# australia_newz053 - Windy Creek - 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/4076
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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_newz053 - Windy Creek - 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: Windy Creek
#	Location:
#	Country: New Zealand
#	Northernmost_Latitude: -43.08
#	Southernmost_Latitude: -43.08
#	Easternmost_Longitude: 171.58
#	Westernmost_Longitude: 171.58
#	Elevation: 1350 m
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# Data_Collection
#	Collection_Name: australia_newz053B
#	Earliest_Year: 1839
#	Most_Recent_Year: 1979
#	Time_Unit: y_ad
#	Core_Length:
#	Notes: {"database":{"database1":"LMR","database2":"Breits"}} {"climateInterpretation":{"basis":"", "climateVariable":"T", "climateVariableDetail":"air", "interpDirection":"positive", "seasonality":"[-12, 1, 2]"}}{"VSLite_parameters":{"T1":"3.14380803737","T2":"12.0818505532","M1":"0.0230714865683","M2":"0.607466348768"}}
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# Species
#	Species_Name: mountain beech nothofagus
#	Species_Code: NOSO
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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
1839	1.084
1840	1.438
1841	1.804
1842	1.471
1843	1.028
1844	0.554
1845	1.508
1846	1.492
1847	1.39
1848	1.325
1849	1.185
1850	1.015
1851	0.445
1852	0.161
1853	1.091
1854	0.784
1855	0.68
1856	0.812
1857	0.905
1858	1.113
1859	1.233
1860	1.306
1861	1.357
1862	0.708
1863	0.529
1864	0.742
1865	0.75
1866	1.89
1867	1.224
1868	1.197
1869	1.42
1870	1.345
1871	1.307
1872	0.932
1873	1.361
1874	1.461
1875	1.446
1876	1.287
1877	1.165
1878	1.119
1879	1.463
1880	1.406
1881	1.061
1882	1.275
1883	0.892
1884	1.406
1885	1.17
1886	1.484
1887	0.975
1888	1.234
1889	1.035
1890	1.161
1891	1.069
1892	0.863
1893	1.222
1894	1.286
1895	1.654
1896	1.338
1897	1.043
1898	0.767
1899	0.806
1900	1.208
1901	1.2
1902	1.096
1903	0.744
1904	0.741
1905	0.891
1906	1.068
1907	0.733
1908	0.517
1909	1.122
1910	1.193
1911	0.688
1912	1.285
1913	1.204
1914	0.61
1915	1.186
1916	0.726
1917	0.149
1918	0.349
1919	1.247
1920	0.836
1921	1.721
1922	1.076
1923	1.659
1924	0.814
1925	1.32
1926	1.411
1927	1.325
1928	1.468
1929	1.03
1930	1.152
1931	1.136
1932	1.046
1933	0.549
1934	0.813
1935	0.316
1936	0.385
1937	0.957
1938	0.651
1939	0.632
1940	0.966
1941	0.564
1942	0.546
1943	0.992
1944	0.636
1945	0.679
1946	1.016
1947	1.061
1948	1.139
1949	0.734
1950	0.854
1951	0.875
1952	1.032
1953	1.269
1954	0.747
1955	1.193
1956	0.972
1957	0.563
1958	0.52
1959	0.727
1960	0.996
1961	1.144
1962	0.875
1963	0.299
1964	0.672
1965	1.121
1966	0.982
1967	1.226
1968	0.911
1969	0.847
1970	1.155
1971	1.054
1972	1.063
1973	0.773
1974	1.085
1975	0.624
1976	0.947
1977	1.224
1978	0.832
1979	1.147