# northamerica_usa_or030 - Grizzly Bear - 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/5080
#
# 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_or030 - Grizzly Bear - 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.
#------------------
# 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 Bear
#	Location:
#	Country: United States
#	Northernmost_Latitude: 45.97
#	Southernmost_Latitude: 45.97
#	Easternmost_Longitude: -117.72
#	Westernmost_Longitude: -117.72
#	Elevation: 1231 m
#--------------------
# Data_Collection
#	Collection_Name: northamerica_usa_or030B
#	Earliest_Year: 1612
#	Most_Recent_Year: 1991
#	Time_Unit: y_ad
#	Core_Length:
#	Notes: {"database":{"database1":"LMR","database2":"Breits"}} {"climateInterpretation":{"basis":"", "climateVariable":"M", "climateVariableDetail":"air", "interpDirection":"positive", "seasonality":"[6, 7, 8]"}}{"VSLite_parameters":{"T1":"4.61977646879","T2":"15.0149334823","M1":"0.0230594164185","M2":"0.514891209705"}}
#--------------------
# Species
#	Species_Name: ponderosa pine
#	Species_Code: PIPO
#--------------------
# Chronology:
#
#
#
#--------------------
# 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
1612	1.224
1613	1.255
1614	1.009
1615	1.06
1616	1.103
1617	1.239
1618	1.152
1619	0.789
1620	0.845
1621	0.916
1622	0.878
1623	0.535
1624	0.761
1625	0.877
1626	0.652
1627	0.83
1628	0.618
1629	0.58
1630	0.68
1631	0.778
1632	0.718
1633	0.876
1634	0.47
1635	0.611
1636	0.693
1637	0.742
1638	0.717
1639	0.71
1640	0.804
1641	1.064
1642	1.011
1643	0.851
1644	0.993
1645	1.024
1646	0.872
1647	0.56
1648	0.979
1649	0.72
1650	0.757
1651	0.462
1652	0.528
1653	0.769
1654	0.879
1655	0.726
1656	1.041
1657	0.628
1658	1.162
1659	1.044
1660	0.999
1661	0.926
1662	0.945
1663	0.944
1664	0.888
1665	0.706
1666	1.034
1667	1.123
1668	0.895
1669	1.217
1670	1.26
1671	1.006
1672	1.052
1673	1.054
1674	0.929
1675	0.951
1676	0.817
1677	0.732
1678	0.919
1679	1.048
1680	0.946
1681	1.207
1682	0.96
1683	0.897
1684	1.04
1685	1.166
1686	1.049
1687	1.191
1688	1.235
1689	1.183
1690	1.156
1691	1.249
1692	1.331
1693	1.226
1694	1.264
1695	1.025
1696	1.105
1697	1.278
1698	1.061
1699	1.19
1700	1.23
1701	1.074
1702	1.328
1703	1.418
1704	1.175
1705	1.197
1706	1.241
1707	1.455
1708	0.887
1709	0.999
1710	1.004
1711	1.179
1712	1.172
1713	1.226
1714	0.992
1715	1.427
1716	1.348
1717	0.79
1718	0.772
1719	0.958
1720	0.931
1721	0.436
1722	0.896
1723	0.914
1724	0.956
1725	0.966
1726	1.115
1727	1.287
1728	0.895
1729	0.802
1730	1.071
1731	1.074
1732	1.026
1733	1.329
1734	1.141
1735	0.99
1736	0.868
1737	0.874
1738	1.05
1739	0.663
1740	0.602
1741	0.74
1742	0.99
1743	0.948
1744	0.88
1745	1.094
1746	1.111
1747	0.937
