# asia_nepa031 - Marsyangdi Khola - Breitenmoser Tree Ring Chronology Data
#-----------------------------------------------------------------------
#		World Data Center for Paleoclimatology, Boulder
#				and
#		NOAA Paleoclimatology Program
#-----------------------------------------------------------------------
# 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/3788
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# Description/Documentation lines begin with #
# Data lines have no #
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# Archive: Tree Rings
#--------------------
# Contribution_Date
#	Date: 2016-01-07
#--------------------
# Title
#	Study_Name: asia_nepa031 - Marsyangdi Khola - Breitenmoser Tree Ring Chronology Data
#--------------------
# 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.
#--------------------
#	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: Marsyangdi Khola
#	Location:
#	Country: Nepal
#	Northernmost_Latitude: 28.35
#	Southernmost_Latitude: 28.35
#	Easternmost_Longitude: 84.15
#	Westernmost_Longitude: 84.15
#	Elevation: 2900 m
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# Data_Collection
#	Collection_Name: asia_nepa031B
#	Earliest_Year: 1659
#	Most_Recent_Year: 1979
#	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":"4.26945392559","T2":"15.2227131413","M1":"0.0229934813899","M2":"0.61295652471"}}
#--------------------
# Species
#	Species_Name: silver fir
#	Species_Code: ABSB
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# Chronology:
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#
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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)
#
##age	age, , ,years AD, , , , ,N
##trsgi	tree ring standardized growth index, tree ring, ,percent relative to mean growth, , Tree Rings, , ,N
#
#--------------------
# Data:
# Data lines follow (have no #)
# Data line format - tab-delimited text, variable short name as header
# Missing Values: nan
#
age	trsgi
1659	0.913
1660	0.758
1661	0.51
1662	0.753
1663	0.769
1664	0.95
1665	0.677
1666	0.955
1667	0.839
1668	0.786
1669	0.867
1670	0.864
1671	0.853
1672	0.759
1673	0.815
1674	0.865
1675	0.784
1676	0.633
1677	0.577
1678	0.729
1679	0.718
1680	0.909
1681	0.809
1682	0.901
1683	0.917
1684	0.791
1685	0.888
1686	0.923
1687	0.867
1688	0.884
1689	0.885
1690	0.858
1691	0.778
1692	0.833
1693	0.762
1694	0.736
1695	0.641
1696	0.881
1697	0.996
1698	0.956
1699	1.189
1700	0.897
1701	1.058
1702	1.218
1703	1.195
1704	1.222
1705	1.031
1706	0.952
1707	0.763
1708	1.117
1709	1.185
1710	1.187
1711	1.233
1712	1.24
1713	1.073
1714	0.934
1715	0.708
1716	0.941
1717	0.594
1718	0.854
1719	0.966
1720	1.022
1721	1.174
1722	1.112
1723	1.059
1724	0.873
1725	1.214
1726	0.874
1727	1.118
1728	1.291
1729	1.236
1730	1.244
1731	1.212
1732	1.06
1733	0.93
1734	1.211
1735	0.975
1736	1.398
1737	1.175
1738	0.963
1739	1.174
1740	0.87
1741	0.705
1742	1.021
1743	0.91
1744	1.016
1745	1.074
1746	1.357
1747	0.875
1748	1.242
1749	0.698
1750	0.859
1751	1.394
1752	1.137
1753	1.038
1754	0.995
1755	0.993
1756	0.937
1757	0.758
1758	0.847
1759	0.828
1760	0.913
1761	0.951
1762	0.883
1763	0.785
1764	0.78
1765	1.036
1766	0.759
1767	0.864
1768	1.03
1769	0.929
1770	1.133
1771	1.089
1772	0.947
1773	1.227
1774	0.783
1775	0.881
1776	1.026
1777	1.171
1778	0.905
1779	1.047
1780	0.954
1781	0.961
1782	0.803
1783	0.806
1784	0.737
1785	0.911
1786	1.0
1787	1.12
1788	0.922
1789	0.846
1790	0.844
1791	0.88
1792	0.87
1793	0.679
1794	0.759
1795	0.776
1796	0.954
1797	0.854
1798	1.076
1799	0.859
1800	0.835
1801	0.651
1802	0.728
1803	0.899
1804	0.914
1805	0.828
1806	1.132
1807	1.041
1808	1.245
1809	1.189
1810	1.054
1811	1.181
1812	1.134
1813	0.811
1814	0.784
1815	1.115
1816	1.158
1817	1.231
1818	1.144
1819	1.38
1820	1.389
1821	0.858
1822	1.152
1823	1.156
1824	1.306
1825	1.364
1826	1.086
1827	1.257
1828	1.063
1829	1.215
1830	1.152
1831	1.2
1832	1.278
1833	1.126
1834	1.035
1835	1.141
1836	1.302
1837	1.252
1838	0.826
1839	0.937
1840	1.103
1841	1.092
1842	1.006
1843	1.153
1844	0.998
1845	0.992
1846	1.121
1847	1.067
1848	1.278
1849	0.954
1850	1.202
1851	1.196
1852	1.283
1853	1.078
1854	1.108
1855	1.199
1856	0.968
1857	0.803
1858	0.652
1859	0.652
1860	0.614
1861	0.907
1862	1.031
1863	1.053
1864	1.162
1865	1.188
1866	0.875
1867	1.161
1868	0.86
1869	0.758
1870	0.862
1871	0.929
1872	1.173
1873	1.339
1874	0.932
1875	0.843
1876	1.045
1877	0.795
1878	1.173
1879	0.877
1880	0.718
1881	1.089
1882	1.182
1883	1.095
1884	0.888
1885	1.217
1886	1.197
1887	1.171
1888	1.19
1889	1.083
1890	1.031
1891	1.176
1892	0.774
1893	1.101
1894	0.873
1895	0.873
1896	0.739
1897	0.845
1898	0.752
1899	1.115
1900	0.958
1901	1.076
1902	1.159
1903	1.453
1904	1.414
1905	1.102
1906	0.919
1907	0.986
1908	0.722
1909	0.914
1910	1.25
1911	1.143
1912	1.029
1913	1.077
1914	0.816
1915	0.878
1916	0.821
1917	0.996
1918	0.855
1919	1.058
1920	1.268
1921	0.575
1922	1.002
1923	0.614
1924	0.992
1925	0.847
1926	0.827
1927	0.848
1928	0.892
1929	0.801
1930	0.921
1931	1.097
1932	0.945
1933	1.163
1934	0.94
1935	0.789
1936	0.977
1937	1.108
1938	1.022
1939	0.902
1940	0.667
1941	0.904
1942	0.528
1943	0.966
1944	0.726
1945	0.696
1946	0.833
1947	0.819
1948	0.627
1949	1.002
1950	0.767
1951	0.843
1952	0.688
1953	0.533
1954	0.691
1955	0.922
1956	0.866
1957	0.904
1958	0.56
1959	0.333
1960	0.659
1961	0.531
1962	0.873
1963	0.908
1964	0.966
1965	1.132
1966	0.647
1967	0.786
1968	0.854
1969	1.086
1970	1.09
1971	1.216
1972	1.032
1973	1.207
1974	0.968
1975	0.88
1976	1.363
1977	1.446
1978	1.233
1979	1.376