# asia_nepa022 - Kalingchok - 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/3779
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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_nepa022 - Kalingchok - 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: Kalingchok
#	Location:
#	Country: Nepal
#	Northernmost_Latitude: 27.45
#	Southernmost_Latitude: 27.45
#	Easternmost_Longitude: 86.05
#	Westernmost_Longitude: 86.05
#	Elevation: 3720 m
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# Data_Collection
#	Collection_Name: asia_nepa022B
#	Earliest_Year: 1754
#	Most_Recent_Year: 1978
#	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":"4.9553450246","T2":"15.0309933134","M1":"0.0224358061068","M2":"0.43668645248"}}
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# Species
#	Species_Name: silver fir
#	Species_Code: ABSB
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# Chronology:
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# Variables
#
# 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
1754	0.699
1755	0.623
1756	0.69
1757	0.689
1758	0.849
1759	1.037
1760	0.844
1761	0.763
1762	0.769
1763	0.901
1764	1.049
1765	1.055
1766	1.071
1767	0.986
1768	0.942
1769	0.936
1770	0.817
1771	0.911
1772	0.898
1773	0.959
1774	0.967
1775	0.894
1776	0.836
1777	0.905
1778	0.946
1779	0.884
1780	0.88
1781	0.848
1782	0.792
1783	0.783
1784	0.949
1785	0.89
1786	0.976
1787	0.919
1788	0.839
1789	0.908
1790	0.776
1791	0.71
1792	0.751
1793	0.929
1794	1.326
1795	1.252
1796	1.391
1797	1.371
1798	1.364
1799	1.075
1800	1.177
1801	1.147
1802	1.126
1803	1.209
1804	0.978
1805	0.923
1806	1.004
1807	0.908
1808	0.921
1809	0.995
1810	0.985
1811	0.79
1812	0.603
1813	0.515
1814	0.776
1815	0.634
1816	0.681
1817	0.577
1818	0.594
1819	0.559
1820	0.626
1821	0.754
1822	0.692
1823	0.842
1824	1.174
1825	1.308
1826	1.282
1827	1.361
1828	1.057
1829	0.774
1830	0.619
1831	0.652
1832	0.669
1833	0.906
1834	0.826
1835	0.945
1836	0.966
1837	0.909
1838	0.861
1839	0.868
1840	0.941
1841	0.864
1842	0.841
1843	0.822
1844	0.844
1845	0.892
1846	1.059
1847	1.2
1848	1.115
1849	1.058
1850	1.286
1851	1.38
1852	1.068
1853	1.207
1854	1.262
1855	1.247
1856	1.317
1857	1.518
1858	1.452
1859	1.155
1860	1.159
1861	1.336
1862	1.029
1863	1.144
1864	1.04
1865	1.15
1866	1.158
1867	1.025
1868	0.709
1869	0.769
1870	0.841
1871	1.118
1872	1.114
1873	1.191
1874	1.052
1875	0.905
1876	0.958
1877	0.859
1878	0.991
1879	0.849
1880	0.88
1881	1.074
1882	0.89
1883	0.962
1884	1.106
1885	1.17
1886	0.995
1887	0.761
1888	0.892
1889	1.196
1890	1.086
1891	1.209
1892	1.464
1893	1.127
1894	1.104
1895	0.857
1896	1.078
1897	1.146
1898	1.028
1899	1.064
1900	1.197
1901	0.869
1902	0.881
1903	0.766
1904	1.026
1905	0.561
1906	0.32
1907	0.475
1908	0.886
1909	0.914
1910	0.953
1911	1.001
1912	0.863
1913	0.886
1914	1.114
1915	0.81
1916	0.841
1917	1.076
1918	1.097
1919	1.131
1920	1.443
1921	1.387
1922	1.11
1923	0.97
1924	1.346
1925	1.192
1926	0.847
1927	0.895
1928	0.908
1929	0.982
1930	1.203
1931	1.62
1932	1.19
1933	1.147
1934	1.238
1935	1.198
1936	1.023
1937	1.016
1938	0.924
1939	0.814
1940	1.038
1941	1.239
1942	1.167
1943	0.902
1944	0.744
1945	0.679
1946	0.687
1947	0.905
1948	0.808
1949	0.697
1950	0.785
1951	0.986
1952	0.878
1953	0.557
1954	0.629
1955	0.746
1956	0.739
1957	1.027
1958	1.211
1959	0.913
1960	0.867
1961	0.802
1962	0.882
1963	0.872
1964	0.884
1965	0.744
1966	1.007
1967	0.876
1968	0.544
1969	0.583
1970	0.602
1971	0.619
1972	0.438
1973	0.524
1974	0.61
1975	0.797
1976	0.697
1977	0.982
1978	0.721