# asia_indi004 - Sarbal - 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/3575
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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_indi004 - Sarbal - 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:
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#	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: Sarbal
#	Location:
#	Country: India
#	Northernmost_Latitude: 34.5
#	Southernmost_Latitude: 34.5
#	Easternmost_Longitude: 75.75
#	Westernmost_Longitude: 75.75
#	Elevation: 3110 m
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# Data_Collection
#	Collection_Name: asia_indi004B
#	Earliest_Year: 1800
#	Most_Recent_Year: 1981
#	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":"3.53771663921","T2":"14.9636435665","M1":"0.0232560820896","M2":"0.502059356513"}}
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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
1800	1.0
1801	0.944
1802	0.722
1803	0.772
1804	0.845
1805	0.735
1806	0.694
1807	0.96
1808	0.968
1809	0.835
1810	0.988
1811	0.954
1812	0.845
1813	0.836
1814	1.215
1815	1.135
1816	1.289
1817	1.014
1818	1.196
1819	1.048
1820	1.203
1821	1.146
1822	1.115
1823	0.929
1824	0.836
1825	0.863
1826	0.877
1827	0.816
1828	0.863
1829	0.96
1830	1.059
1831	0.957
1832	1.036
1833	1.066
1834	1.004
1835	0.904
1836	1.112
1837	1.276
1838	1.206
1839	1.326
1840	1.355
1841	1.012
1842	1.174
1843	1.142
1844	1.089
1845	0.922
1846	0.943
1847	0.861
1848	1.054
1849	1.006
1850	1.003
1851	1.165
1852	0.951
1853	0.957
1854	1.031
1855	1.335
1856	1.514
1857	1.56
1858	1.433
1859	1.069
1860	1.131
1861	1.008
1862	0.932
1863	0.894
1864	0.978
1865	0.978
1866	0.806
1867	0.747
1868	0.741
1869	0.757
1870	1.017
1871	0.834
1872	0.762
1873	0.95
1874	1.013
1875	0.836
1876	0.956
1877	1.053
1878	1.047
1879	0.855
1880	0.904
1881	0.989
1882	0.977
1883	0.878
1884	0.854
1885	0.691
1886	0.839
1887	0.689
1888	0.755
1889	0.899
1890	0.895
1891	1.072
1892	1.21
1893	1.239
1894	1.483
1895	1.123
1896	1.177
1897	0.799
1898	0.982
1899	0.912
1900	1.152
1901	1.236
1902	1.081
1903	1.21
1904	1.324
1905	1.087
1906	0.958
1907	1.126
1908	0.988
1909	0.875
1910	0.783
1911	0.838
1912	0.84
1913	0.765
1914	0.907
1915	0.699
1916	0.654
1917	0.77
1918	0.798
1919	0.864
1920	0.927
1921	0.979
1922	1.083
1923	0.958
1924	0.796
1925	0.788
1926	0.894
1927	1.006
1928	1.062
1929	1.174
1930	1.264
1931	1.215
1932	1.261
1933	1.138
1934	0.984
1935	1.092
1936	0.974
1937	0.863
1938	0.863
1939	0.78
1940	0.795
1941	0.825
1942	0.901
1943	1.09
1944	1.179
1945	1.122
1946	0.949
1947	0.953
1948	1.149
1949	1.31
1950	1.06
1951	1.229
1952	0.96
1953	0.985
1954	1.021
1955	0.971
1956	1.006
1957	0.751
1958	1.121
1959	0.919
1960	0.892
1961	0.746
1962	0.61
1963	0.737
1964	0.702
1965	0.727
1966	0.804
1967	0.815
1968	0.78
1969	0.849
1970	0.972
1971	0.904
1972	0.821
1973	1.088
1974	0.952
1975	0.97
1976	1.013
1977	1.172
1978	1.404
1979	1.343
1980	1.479
1981	1.605