# asia_nepa016 - Deorali La - 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/3773
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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_nepa016 - Deorali La - 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: Deorali La
#	Location:
#	Country: Nepal
#	Northernmost_Latitude: 28.23
#	Southernmost_Latitude: 28.23
#	Easternmost_Longitude: 83.42
#	Westernmost_Longitude: 83.42
#	Elevation: 1830 m
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# Data_Collection
#	Collection_Name: asia_nepa016B
#	Earliest_Year: 1778
#	Most_Recent_Year: 1997
#	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":"4.25056254236","T2":"16.1164887853","M1":"0.0226770295633","M2":"0.538198931633"}}
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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
1778	1.091
1779	0.857
1780	0.915
1781	1.048
1782	1.002
1783	0.69
1784	0.908
1785	1.222
1786	1.117
1787	0.903
1788	1.034
1789	0.831
1790	0.659
1791	0.669
1792	0.747
1793	0.901
1794	0.962
1795	1.115
1796	1.435
1797	1.464
1798	1.192
1799	1.033
1800	1.198
1801	1.017
1802	0.593
1803	1.037
1804	1.217
1805	0.964
1806	1.014
1807	0.704
1808	0.933
1809	0.929
1810	1.272
1811	0.885
1812	0.786
1813	0.961
1814	0.82
1815	0.443
1816	0.728
1817	0.494
1818	0.555
1819	0.582
1820	0.666
1821	0.911
1822	0.857
1823	0.951
1824	0.858
1825	0.763
1826	1.019
1827	1.237
1828	0.918
1829	0.909
1830	0.924
1831	0.96
1832	0.877
1833	0.791
1834	0.652
1835	0.564
1836	0.564
1837	0.665
1838	0.432
1839	0.677
1840	1.06
1841	0.942
1842	0.985
1843	0.873
1844	0.988
1845	1.223
1846	1.516
1847	0.994
1848	1.138
1849	0.878
1850	0.994
1851	1.051
1852	1.281
1853	1.638
1854	1.312
1855	1.306
1856	1.257
1857	0.846
1858	1.051
1859	1.142
1860	1.143
1861	0.809
1862	0.949
1863	0.979
1864	0.908
1865	1.101
1866	1.008
1867	0.883
1868	0.983
1869	0.967
1870	0.9
1871	1.076
1872	1.046
1873	0.912
1874	0.562
1875	0.856
1876	1.019
1877	0.915
1878	1.308
1879	1.056
1880	0.844
1881	1.146
1882	1.267
1883	1.108
1884	0.781
1885	0.8
1886	1.063
1887	1.137
1888	1.36
1889	1.172
1890	0.896
1891	1.034
1892	0.853
1893	0.514
1894	0.969
1895	0.95
1896	0.961
1897	1.075
1898	0.782
1899	0.929
1900	1.113
1901	0.615
1902	0.74
1903	1.208
1904	1.106
1905	0.67
1906	0.878
1907	1.005
1908	1.257
1909	1.094
1910	1.091
1911	1.23
1912	1.224
1913	1.235
1914	1.366
1915	1.34
1916	1.162
1917	1.135
1918	1.098
1919	1.192
1920	1.183
1921	0.94
1922	0.755
1923	0.877
1924	1.425
1925	1.04
1926	1.098
1927	1.06
1928	0.865
1929	1.14
1930	1.344
1931	1.042
1932	0.651
1933	0.966
1934	1.503
1935	0.998
1936	0.814
1937	0.885
1938	0.811
1939	0.739
1940	0.762
1941	0.919
1942	1.126
1943	1.153
1944	0.566
1945	0.639
1946	0.731
1947	0.88
1948	0.88
1949	0.942
1950	1.035
1951	1.378
1952	1.196
1953	0.89
1954	1.008
1955	1.062
1956	1.016
1957	1.305
1958	1.214
1959	0.827
1960	0.586
1961	0.775
1962	0.732
1963	0.935
1964	0.927
1965	0.568
1966	0.888
1967	0.691
1968	0.374
1969	0.806
1970	0.71
1971	0.766
1972	1.121
1973	1.062
1974	0.784
1975	0.513
1976	0.878
1977	1.179
1978	0.918
1979	1.168
1980	0.989
1981	0.618
1982	0.838
1983	1.037
1984	0.919
1985	0.863
1986	1.126
1987	1.231
1988	1.0
1989	0.646
1990	0.776
1991	0.919
1992	0.889
1993	0.561
1994	0.597
1995	0.718
1996	1.033
1997	0.891