# australia_newz054 - Upper Takahe Valley - 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/4075
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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_newz054 - Upper Takahe Valley - 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
#--------------------
# 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: Upper Takahe Valley
#	Location:
#	Country: New Zealand
#	Northernmost_Latitude: -45.2
#	Southernmost_Latitude: -45.2
#	Easternmost_Longitude: 167.65
#	Westernmost_Longitude: 167.65
#	Elevation: 1000 m
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# Data_Collection
#	Collection_Name: australia_newz054B
#	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":"5.22729204733","T2":"13.2874339448","M1":"0.0227441776489","M2":"0.440098031243"}}
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# Species
#	Species_Name: silver beech nothofagus
#	Species_Code: NOME
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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	1.467
1840	1.461
1841	1.637
1842	1.294
1843	0.806
1844	0.868
1845	1.202
1846	1.301
1847	1.27
1848	1.535
1849	1.365
1850	1.674
1851	2.007
1852	1.444
1853	1.814
1854	0.502
1855	1.64
1856	1.573
1857	1.489
1858	1.469
1859	0.537
1860	1.141
1861	1.203
1862	0.954
1863	0.973
1864	1.552
1865	1.215
1866	1.485
1867	0.796
1868	1.164
1869	1.096
1870	1.322
1871	1.394
1872	0.706
1873	1.212
1874	1.163
1875	1.322
1876	0.79
1877	0.989
1878	1.104
1879	1.501
1880	1.165
1881	1.14
1882	1.874
1883	0.774
1884	1.42
1885	1.391
1886	1.646
1887	0.576
1888	1.327
1889	1.324
1890	1.301
1891	1.255
1892	0.818
1893	1.62
1894	0.898
1895	0.764
1896	1.515
1897	0.627
1898	1.183
1899	0.927
1900	1.013
1901	1.193
1902	0.743
1903	1.358
1904	0.595
1905	0.23
1906	0.774
1907	0.211
1908	0.834
1909	0.678
1910	0.725
1911	0.78
1912	1.024
1913	1.128
1914	0.452
1915	1.322
1916	0.545
1917	0.916
1918	0.625
1919	1.157
1920	0.861
1921	1.559
1922	0.684
1923	1.224
1924	0.995
1925	1.044
1926	0.856
1927	1.26
1928	0.852
1929	0.652
1930	0.614
1931	1.072
1932	1.203
1933	1.337
1934	1.095
1935	0.538
1936	0.844
1937	1.67
1938	0.841
1939	0.473
1940	1.491
1941	0.996
1942	0.924
1943	1.337
1944	1.277
1945	1.437
1946	1.095
1947	0.65
1948	1.045
1949	0.797
1950	1.005
1951	0.404
1952	0.958
1953	0.862
1954	1.031
1955	0.948
1956	0.328
1957	0.584
1958	0.311
1959	0.158
1960	0.779
1961	1.19
1962	0.858
1963	0.828
1964	0.83
1965	0.912
1966	0.381
1967	0.591
1968	0.906
1969	0.856
1970	1.534
1971	0.642
1972	1.319
1973	1.134
1974	1.268
1975	1.074
1976	1.038
1977	1.307
1978	0.386
1979	1.351