# asia_nepa034 - Nehe Karka - 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/3791
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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_nepa034 - Nehe Karka - 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: Nehe Karka
#	Location:
#	Country: Nepal
#	Northernmost_Latitude: 27.42
#	Southernmost_Latitude: 27.42
#	Easternmost_Longitude: 87.1
#	Westernmost_Longitude: 87.1
#	Elevation: 3250 m
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# Data_Collection
#	Collection_Name: asia_nepa034B
#	Earliest_Year: 1787
#	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":"5.57385762033","T2":"21.3394804909","M1":"0.0221382123922","M2":"0.320451787636"}}
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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
1787	1.216
1788	1.054
1789	0.938
1790	0.654
1791	0.442
1792	0.537
1793	0.928
1794	0.913
1795	1.08
1796	1.273
1797	1.15
1798	1.331
1799	0.868
1800	1.067
1801	0.883
1802	0.968
1803	1.136
1804	1.061
1805	1.395
1806	1.373
1807	1.264
1808	1.313
1809	1.462
1810	1.557
1811	1.319
1812	0.779
1813	0.793
1814	0.882
1815	0.758
1816	0.84
1817	0.481
1818	0.265
1819	0.212
1820	0.434
1821	0.727
1822	0.785
1823	0.746
1824	0.864
1825	0.934
1826	1.106
1827	1.155
1828	0.932
1829	0.651
1830	0.743
1831	0.636
1832	0.693
1833	0.621
1834	0.556
1835	0.99
1836	1.203
1837	1.082
1838	0.92
1839	0.901
1840	1.06
1841	1.025
1842	0.942
1843	0.812
1844	0.858
1845	1.001
1846	1.04
1847	1.08
1848	1.34
1849	1.267
1850	1.29
1851	1.236
1852	1.242
1853	1.128
1854	0.813
1855	0.898
1856	0.831
1857	1.073
1858	1.037
1859	0.975
1860	1.116
1861	1.181
1862	1.098
1863	0.95
1864	0.79
1865	0.944
1866	0.681
1867	0.78
1868	0.813
1869	0.75
1870	0.756
1871	0.853
1872	0.645
1873	0.792
1874	0.878
1875	1.333
1876	1.436
1877	1.235
1878	1.258
1879	1.256
1880	1.182
1881	0.906
1882	0.975
1883	1.217
1884	1.03
1885	1.116
1886	1.058
1887	1.061
1888	1.289
1889	1.142
1890	1.103
1891	1.175
1892	0.773
1893	0.843
1894	1.132
1895	0.899
1896	0.864
1897	0.881
1898	0.798
1899	1.049
1900	1.016
1901	1.002
1902	1.007
1903	0.97
1904	0.933
1905	0.755
1906	0.73
1907	0.891
1908	1.288
1909	1.198
1910	1.238
1911	1.563
1912	1.161
1913	0.826
1914	0.791
1915	0.624
1916	0.719
1917	0.912
1918	0.86
1919	0.703
1920	0.77
1921	0.797
1922	0.828
1923	1.088
1924	1.349
1925	1.555
1926	1.398
1927	1.038
1928	1.096
1929	1.068
1930	1.172
1931	0.944
1932	0.77
1933	1.104
1934	1.198
1935	1.01
1936	1.076
1937	0.863
1938	0.953
1939	0.936
1940	1.357
1941	1.235
1942	1.131
1943	1.156
1944	1.018
1945	1.099
1946	0.942
1947	1.043
1948	1.054
1949	1.197
1950	1.255
1951	1.268
1952	1.285
1953	1.341
1954	0.913
1955	0.559
1956	0.778
1957	1.159
1958	1.148
1959	0.77
1960	0.976
1961	0.861
1962	0.461
1963	0.606
1964	0.619
1965	0.774
1966	0.738
1967	0.383
1968	0.323
1969	0.494
1970	0.663
1971	0.664
1972	0.524
1973	0.536
1974	0.69
1975	0.785
1976	0.8
1977	0.932
1978	0.428
1979	0.649
1980	0.652
1981	0.866
1982	0.789
1983	0.838
1984	0.665
1985	0.68
1986	0.707
1987	0.722
1988	0.607
1989	0.706
1990	1.015
1991	0.955
1992	1.002
1993	1.196
1994	1.206
1995	0.67
1996	0.762