# asia_indi013 - Manali - 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/2795
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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_indi013 - Manali - 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.
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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: Manali
#	Location:
#	Country: India
#	Northernmost_Latitude: 32.27
#	Southernmost_Latitude: 32.27
#	Easternmost_Longitude: 77.17
#	Westernmost_Longitude: 77.17
#	Elevation: 2000 m
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# Data_Collection
#	Collection_Name: asia_indi013B
#	Earliest_Year: 1724
#	Most_Recent_Year: 1988
#	Time_Unit: y_ad
#	Core_Length:
#	Notes: {"database":{"database1":"LMR","database2":"Breits"}} {"climateInterpretation":{"basis":"", "climateVariable":"M", "climateVariableDetail":"air", "interpDirection":"positive", "seasonality":"[6, 7, 8]"}}{"VSLite_parameters":{"T1":"4.91780914165","T2":"12.6457784015","M1":"0.0229683406872","M2":"0.577821575051"}}
#--------------------
# Species
#	Species_Name: deodar cedar
#	Species_Code: CDDE
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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
1724	0.869
1725	0.81
1726	0.737
1727	0.722
1728	0.691
1729	1.035
1730	0.875
1731	1.17
1732	0.963
1733	0.769
1734	0.727
1735	1.104
1736	1.298
1737	0.866
1738	1.175
1739	1.483
1740	1.586
1741	1.676
1742	1.141
1743	1.047
1744	0.979
1745	0.876
1746	0.779
1747	1.001
1748	0.93
1749	0.774
1750	0.914
1751	0.87
1752	0.759
1753	0.948
1754	1.014
1755	0.742
1756	0.979
1757	0.936
1758	1.223
1759	0.972
1760	0.896
1761	0.993
1762	1.091
1763	1.045
1764	0.945
1765	1.028
1766	1.232
1767	1.174
1768	1.144
1769	0.985
1770	0.942
1771	1.027
1772	1.215
1773	0.827
1774	0.875
1775	0.697
1776	0.911
1777	1.112
1778	1.31
1779	1.077
1780	0.944
1781	0.747
1782	0.656
1783	0.919
1784	1.09
1785	0.897
1786	1.161
1787	0.972
1788	0.856
1789	1.139
1790	0.868
1791	1.049
1792	0.862
1793	1.068
1794	0.809
1795	1.073
1796	0.857
1797	0.798
1798	0.959
1799	0.845
1800	0.727
1801	0.885
1802	0.701
1803	0.757
1804	0.559
1805	0.84
1806	0.937
1807	0.723
1808	1.077
1809	0.956
1810	0.92
1811	0.823
1812	0.999
1813	0.703
1814	0.787
1815	0.699
1816	0.732
1817	1.081
1818	1.198
1819	1.298
1820	1.062
1821	0.894
1822	0.772
1823	1.059
1824	1.111
1825	0.891
1826	0.712
1827	0.977
1828	1.097
1829	0.835
1830	0.971
1831	0.721
1832	0.797
1833	0.849
1834	0.994
1835	1.007
1836	0.862
1837	0.971
1838	1.01
1839	0.888
1840	0.988
1841	0.893
1842	1.052
1843	0.878
1844	0.99
1845	0.915
1846	0.78
1847	0.842
1848	0.983
1849	0.715
1850	0.702
1851	0.984
1852	1.097
1853	1.046
1854	0.845
1855	1.019
1856	0.776
1857	0.823
1858	0.686
1859	1.18
1860	0.976
1861	0.952
1862	0.996
1863	1.066
1864	1.018
1865	1.114
1866	1.101
1867	1.214
1868	1.123
1869	0.907
1870	1.062
1871	1.158
1872	1.089
1873	0.932
1874	1.069
1875	0.85
1876	1.108
1877	1.16
1878	1.416
1879	1.216
1880	1.103
1881	1.258
1882	1.191
1883	0.955
1884	1.218
1885	1.38
1886	1.344
1887	0.928
1888	1.058
1889	1.425
1890	1.229
1891	1.171
1892	0.656
1893	1.217
1894	1.26
1895	1.237
1896	1.342
1897	1.402
1898	0.898
1899	1.007
1900	1.097
1901	1.024
1902	1.136
1903	1.157
1904	0.835
1905	0.936
1906	0.819
1907	0.797
1908	0.824
1909	0.908
1910	0.708
1911	0.801
1912	0.998
1913	0.961
1914	1.142
1915	0.979
1916	0.86
1917	1.177
1918	0.866
1919	1.117
1920	1.013
1921	0.326
1922	0.854
1923	0.84
1924	1.019
1925	0.984
1926	1.033
1927	0.856
1928	0.899
1929	0.86
1930	0.974
1931	0.923
1932	0.605
1933	0.988
1934	0.868
1935	0.91
1936	1.105
1937	0.926
1938	0.921
1939	0.902
1940	1.044
1941	0.522
1942	1.087
1943	0.959
1944	0.86
1945	0.911
1946	0.549
1947	0.676
1948	0.864
1949	0.997
1950	1.033
1951	0.857
1952	1.028
1953	0.877
1954	0.827
1955	1.075
1956	0.697
1957	1.095
1958	0.862
1959	0.869
1960	0.783
1961	0.931
1962	0.988
1963	0.914
1964	1.258
1965	0.965
1966	0.936
1967	1.037
1968	0.817
1969	0.976
1970	0.527
1971	0.749
1972	0.682
1973	0.848
1974	0.728
1975	0.806
1976	0.798
1977	0.834
1978	0.578
1979	0.918
1980	0.749
1981	1.093
1982	1.201
1983	1.285
1984	0.95
1985	1.152
1986	1.296
1987	1.584
1988	1.203