# asia_nepa009 - Bhule Pokari - Breitenmoser Tree Ring Chronology Data
#-----------------------------------------------------------------------
#		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/3765
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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
#--------------------
# Title
#	Study_Name: asia_nepa009 - Bhule Pokari - 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: Bhule Pokari
#	Location:
#	Country: Nepal
#	Northernmost_Latitude: 27.43
#	Southernmost_Latitude: 27.43
#	Easternmost_Longitude: 86.28
#	Westernmost_Longitude: 86.28
#	Elevation: 3600 m
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# Data_Collection
#	Collection_Name: asia_nepa009B
#	Earliest_Year: 1696
#	Most_Recent_Year: 1998
#	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":"5.53672180595","T2":"21.134074382","M1":"0.022316112392","M2":"0.252094981115"}}
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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)
#
##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
1696	1.126
1697	0.907
1698	0.789
1699	1.012
1700	1.051
1701	1.118
1702	1.181
1703	1.023
1704	1.214
1705	1.672
1706	1.29
1707	0.986
1708	1.137
1709	1.148
1710	1.022
1711	0.919
1712	1.195
1713	0.963
1714	0.906
1715	0.851
1716	0.971
1717	1.074
1718	1.196
1719	1.039
1720	1.044
1721	0.992
1722	1.01
1723	1.208
1724	1.154
1725	0.888
1726	0.82
1727	0.88
1728	1.045
1729	0.892
1730	0.822
1731	0.755
1732	0.717
1733	0.669
1734	0.804
1735	0.912
1736	1.079
1737	0.902
1738	0.822
1739	0.885
1740	0.885
1741	0.744
1742	0.643
1743	0.728
1744	1.027
1745	1.01
1746	1.068
1747	1.163
1748	1.587
1749	1.238
1750	1.021
1751	1.307
1752	1.219
1753	1.203
1754	1.368
1755	1.067
1756	1.019
1757	0.794
1758	0.879
1759	0.961
1760	0.86
1761	0.826
1762	0.986
1763	1.03
1764	0.818
1765	0.939
1766	1.101
1767	1.038
1768	0.773
1769	0.705
1770	0.682
1771	0.816
1772	0.815
1773	0.825
1774	0.883
1775	1.0
1776	0.882
1777	0.865
1778	0.954
1779	1.189
1780	1.238
1781	1.186
1782	1.033
1783	0.885
1784	0.728
1785	0.694
1786	0.888
1787	0.806
1788	0.9
1789	1.064
1790	1.018
1791	0.799
1792	0.782
1793	0.815
1794	1.1
1795	1.005
1796	1.045
1797	0.986
1798	1.093
1799	1.133
1800	1.404
1801	1.288
1802	1.441
1803	1.55
1804	1.366
1805	0.9
1806	0.811
1807	0.716
1808	0.879
1809	0.877
1810	0.751
1811	0.673
1812	0.598
1813	0.517
1814	0.608
1815	0.509
1816	0.382
1817	0.284
1818	0.285
1819	0.241
1820	0.382
1821	0.38
1822	0.424
1823	0.637
1824	0.742
1825	0.724
1826	0.804
1827	0.976
1828	0.824
1829	0.597
1830	0.498
1831	0.508
1832	0.5
1833	0.556
1834	0.556
1835	0.639
1836	0.768
1837	0.871
1838	0.829
1839	0.786
1840	0.869
1841	0.774
1842	0.891
1843	1.006
1844	0.994
1845	1.144
1846	1.294
1847	0.982
1848	1.062
1849	1.073
1850	1.19
1851	1.253
1852	1.04
1853	1.028
1854	0.903
1855	0.93
1856	1.025
1857	0.926
1858	1.063
1859	0.944
1860	0.936
1861	1.036
1862	1.117
1863	1.08
1864	0.803
1865	0.944
1866	0.852
1867	0.932
1868	0.922
1869	1.209
1870	1.138
1871	1.245
1872	1.188
1873	1.245
1874	1.127
1875	1.461
1876	1.531
1877	1.248
1878	1.291
1879	1.563
1880	1.391
1881	1.293
1882	1.366
1883	1.438
1884	1.258
1885	1.233
1886	1.068
1887	0.873
1888	1.031
1889	1.573
1890	1.394
1891	1.259
1892	1.249
1893	1.103
1894	1.096
1895	0.985
1896	1.14
1897	1.25
1898	1.279
1899	1.158
1900	1.347
1901	1.4
1902	1.389
1903	1.08
1904	1.211
1905	0.729
1906	0.583
1907	0.652
1908	0.901
1909	1.031
1910	1.057
1911	1.372
1912	1.247
1913	1.134
1914	1.101
1915	0.99
1916	0.956
1917	0.953
1918	0.99
1919	1.143
1920	1.292
1921	1.477
1922	1.212
1923	1.228
1924	1.895
1925	1.484
1926	0.943
1927	0.832
1928	0.954
1929	1.075
1930	1.336
1931	1.632
1932	1.159
1933	1.016
1934	1.255
1935	1.319
1936	1.174
1937	1.073
1938	1.154
1939	0.962
1940	1.125
1941	1.134
1942	1.209
1943	1.098
1944	1.06
1945	1.23
1946	1.082
1947	1.047
1948	0.949
1949	0.805
1950	0.797
1951	0.918
1952	1.171
1953	0.925
1954	1.096
1955	1.132
1956	1.056
1957	1.12
1958	1.615
1959	1.143
1960	0.89
1961	0.761
1962	0.692
1963	0.835
1964	0.919
1965	0.664
1966	0.557
1967	0.306
1968	0.231
1969	0.363
1970	0.447
1971	0.471
1972	0.493
1973	0.654
1974	0.792
1975	0.878
1976	0.864
1977	1.145
1978	0.598
1979	0.553
1980	0.558
1981	0.681
1982	0.697
1983	0.73
1984	0.576
1985	0.694
1986	0.717
1987	0.82
1988	0.874
1989	0.774
1990	0.84
1991	0.852
1992	0.717
1993	0.631
1994	0.548
1995	0.589
1996	0.822
1997	0.805
1998	0.845