: 84.18
#	Westernmost_Longitude: 84.18
#	Elevation: 2270 m
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# Data_Collection
#	Collection_Name: asia_nepa006B
#	Earliest_Year: 1840
#	Most_Recent_Year: 1994
#	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":"6.91270968902","T2":"19.9742925843","M1":"0.0220831725582","M2":"0.304660040739"}}
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# Species
#	Species_Name: cottonwood
#	Species_Code: PPSP
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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
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age	trsgi
1840	0.886
1841	0.659
1842	0.728
1843	0.94
1844	1.242
1845	1.151
1846	0.948
1847	1.009
1848	1.112
1849	1.151
1850	1.108
1851	0.834
1852	1.007
1853	1.499
1854	0.835
1855	1.021
1856	0.84
1857	0.972
1858	0.931
1859	1.042
1860	0.994
1861	0.914
1862	1.146
1863	0.865
1864	0.84
1865	1.025
1866	1.088
1867	0.959
1868	1.017
1869	1.071
1870	1.059
1871	0.768
1872	1.164
1873	1.246
1874	1.198
1875	1.254
1876	0.957
1877	1.083
1878	1.085
1879	1.084
1880	0.769
1881	1.033
1882	0.979
1883	1.059
1884	0.655
1885	0.554
1886	0.711
1887	0.757
1888	1.171
1889	0.969
1890	0.702
1891	0.457
1892	0.63
1893	0.638
1894	0.538
1895	0.599
1896	1.209
1897	1.082
1898	1.114
1899	0.503
1900	0.961
1901	1.065
1902	0.852
1903	1.229
1904	0.425
1905	0.641
1906	0.906
1907	0.488
1908	1.004
1909	0.894
1910	0.893
1911	0.604
1912	0.836
1913	1.137
1914	1.447
1915	0.985
1916	0.644
1917	0.428
1918	0.447
1919	0.615
1920	0.95
1921	1.057
1922	1.267
1923	1.428
1924	1.47
1925	1.01
1926	1.12
1927	1.233
1928	1.34
1929	1.23
1930	1.384
1931	1.759
1932	1.619
1933	0.79
1934	1.18
1935	1.178
1936	1.237
1937	1.235
1938	1.125
1939	1.079
1940	1.056
1941	0.756
1942	1.253
1943	0.751
1944	0.947
1945	0.747
1946	0.656
1947	0.862
1948	0.665
1949	0.693
1950	0.793
1951	0.786
1952	0.79
1953	1.291
1954	0.941
1955	0.878
1956	0.542
1957	1.175
1958	1.012
1959	0.865
1960	0.915
1961	1.254
1962	1.01
1963	0.747
1964	1.021
1965	0.968
1966	0.967
1967	0.78
1968	1.011
1969	1.173
1970	0.819
1971	0.488
1972	0.97
1973	1.122
1974	1.487
1975	1.096
1976	0.594
1977	0.805
1978	0.798
1979	1.317
1980	1.036
1981	0.738
1982	0.805
1983	1.11
1984	1.099
1985	1.138
1986	0.853
1987	1.106
1988	0.92
1989	0.752
1990	0.669
1991	0.782
1992	1.597
1993	1.193
1994	1.585