# australia_newz039 - Cream Creek - Breitenmoser Tree Ring Chronology Data
#-----------------------------------------------------------------------
#		World Data Center for Paleoclimatology, Boulder
#				and
#		NOAA Paleoclimatology Program
#-----------------------------------------------------------------------
# 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.
#
#
# Online_Resource:
#
# Online_Resource: https://www.ncdc.noaa.gov/paleo/study/24611
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# Original_Source_URL:https://www.ncdc.noaa.gov/paleo/study/4049
#
# Description/Documentation lines begin with #
# Data lines have no #
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# Archive: Tree Rings
#--------------------
# Contribution_Date
#	Date: 2016-01-07
#--------------------
# Title
#	Study_Name: australia_newz039 - Cream Creek - Breitenmoser Tree Ring Chronology Data
#--------------------
# 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.
#--------------------
#	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: Cream Creek
#	Location:
#	Country: New Zealand
#	Northernmost_Latitude: -43.08
#	Southernmost_Latitude: -43.08
#	Easternmost_Longitude: 170.98
#	Westernmost_Longitude: 170.98
#	Elevation: 800 m
#--------------------
# Data_Collection
#	Collection_Name: australia_newz039B
#	Earliest_Year: 1684
#	Most_Recent_Year: 1978
#	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":"3.50008220374","T2":"16.6005425792","M1":"0.0225600377483","M2":"0.405225619795"}}
#--------------------
# Species
#	Species_Name: New Zealand cedar
#	Species_Code: LIBI
#--------------------
# Chronology:
#
#
#
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# Variables
#
# 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)
#
##age	age, , ,years AD, , , , ,N
##trsgi	tree ring standardized growth index, tree ring, ,percent relative to mean growth, , Tree Rings, , ,N
#
#--------------------
# Data:
# Data lines follow (have no #)
# Data line format - tab-delimited text, variable short name as header
# Missing Values: nan
#
age	trsgi
1684	0.961
1685	1.055
1686	0.847
1687	0.525
1688	0.723
1689	0.811
1690	1.142
1691	1.086
1692	0.838
1693	0.938
1694	1.023
1695	1.091
1696	1.038
1697	1.095
1698	1.081
1699	0.984
1700	1.053
1701	1.042
1702	0.805
1703	1.135
1704	1.109
1705	1.1
1706	1.151
1707	0.709
1708	0.584
1709	0.866
1710	0.738
1711	0.744
1712	0.915
1713	0.772
1714	1.078
1715	0.987
1716	0.902
1717	0.853
1718	0.526
1719	0.439
1720	0.704
1721	0.808
1722	0.962
1723	1.0
1724	1.0
1725	1.125
1726	0.97
1727	1.134
1728	1.42
1729	1.034
1730	1.211
1731	1.05
1732	0.944
1733	0.866
1734	0.742
1735	1.146
1736	1.144
1737	0.976
1738	0.871
1739	1.215
1740	1.024
1741	0.828
1742	0.823
1743	0.879
1744	1.035
1745	1.201
1746	1.246
1747	1.046
1748	1.216
1749	1.007
1750	0.748
1751	1.141
1752	1.009
1753	1.022
1754	0.915
1755	0.881
1756	1.042
1757	1.109
1758	1.021
1759	1.085
1760	0.9
1761	0.893
1762	0.971
1763	0.93
1764	1.028
1765	0.972
1766	0.912
1767	0.882
1768	1.024
1769	0.938
1770	0.522
1771	0.727
1772	0.547
1773	0.648
1774	0.677
1775	0.762
1776	0.69
1777	1.035
1778	1.121
1779	1.154
1780	1.216
1781	1.189
1782	1.017
1783	0.991
1784	1.04
1785	1.057
1786	1.259
1787	1.156
1788	1.156
1789	1.17
1790	0.997
1791	0.866
1792	0.964
1793	0.963
1794	0.965
1795	0.826
1796	0.865
1797	1.173
1798	0.953
1799	0.832
1800	1.348
1801	1.431
1802	1.488
1803	1.099
1804	1.561
1805	1.877
1806	1.103
1807	0.53
1808	0.629
1809	0.76
1810	0.9
1811	0.893
1812	1.239
1813	1.022
1814	1.144
1815	1.508
1816	1.482
1817	1.088
1818	0.87
1819	0.948
1820	1.051
1821	1.08
1822	1.124
1823	1.199
1824	1.316
1825	1.54
1826	1.067
1827	1.426
1828	1.413
1829	1.373
1830	1.026
1831	1.035
1832	0.764
1833	0.64
1834	0.974
1835	1.219
1836	1.325
1837	1.26
1838	1.309
1839	1.223
1840	1.467
1841	1.669
1842	1.418
1843	1.313
1844	1.147
1845	1.4
1846	1.287
1847	1.333
1848	1.226
1849	1.044
1850	0.71
1851	0.738
1852	0.78
1853	0.923
1854	0.982
1855	1.147
1856	0.84
1857	0.907
1858	0.723
1859	0.594
1860	0.501
1861	0.754
1862	0.75
1863	0.8
1864	1.053
1865	1.077
1866	1.161
1867	1.004
1868	1.126
1869	1.173
1870	1.257
1871	1.139
1872	1.114
1873	1.417
1874	1.476
1875	1.526
1876	1.205
1877	1.25
1878	0.858
1879	1.252
1880	1.093
1881	1.119
1882	1.09
1883	1.124
1884	1.157
1885	1.226
1886	1.22
1887	1.124
1888	1.036
1889	1.178
1890	1.103
1891	1.199
1892	1.452
1893	1.42
1894	0.99
1895	0.674
1896	1.345
1897	1.165
1898	0.769
1899	0.841
1900	0.9
1901	0.854
1902	0.889
1903	0.73
1904	0.682
1905	0.531
1906	0.585
1907	0.541
1908	0.682
1909	0.671
1910	0.715
1911	0.793
1912	0.731
1913	0.92
1914	0.825
1915	0.95
1916	0.767
1917	1.056
1918	0.869
1919	0.897
1920	0.87
1921	0.881
1922	0.808
1923	0.612
1924	0.715
1925	0.604
1926	0.632
1927	0.768
1928	0.668
1929	0.797
1930	0.841
1931	0.939
1932	1.037
1933	1.118
1934	0.998
1935	0.435
1936	0.383
1937	0.462
1938	0.245
1939	0.346
1940	0.699
1941	0.86
1942	0.791
1943	0.799
1944	0.831
1945	0.721
1946	0.753
1947	0.825
1948	1.021
1949	0.923
1950	1.215
1951	0.69
1952	0.883
1953	0.954
1954	1.001
1955	0.875
1956	0.845
1957	0.772
1958	0.497
1959	0.48
1960	0.847
1961	0.727
1962	0.623
1963	0.59
1964	0.538
1965	0.671
1966	0.594
1967	0.745
1968	0.459
1969	0.277
1970	0.725
1971	1.167
1972	1.589
1973	1.789
1974	1.654
1975	1.612
1976	1.581
1977	1.626
1978	1.232