1748	0.799
1749	0.918
1750	1.301
1751	1.136
1752	0.963
1753	0.837
1754	0.728
1755	1.0
1756	0.597
1757	0.518
1758	0.726
1759	0.699
1760	0.656
1761	1.226
1762	1.174
1763	0.991
1764	0.813
1765	1.061
1766	1.041
1767	1.051
1768	0.99
1769	1.002
1770	1.128
1771	1.047
1772	0.994
1773	1.206
1774	1.076
1775	1.171
1776	0.975
1777	0.902
1778	1.077
1779	1.146
1780	1.087
1781	1.03
1782	1.081
1783	0.726
1784	0.711
1785	0.908
1786	0.976
1787	0.706
1788	1.038
1789	1.175
1790	0.978
1791	0.983
1792	1.134
1793	1.056
1794	0.946
1795	1.121
1796	1.09
1797	0.514
1798	0.567
1799	0.982
1800	0.702
1801	0.909
1802	1.128
1803	1.03
1804	0.845
1805	0.992
1806	1.091
1807	0.801
1808	0.901
1809	1.104
1810	1.047
1811	1.031
1812	1.354
1813	1.104
1814	1.346
1815	1.113
1816	1.09
1817	0.983
1818	1.163
1819	1.252
1820	1.044
1821	1.001
1822	1.159
1823	0.674
1824	0.974
1825	1.004
1826	0.914
1827	1.075
1828	1.052
1829	1.172
1830	0.947
1831	0.943
1832	1.277
1833	1.351
1834	1.003
1835	0.893
1836	1.078
1837	1.033
1838	1.138
1839	0.476
1840	0.608
1841	0.898
1842	0.871
1843	0.911
1844	0.826
1845	1.131
1846	0.902
1847	0.814
1848	0.811
1849	0.661
1850	0.842
1851	0.849
1852	0.765
1853	1.014
1854	0.966
1855	1.11
1856	1.031
1857	1.147
1858	1.215
1859	0.989
1860	1.166
1861	1.385
1862	1.189
1863	1.129
1864	1.209
1865	1.061
1866	1.334
1867	1.098
1868	0.903
1869	0.814
1870	0.991
1871	1.005
1872	0.877
1873	1.115
1874	0.986
1875	1.07
1876	1.275
1877	1.684
1878	1.415
1879	1.318
1880	1.162
1881	1.496
1882	1.21
1883	0.931
1884	1.036
1885	1.312
1886	0.84
1887	0.969
1888	1.096
1889	0.745
1890	0.61
1891	0.835
1892	0.821
1893	0.69
1894	1.104
1895	1.051
1896	0.796
1897	0.954
1898	0.815
1899	0.615
1900	1.11
1901	1.152
1902	0.899
1903	0.923
1904	1.245
1905	0.652
1906	0.748
1907	1.105
1908	1.122
1909	0.903
1910	0.978
1911	0.838
1912	0.934
1913	1.519
1914	1.32
1915	1.014
1916	1.235
1917	1.051
1918	0.83
1919	1.085
1920	0.932
1921	1.258
1922	1.008
1923	0.831
1924	0.899
1925	0.838
1926	0.807
1927	0.991
1928	1.225
1929	0.744
1930	0.652
1931	0.75
1932	0.758
1933	0.61
1934	0.899
1935	0.705
1936	0.587
1937	0.824
1938	0.967
1939	0.898
1940	0.731
1941	0.893
1942	1.618
1943	1.217
1944	0.693
1945	0.896
1946	1.231
1947	1.268
1948	0.765
1949	0.821
1950	1.01
1951	1.073
1952	1.113
1953	0.864
1954	1.016
1955	1.14
1956	1.23
1957	1.299
1958	0.907
1959	1.171
1960	1.515
1961	1.155
1962	1.136
1963	1.052
1964	0.767
1965	0.954
1966	0.923
1967	0.633
1968	0.643
1969	1.023
1970	0.76
1971	0.756
1972	0.872
1973	0.643
1974	0.656
1975	0.934
1976	1.306
1977	0.502
1978	1.087
1979	1.119
1980	1.178
1981	1.292
1982	1.129
1983	1.396
1984	1.202
1985	0.846
1986	1.191
1987	0.965
1988	0.674
1989	0.539
1990	1.19
1991	0.901