# australia_newz001 - Paparoa - 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/3142
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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: australia_newz001 - Paparoa - 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
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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: Paparoa
#	Location:
#	Country: New Zealand
#	Northernmost_Latitude: -36.12
#	Southernmost_Latitude: -36.12
#	Easternmost_Longitude: 174.25
#	Westernmost_Longitude: 174.25
#	Elevation: 160 m
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# Data_Collection
#	Collection_Name: australia_newz001B
#	Earliest_Year: 1834
#	Most_Recent_Year: 1975
#	Time_Unit: y_ad
#	Core_Length:
#	Notes: {"database":{"database1":"LMR","database2":"Breits"}} {"climateInterpretation":{"basis":"", "climateVariable":"M", "climateVariableDetail":"air", "interpDirection":"positive", "seasonality":"[-12, 1, 2]"}}{"VSLite_parameters":{"T1":"4.47222355885","T2":"12.6861470977","M1":"0.022494842008","M2":"0.617077194951"}}
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# Species
#	Species_Name: tanekaha celery top pine
#	Species_Code: PHTR
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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
1834	0.478
1835	0.464
1836	0.753
1837	0.913
1838	1.007
1839	0.726
1840	0.731
1841	0.931
1842	0.85
1843	1.088
1844	0.752
1845	0.8
1846	0.604
1847	0.821
1848	1.028
1849	0.973
1850	0.935
1851	1.235
1852	1.158
1853	0.968
1854	0.935
1855	0.731
1856	1.059
1857	0.912
1858	0.981
1859	0.7
1860	0.954
1861	0.906
1862	0.734
1863	0.832
1864	0.868
1865	0.949
1866	0.909
1867	1.009
1868	1.003
1869	0.819
1870	0.982
1871	0.734
1872	0.679
1873	0.715
1874	0.862
1875	0.649
1876	0.808
1877	0.885
1878	0.721
1879	0.764
1880	0.748
1881	1.245
1882	0.726
1883	1.06
1884	1.107
1885	1.073
1886	0.81
1887	0.94
1888	1.325
1889	1.086
1890	1.157
1891	1.411
1892	1.407
1893	1.222
1894	1.252
1895	1.003
1896	0.926
1897	0.952
1898	1.292
1899	0.755
1900	1.377
1901	1.626
1902	1.439
1903	1.169
1904	1.306
1905	1.537
1906	1.365
1907	0.563
1908	0.794
1909	0.967
1910	1.129
1911	1.287
1912	1.159
1913	1.139
1914	0.432
1915	1.207
1916	1.131
1917	1.345
1918	1.355
1919	1.103
1920	1.039
1921	1.036
1922	1.188
1923	1.086
1924	1.031
1925	1.153
1926	1.511
1927	0.843
1928	1.016
1929	1.254
1930	1.339
1931	0.699
1932	0.61
1933	0.975
1934	1.115
1935	1.481
1936	1.369
1937	1.248
1938	0.649
1939	0.837
1940	1.15
1941	1.097
1942	0.558
1943	1.377
1944	1.038
1945	0.879
1946	0.684
1947	0.689
1948	0.899
1949	0.703
1950	1.224
1951	1.166
1952	1.287
1953	0.773
1954	0.808
1955	0.687
1956	0.764
1957	1.124
1958	1.063
1959	0.833
1960	1.073
1961	0.827
1962	1.074
1963	0.892
1964	1.295
1965	1.051
1966	0.956
1967	0.714
1968	0.94
1969	0.698
1970	0.745
1971	0.371
1972	0.815
1973	0.691
1974	0.453
1975	0.223