# northamerica_usa_ca524 - Grizzly Peak - 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
#
# Original_Source_URL:https://www.ncdc.noaa.gov/paleo/study/3316
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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_ca524 - Grizzly Peak - 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
#------------------
# Site_Information
#	Site_Name: Grizzly Peak
#	Location:
#	Country: United States
#	Northernmost_Latitude: 41.17
#	Southernmost_Latitude: 41.17
#	Easternmost_Longitude: -122.03
#	Westernmost_Longitude: -122.03
#	Elevation: 1463 m
#--------------------
# Data_Collection
#	Collection_Name: northamerica_usa_ca524B
#	Earliest_Year: 1686
#	Most_Recent_Year: 1980
#	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":"3.61594828743","T2":"14.6136111759","M1":"0.0228090452823","M2":"0.458125765224"}}
#--------------------
# Species
#	Species_Name: ponderosa pine
#	Species_Code: PIPO
#--------------------
# 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
1686	0.871
1687	0.852
1688	0.801
1689	0.875
1690	0.939
1691	0.88
1692	0.792
1693	0.74
1694	0.759
1695	0.966
1696	0.837
1697	1.096
1698	0.975
1699	0.938
1700	0.961
1701	0.74
1702	1.222
1703	0.821
1704	1.027
1705	1.123
1706	0.904
1707	0.941
1708	1.091
1709	0.797
1710	1.041
1711	0.791
1712	1.019
1713	0.917
1714	0.743
1715	1.049
1716	1.174
1717	1.18
1718	0.919
1719	1.079
1720	0.996
1721	1.146
1722	1.175
1723	1.268
1724	0.897
1725	0.952
1726	1.374
1727	1.231
1728	1.175
1729	0.975
1730	1.188
1731	1.242
1732	1.259
1733	1.163
1734	0.955
1735	0.945
1736	0.976
1737	1.048
1738	1.294
1739	1.045
1740	1.017
1741	0.902
1742	0.942
1743	0.818
1744	1.014
1745	1.057
1746	1.074
1747	1.013
1748	0.862
1749	1.061
1750	1.029
1751	1.009
1752	1.169
1753	0.827
1754	0.915
1755	1.358
1756	0.722
1757	0.661
1758	1.048
1759	0.915
1760	0.904
1761	1.232
1762	1.097
1763	0.961
1764	0.837
1765	1.072
1766	0.98
1767	0.95
1768	1.043
1769	0.858
1770	1.083
1771	0.711
1772	1.061
1773	0.896
1774	0.859
1775	0.909
1776	0.914
1777	0.763
1778	0.816
1779	0.825
1780	1.094
1781	0.763
1782	1.069
1783	0.809
1784	0.832
1785	0.997
1786	1.027
1787	0.752
1788	0.926
1789	0.772
1790	0.833
1791	1.313
1792	1.039
1793	1.287
1794	0.927
1795	0.868
1796	0.792
1797	0.894
1798	0.812
1799	0.864
1800	0.831
1801	0.761
1802	0.894
1803	1.019
1804	1.133
1805	0.996
1806	1.031
1807	1.046
1808	1.09
1809	1.23
1810	1.101
1811	1.119
1812	1.331
1813	1.189
1814	1.481
1815	1.17
1816	1.05
1817	0.825
1818	1.093
1819	1.196
1820	0.935
1821	0.851
1822	1.007
1823	0.696
1824	0.934
1825	1.059
1826	0.96
1827	0.996
1828	1.078
1829	0.995
1830	0.726
1831	0.791
1832	1.133
1833	0.821
1834	0.694
1835	1.044
1836	1.045
1837	1.194
1838	1.234
1839	1.105
1840	1.033
1841	1.098
1842	0.913
1843	0.888
1844	0.918
1845	0.917
1846	1.085
1847	0.824
1848	0.916
1849	0.855
1850	0.837
1851	0.963
1852	1.03
1853	0.932
1854	0.92
1855	1.069
1856	0.957
1857	1.013
1858	0.716
1859	0.485
1860	0.959
1861	1.122
1862	0.741
1863	1.025
1864	0.961
1865	0.679
1866	1.117
1867	1.102
1868	1.199
1869	1.176
1870	1.04
1871	0.999
1872	0.934
1873	1.037
1874	0.911
1875	1.088
1876	0.826
1877	1.25
1878	0.893
1879	1.19
1880	0.935
1881	1.141
1882	0.839
1883	0.878
1884	1.217
1885	1.476
1886	0.948
1887	0.85
1888	0.89
1889	0.761
1890	0.596
1891	0.704
1892	1.0
1893	0.931
1894	0.902
1895	1.044
1896	1.168
1897	1.181
1898	0.958
1899	1.046
1900	1.639
1901	1.486
1902	1.323
1903	1.266
1904	1.038
1905	0.933
1906	0.954
1907	1.372
1908	1.185
1909	1.012
1910	0.938
1911	0.84
1912	1.114
1913	1.31
1914	1.331
1915	1.576
1916	1.406
1917	1.109
1918	1.153
1919	1.215
1920	1.089
1921	1.167
1922	0.893
1923	1.077
1924	0.8
1925	0.866
1926	1.351
1927	0.947
1928	0.934
1929	0.826
1930	0.98
1931	1.134
1932	0.783
1933	0.785
1934	1.173
1935	0.677
1936	0.577
1937	0.485
1938	0.783
1939	0.722
1940	0.681
1941	1.047
1942	1.109
1943	1.008
1944	0.951
1945	1.019
1946	1.079
1947	1.16
1948	0.872
1949	0.894
1950	0.664
1951	1.043
1952	0.769
1953	0.72
1954	1.043
1955	0.793
1956	0.732
1957	0.999
1958	1.16
1959	0.899
1960	1.037
1961	1.149
1962	1.104
1963	1.443
1964	1.287
1965	1.085
1966	0.969
1967	0.675
1968	0.912
1969	0.943
1970	0.681
1971	0.822
1972	0.971
1973	0.833
1974	0.848
1975	0.945
1976	0.974
1977	0.616
1978	0.777
1979	0.799
1980	0.925