# asia_nepa011 - BudoRouke - Breitenmoser Tree Ring Chronology Data
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#		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/3768
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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_nepa011 - BudoRouke - 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: BudoRouke
#	Location:
#	Country: Nepal
#	Northernmost_Latitude: 27.45
#	Southernmost_Latitude: 27.45
#	Easternmost_Longitude: 87.17
#	Westernmost_Longitude: 87.17
#	Elevation: 2970 m
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# Data_Collection
#	Collection_Name: asia_nepa011B
#	Earliest_Year: 1692
#	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":"5.46075522306","T2":"19.3750324545","M1":"0.0229916273727","M2":"0.225398216008"}}
#--------------------
# 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)
#
##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
1692	1.008
1693	1.051
1694	0.929
1695	0.928
1696	1.03
1697	1.107
1698	0.999
1699	1.091
1700	1.16
1701	1.19
1702	1.355
1703	1.318
1704	1.036
1705	1.116
1706	1.296
1707	0.99
1708	1.044
1709	1.042
1710	1.158
1711	1.116
1712	1.005
1713	0.775
1714	1.169
1715	0.982
1716	1.071
1717	0.884
1718	0.813
1719	0.739
1720	1.053
1721	0.96
1722	0.91
1723	0.818
1724	0.659
1725	0.715
1726	0.807
1727	0.653
1728	0.635
1729	0.626
1730	0.806
1731	0.802
1732	0.732
1733	0.731
1734	1.002
1735	0.811
1736	0.763
1737	0.768
1738	0.727
1739	0.774
1740	0.711
1741	0.668
1742	0.943
1743	0.84
1744	0.807
1745	0.703
1746	0.996
1747	1.193
1748	0.98
1749	0.782
1750	0.705
1751	0.744
1752	0.681
1753	0.697
1754	0.776
1755	1.012
1756	1.12
1757	1.015
1758	1.023
1759	0.979
1760	1.027
1761	0.947
1762	0.954
1763	0.876
1764	1.151
1765	1.245
1766	1.136
1767	1.013
1768	0.989
1769	0.863
1770	0.977
1771	1.102
1772	1.233
1773	1.23
1774	0.986
1775	1.016
1776	0.965
1777	1.314
1778	1.058
1779	0.949
1780	0.848
1781	1.032
1782	0.945
1783	1.093
1784	1.274
1785	1.393
1786	1.296
1787	0.957
1788	1.139
1789	1.19
1790	1.115
1791	1.074
1792	1.059
1793	1.028
1794	1.105
1795	0.964
1796	1.068
1797	1.061
1798	1.155
1799	1.085
1800	1.089
1801	1.029
1802	1.127
1803	1.049
1804	1.066
1805	1.245
1806	1.286
1807	1.199
1808	0.844
1809	0.837
1810	0.919
1811	0.869
1812	0.77
1813	0.881
1814	1.074
1815	1.189
1816	1.117
1817	0.959
1818	0.748
1819	0.744
1820	0.766
1821	0.823
1822	0.891
1823	0.721
1824	0.995
1825	0.792
1826	1.03
1827	1.01
1828	0.843
1829	1.069
1830	1.202
1831	1.117
1832	1.159
1833	1.374
1834	1.247
1835	1.222
1836	1.13
1837	1.182
1838	0.907
1839	1.323
1840	1.316
1841	1.017
1842	1.033
1843	0.87
1844	0.928
1845	0.686
1846	0.961
1847	0.811
1848	1.038
1849	0.629
1850	0.672
1851	0.62
1852	0.676
1853	0.838
1854	0.92
1855	0.948
1856	0.886
1857	0.953
1858	1.077
1859	0.878
1860	0.892
1861	0.747
1862	0.774
1863	0.684
1864	0.777
1865	1.026
1866	0.779
1867	0.912
1868	0.762
1869	0.677
1870	0.719
1871	1.011
1872	0.667
1873	0.672
1874	0.684
1875	0.67
1876	0.891
1877	1.16
1878	0.972
1879	1.132
1880	1.009
1881	1.238
1882	1.099
1883	1.231
1884	1.009
1885	1.005
1886	0.938
1887	0.781
1888	0.906
1889	0.952
1890	0.935
1891	1.157
1892	0.924
1893	1.199
1894	1.144
1895	0.843
1896	1.018
1897	1.013
1898	0.996
1899	1.099
1900	1.074
1901	0.708
1902	0.821
1903	0.978
1904	0.806
1905	0.781
1906	0.761
1907	0.944
1908	1.146
1909	1.126
1910	1.807
1911	1.879
1912	1.009
1913	0.878
1914	1.08
1915	0.679
1916	0.655
1917	0.754
1918	0.619
1919	0.945
1920	0.84
1921	0.835
1922	1.265
1923	1.02
1924	0.989
1925	1.082
1926	0.934
1927	0.668
1928	0.757
1929	0.783
1930	0.945
1931	0.861
1932	0.773
1933	0.871
1934	0.693
1935	0.75
1936	0.898
1937	0.772
1938	0.674
1939	0.763
1940	0.719
1941	0.606
1942	0.845
1943	0.884
1944	0.957
1945	0.889
1946	1.03
1947	1.146
1948	0.965
1949	0.904
1950	0.782
1951	0.716
1952	0.771
1953	1.058
1954	1.172
1955	0.988
1956	0.903
1957	0.895
1958	0.715
1959	0.524
1960	0.704
1961	0.776
1962	0.993
1963	0.827
1964	0.495
1965	0.718
1966	1.278
1967	0.877
1968	1.065
1969	1.088
1970	1.009
1971	0.864
1972	0.727
1973	0.829
1974	0.964
1975	0.946
1976	0.873
1977	0.884
1978	0.871
1979	1.152
1980	0.879
1981	1.204
1982	0.871
1983	0.936
1984	0.796
1985	1.146
1986	1.418
1987	1.304
1988	1.122
1989	0.853
1990	0.907
1991	0.782
1992	0.877
1993	1.116
1994	0.939
1995	0.805
1996	0.708