# asia_indi002 - Gulmarg - 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/3567
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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_indi002 - Gulmarg - 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: Gulmarg
#	Location:
#	Country: India
#	Northernmost_Latitude: 35.08
#	Southernmost_Latitude: 35.08
#	Easternmost_Longitude: 74.3
#	Westernmost_Longitude: 74.3
#	Elevation: 2740 m
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# Data_Collection
#	Collection_Name: asia_indi002B
#	Earliest_Year: 1798
#	Most_Recent_Year: 1980
#	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":"3.42761284165","T2":"17.059269436","M1":"0.0223344281971","M2":"0.339492264299"}}
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# Species
#	Species_Name: Himalayan silver fir
#	Species_Code: ABPI
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# Chronology:
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# Variables
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# 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
1798	0.95
1799	0.95
1800	1.136
1801	1.063
1802	0.966
1803	0.915
1804	0.799
1805	0.809
1806	0.77
1807	0.89
1808	0.749
1809	0.731
1810	0.9
1811	0.877
1812	0.808
1813	0.862
1814	1.012
1815	1.089
1816	1.148
1817	0.901
1818	1.012
1819	1.072
1820	1.383
1821	1.082
1822	1.071
1823	0.728
1824	0.689
1825	0.638
1826	0.785
1827	0.699
1828	0.882
1829	0.93
1830	0.963
1831	0.661
1832	0.933
1833	0.849
1834	1.161
1835	1.192
1836	1.333
1837	1.371
1838	1.166
1839	0.928
1840	1.091
1841	0.93
1842	0.946
1843	1.018
1844	1.139
1845	0.756
1846	0.807
1847	0.79
1848	0.901
1849	0.946
1850	0.865
1851	0.99
1852	0.777
1853	0.941
1854	1.035
1855	1.057
1856	1.44
1857	1.066
1858	1.086
1859	1.055
1860	1.042
1861	0.604
1862	0.612
1863	0.522
1864	0.734
1865	1.0
1866	0.904
1867	0.76
1868	0.814
1869	0.864
1870	0.928
1871	0.655
1872	0.835
1873	0.915
1874	0.888
1875	0.653
1876	1.0
1877	0.88
1878	1.238
1879	1.193
1880	1.076
1881	0.831
1882	0.942
1883	0.841
1884	0.89
1885	0.652
1886	0.915
1887	0.925
1888	1.176
1889	1.153
1890	1.023
1891	1.01
1892	1.218
1893	1.433
1894	1.818
1895	1.563
1896	1.46
1897	1.188
1898	1.081
1899	1.141
1900	0.988
1901	1.08
1902	1.068
1903	1.085
1904	1.327
1905	1.151
1906	1.078
1907	1.094
1908	1.18
1909	1.147
1910	1.119
1911	0.894
1912	1.04
1913	0.988
1914	0.984
1915	0.773
1916	0.86
1917	0.906
1918	0.959
1919	0.975
1920	0.914
1921	0.99
1922	1.073
1923	1.155
1924	1.032
1925	1.095
1926	0.955
1927	1.127
1928	0.887
1929	0.856
1930	1.021
1931	1.241
1932	1.608
1933	1.167
1934	1.008
1935	1.287
1936	1.32
1937	1.058
1938	1.073
1939	0.905
1940	0.969
1941	0.864
1942	0.983
1943	1.078
1944	1.068
1945	0.966
1946	1.041
1947	0.992
1948	1.3
1949	1.46
1950	1.176
1951	1.195
1952	1.099
1953	0.883
1954	0.996
1955	0.71
1956	0.662
1957	0.627
1958	0.892
1959	0.939
1960	0.996
1961	1.077
1962	0.868
1963	0.662
1964	0.681
1965	0.699
1966	0.728
1967	0.711
1968	0.51
1969	0.577
1970	0.677
1971	0.673
1972	0.597
1973	0.69
1974	0.74
1975	0.671
1976	0.674
1977	0.976
1978	1.297
1979	0.892
1980	1.005