# northamerica_usa_ak065 - Gordon's Cat - 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/3052
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# 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: northamerica_usa_ak065 - Gordon's Cat - 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 VaganovÃÂ¢ÃÂÃÂShashkin 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 4ÃÂ¢ÃÂÃÂ6 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 modelÃÂ¢ÃÂÃÂs 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: Gordon's Cat
#	Location:
#	Country: United States
#	Northernmost_Latitude: 65.2
#	Southernmost_Latitude: 65.2
#	Easternmost_Longitude: -162.2
#	Westernmost_Longitude: -162.2
#	Elevation: 168 m
#--------------------
# Data_Collection
#	Collection_Name: northamerica_usa_ak065B
#	Earliest_Year: 1734
#	Most_Recent_Year: 2002
#	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":"4.93703555732","T2":"17.2092896047","M1":"0.0228836469539","M2":"0.407163253339"}}
#--------------------
# Species
#	Species_Name: white spruce
#	Species_Code: PCGL
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# 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
1734	1.034
1735	0.736
1736	1.068
1737	1.037
1738	1.024
1739	1.288
1740	0.974
1741	0.874
1742	0.674
1743	1.139
1744	0.667
1745	0.805
1746	1.012
1747	0.988
1748	1.261
1749	1.497
1750	1.542
1751	0.865
1752	1.409
1753	1.099
1754	1.248
1755	1.113
1756	1.083
1757	0.968
1758	1.098
1759	1.042
1760	1.184
1761	1.353
1762	1.249
1763	1.142
1764	1.251
1765	1.041
1766	1.235
1767	1.092
1768	1.267
1769	1.115
1770	1.286
1771	0.797
1772	0.732
1773	0.652
1774	1.026
1775	0.727
1776	0.771
1777	0.586
1778	0.54
1779	0.712
1780	0.393
1781	0.755
1782	0.525
1783	0.509
1784	0.599
1785	0.6
1786	0.589
1787	0.769
1788	0.607
1789	0.661
1790	0.888
1791	1.018
1792	1.138
1793	0.897
1794	1.296
1795	1.195
1796	1.107
1797	0.858
1798	0.913
1799	0.807
1800	0.686
1801	0.743
1802	0.812
1803	1.054
1804	0.734
1805	0.78
1806	0.867
1807	0.767
1808	1.042
1809	0.632
1810	0.774
1811	0.75
1812	0.753
1813	0.795
1814	0.615
1815	0.605
1816	0.408
1817	0.93
1818	0.82
1819	0.925
1820	0.941
1821	0.94
1822	0.734
1823	0.865
1824	0.866
1825	1.044
1826	0.672
1827	1.011
1828	0.893
1829	0.926
1830	0.922
1831	1.073
1832	0.965
1833	0.993
1834	0.885
1835	0.789
1836	0.624
1837	0.665
1838	0.794
1839	0.729
1840	0.7
1841	0.558
1842	0.651
1843	0.72
1844	0.791
1845	0.72
1846	0.803
1847	0.985
1848	1.04
1849	0.991
1850	0.971
1851	0.736
1852	1.098
1853	1.17
1854	1.214
1855	1.445
1856	1.056
1857	1.579
1858	1.516
1859	1.269
1860	1.454
1861	1.285
1862	1.009
1863	1.108
1864	1.272
1865	1.332
1866	1.049
1867	1.372
1868	1.052
1869	1.059
1870	1.007
1871	1.023
1872	1.129
1873	1.208
1874	1.506
1875	1.319
1876	1.385
1877	1.703
1878	1.838
1879	1.43
1880	1.602
1881	1.534
1882	1.673
1883	1.349
1884	1.563
1885	1.67
1886	1.424
1887	1.631
1888	1.426
1889	1.384
1890	1.459
1891	1.319
1892	1.297
1893	1.373
1894	1.301
1895	1.42
1896	1.104
1897	1.314
1898	1.408
1899	0.667
1900	1.373
1901	1.045
1902	1.227
1903	1.083
1904	0.883
1905	0.88
1906	1.137
1907	1.034
1908	1.095
1909	0.785
1910	0.767
1911	1.055
1912	0.534
1913	0.784
1914	0.761
1915	0.808
1916	0.796
1917	0.731
1918	0.923
1919	0.649
1920	1.135
1921	1.277
1922	0.652
1923	0.852
1924	0.654
1925	0.746
1926	0.9
1927	0.735
1928	0.712
1929	0.684
1930	0.574
1931	0.519
1932	0.75
1933	0.716
1934	0.742
1935	0.94
1936	0.907
1937	0.872
1938	0.572
1939	0.821
1940	0.488
1941	0.688
1942	0.915
1943	1.107
1944	0.978
1945	0.978
1946	1.044
1947	0.771
1948	1.0
1949	0.805
1950	0.803
1951	0.851
1952	1.137
1953	1.085
1954	0.951
1955	1.083
1956	1.082
1957	1.026
1958	1.126
1959	1.296
1960	1.248
1961	0.973
1962	0.971
1963	0.935
1964	1.074
1965	0.991
1966	1.132
1967	0.855
1968	0.687
1969	0.765
1970	0.913
1971	0.893
1972	0.683
1973	0.877
1974	0.872
1975	0.62
1976	0.597
1977	0.639
1978	0.403
1979	0.568
1980	0.569
1981	0.49
1982	0.699
1983	0.563
1984	0.782
1985	0.835
1986	0.763
1987	0.813
1988	0.917
1989	1.183
1990	1.362
1991	1.104
1992	1.083
1993	0.906
1994	0.914
1995	0.878
1996	0.889
1997	1.417
1998	1.197
1999	1.235
2000	1.141
2001	1.36
2002	1.016