# africa_morc013 - Tazzeka - 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/2937
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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: africa_morc013 - Tazzeka - Breitenmoser Tree Ring Chronology Data
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# Investigators
#	Investigators:  Breitenmoser, P.; Bronnimann, S.; Frank, D.
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# Description_and_Notes
#	Description: Data from Breitenmoser 2014 Journal of past Climate supplementary, see publication for ARSTAN standardization details
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# 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: Tazzeka
#	Location:
#	Country: Morocco
#	Northernmost_Latitude: 34.08
#	Southernmost_Latitude: 34.08
#	Easternmost_Longitude: -4.18
#	Westernmost_Longitude: -4.18
#	Elevation: 1900 m
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# Data_Collection
#	Collection_Name: africa_morc013B
#	Earliest_Year: 1854
#	Most_Recent_Year: 1984
#	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":"5.3270097532","T2":"16.6972006744","M1":"0.0221173107309","M2":"0.292490766697"}}
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# Species
#	Species_Name: Atlantic cedar
#	Species_Code: CDAT
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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
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age	trsgi
1854	0.497
1855	0.618
1856	0.834
1857	0.831
1858	0.942
1859	0.745
1860	0.937
1861	1.177
1862	0.959
1863	0.677
1864	0.166
1865	0.462
1866	0.745
1867	0.982
1868	1.085
1869	1.088
1870	1.213
1871	1.333
1872	1.14
1873	1.173
1874	1.085
1875	1.144
1876	1.13
1877	1.32
1878	1.258
1879	0.67
1880	0.818
1881	0.954
1882	1.02
1883	1.196
1884	1.202
1885	1.1
1886	1.038
1887	1.009
1888	0.981
1889	0.859
1890	0.768
1891	0.873
1892	0.972
1893	1.05
1894	0.767
1895	0.982
1896	1.118
1897	1.267
1898	1.166
1899	1.389
1900	1.198
1901	1.222
1902	1.037
1903	1.125
1904	1.084
1905	1.307
1906	1.078
1907	0.913
1908	0.963
1909	0.962
1910	0.852
1911	0.85
1912	1.159
1913	0.941
1914	1.219
1915	0.811
1916	1.06
1917	1.133
1918	1.111
1919	1.209
1920	1.041
1921	0.931
1922	1.109
1923	0.853
1924	0.95
1925	1.057
1926	0.878
1927	0.826
1928	0.715
1929	0.894
1930	0.762
1931	0.735
1932	1.025
1933	0.87
1934	0.709
1935	0.892
1936	0.826
1937	0.922
1938	0.542
1939	0.692
1940	0.721
1941	0.752
1942	0.877
1943	1.065
1944	1.04
1945	0.619
1946	0.766
1947	1.022
1948	1.063
1949	1.115
1950	1.256
1951	1.206
1952	0.976
1953	0.968
1954	0.98
1955	1.155
1956	0.911
1957	0.951
1958	1.043
1959	0.913
1960	0.984
1961	0.85
1962	0.906
1963	0.962
1964	0.824
1965	0.971
1966	1.089
1967	1.097
1968	1.042
1969	1.196
1970	1.061
1971	1.189
1972	1.056
1973	1.055
1974	0.887
1975	0.971
1976	1.107
1977	1.088
1978	1.004
1979	0.929
1980	0.812
1981	0.946
1982	0.994
1983	1.09
1984	0.972