# asia_nepa039 - Banal-Salme - 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/3762
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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_nepa039 - Banal-Salme - 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: Banal-Salme
#	Location:
#	Country: Nepal
#	Northernmost_Latitude: 28.03
#	Southernmost_Latitude: 28.03
#	Easternmost_Longitude: 85.07
#	Westernmost_Longitude: 85.07
#	Elevation: 3115 m
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# Data_Collection
#	Collection_Name: asia_nepa039B
#	Earliest_Year: 1771
#	Most_Recent_Year: 1996
#	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":"6.20649928015","T2":"17.4796996594","M1":"0.0221355760328","M2":"0.397088873365"}}
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# Species
#	Species_Name: East Himalayan hemlock
#	Species_Code: TSDU
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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
1771	0.979
1772	0.856
1773	0.969
1774	0.899
1775	0.764
1776	0.737
1777	0.727
1778	0.557
1779	0.668
1780	0.528
1781	0.521
1782	0.757
1783	0.92
1784	1.125
1785	0.951
1786	1.059
1787	0.453
1788	0.754
1789	0.907
1790	1.064
1791	0.811
1792	1.168
1793	0.989
1794	1.137
1795	1.073
1796	1.039
1797	0.966
1798	1.071
1799	1.001
1800	0.84
1801	0.911
1802	1.331
1803	1.276
1804	1.139
1805	1.029
1806	1.217
1807	0.996
1808	0.962
1809	0.851
1810	1.168
1811	0.896
1812	0.739
1813	0.992
1814	0.702
1815	0.395
1816	0.84
1817	0.71
1818	0.841
1819	0.717
1820	0.718
1821	0.94
1822	0.84
1823	0.992
1824	1.044
1825	0.652
1826	0.998
1827	1.244
1828	0.797
1829	0.672
1830	1.229
1831	1.324
1832	1.298
1833	1.395
1834	0.748
1835	0.734
1836	0.714
1837	0.873
1838	0.486
1839	0.482
1840	0.916
1841	1.091
1842	0.977
1843	0.943
1844	1.057
1845	1.183
1846	0.96
1847	0.714
1848	1.064
1849	0.943
1850	0.94
1851	1.23
1852	1.306
1853	1.407
1854	0.785
1855	0.768
1856	1.098
1857	1.636
1858	1.057
1859	1.134
1860	1.33
1861	0.908
1862	1.04
1863	1.065
1864	0.842
1865	0.969
1866	0.51
1867	0.389
1868	0.699
1869	0.732
1870	0.578
1871	0.842
1872	1.166
1873	1.183
1874	0.609
1875	0.386
1876	0.998
1877	1.317
1878	1.622
1879	0.829
1880	0.882
1881	1.662
1882	1.27
1883	1.272
1884	1.266
1885	1.182
1886	0.964
1887	0.647
1888	0.712
1889	0.829
1890	0.214
1891	0.521
1892	0.67
1893	0.971
1894	1.782
1895	1.069
1896	0.645
1897	0.224
1898	0.397
1899	0.805
1900	1.361
1901	0.706
1902	0.851
1903	1.128
1904	0.902
1905	0.677
1906	0.735
1907	0.61
1908	1.127
1909	0.648
1910	0.398
1911	0.484
1912	0.735
1913	0.842
1914	1.054
1915	0.77
1916	0.502
1917	0.758
1918	1.444
1919	1.382
1920	0.912
1921	0.741
1922	0.922
1923	0.702
1924	1.159
1925	1.103
1926	1.193
1927	1.055
1928	0.961
1929	0.92
1930	1.077
1931	1.278
1932	0.798
1933	0.792
1934	1.128
1935	1.187
1936	1.316
1937	1.368
1938	0.864
1939	0.801
1940	1.155
1941	1.134
1942	1.234
1943	0.884
1944	0.899
1945	0.919
1946	0.811
1947	0.976
1948	1.049
1949	1.134
1950	1.335
1951	1.328
1952	1.142
1953	0.631
1954	0.817
1955	0.764
1956	0.815
1957	1.217
1958	0.897
1959	0.826
1960	1.064
1961	0.881
1962	0.873
1963	1.04
1964	1.125
1965	0.676
1966	0.74
1967	0.554
1968	0.427
1969	0.654
1970	0.483
1971	0.557
1972	1.187
1973	0.878
1974	0.602
1975	0.908
1976	1.266
1977	1.337
1978	0.985
1979	0.859
1980	1.299
1981	1.563
1982	1.917
1983	1.751
1984	1.193
1985	1.413
1986	1.313
1987	1.271
1988	1.189
1989	1.197
1990	1.319
1991	0.899
1992	0.985
1993	1.111
1994	1.155
1995	0.748
1996	1.144