ÃÂ¯ÃÂ»ÃÂ¿# africa_morc011 - Ifrane - 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/2933
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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: africa_morc011 - Ifrane - 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: Ifrane
#	Location:
#	Country: Morocco
#	Northernmost_Latitude: 33.45
#	Southernmost_Latitude: 33.45
#	Easternmost_Longitude: -5.03
#	Westernmost_Longitude: -5.03
#	Elevation: 1900 m
#--------------------
# Data_Collection
#	Collection_Name: africa_morc011B
#	Earliest_Year: 1549
#	Most_Recent_Year: 1984
#	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":"5.207968805","T2":"15.1806474718","M1":"0.0228746880197","M2":"0.335965490101"}} A negative exponential detrending approached 0, thus this dataset was alternately standardized using a 75% cutoff smoothing spline methodology in ARSTAN, following the methodology outlined in Breitenmoser 2014.
#--------------------
# Species
#	Species_Name: Atlantic cedar
#	Species_Code: CDAT
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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
1549	1.139
1550	0.829
1551	0.748
1552	0.7
1553	1.022
1554	1.095
1555	1.143
1556	1.352
1557	1
1558	0.923
1559	1.162
1560	0.887
1561	0.786
1562	0.97
1563	0.819
1564	0.764
1565	0.927
1566	1.003
1567	1.099
1568	1.4
1569	1.361
1570	1.276
1571	1.089
1572	1.245
1573	1.262
1574	1.08
1575	1.127
1576	1.111
1577	1.219
1578	1.259
1579	1.072
1580	0.777
1581	0.649
1582	0.38
1583	0.478
1584	0.626
1585	0.614
1586	0.526
1587	0.624
1588	0.769
1589	0.832
1590	0.961
1591	1.189
1592	1.155
1593	1.053
1594	1.726
1595	1.268
1596	1.239
1597	1.308
1598	1.27
1599	1.367
1600	0.997
1601	1.288
1602	1.46
1603	1.136
1604	1.392
1605	0.74
1606	0.654
1607	0.925
1608	0.86
1609	0.909
1610	0.79
1611	0.814
1612	1.085
1613	0.525
1614	0.64
1615	0.717
1616	0.812
1617	0.914
1618	0.893
1619	1.145
1620	1.156
1621	1.328
1622	1.099
1623	1.014
1624	1.146
1625	1.084
1626	0.995
1627	1.038
1628	0.907
1629	1.072
1630	0.89
1631	0.919
1632	0.971
1633	1.061
1634	1.137
1635	1.194
1636	1.222
1637	1.158
1638	0.955
1639	0.967
1640	1.019
1641	1.333
1642	1.203
1643	1.001
1644	1.233
1645	0.922
1646	1.105
1647	0.807
1648	0.538
1649	0.851
1650	0.982
1651	1.015
1652	1.184
1653	1.165
1654	1.132
1655	0.968
1656	0.964
1657	1.167
1658	1.037
1659	1.222
1660	1.002
1661	0.816
1662	0.919
1663	0.595
1664	0.629
1665	0.549
1666	0.955
1667	0.767
1668	0.779
1669	0.684
1670	0.759
1671	0.636
1672	0.486
1673	0.693
1674	0.817
1675	0.619
1676	0.551
1677	0.937
1678	0.827
1679	1.025
1680	0.682
1681	1.236
1682	0.952
1683	0.265
1684	0.794
1685	0.731
1686	0.802
1687	0.68
1688	0.67
1689	0.859
1690	0.928
1691	1.068
1692	1.022
1693	0.843
1694	0.775
1695	0.589
1696	0.519
1697	0.294
1698	0.426
1699	0.509
1700	0.546
1701	0.677
1702	0.811
1703	0.847
1704	0.981
1705	1.133
1706	1.1
1707	1.269
1708	1.44
1709	1.306
1710	1.413
1711	1.543
1712	1.108
1713	0.922
1714	1.269
1715	1.372
1716	1.102
1717	1.253
1718	1.271
1719	1.196
1720	1.197
1721	1.313
1722	1.561
1723	1.801
1724	1.547
1725	1.343
1726	1.509
1727	1.564
1728	1.022
1729	0.679
1730	0.565
1731	0.749
1732	0.909
1733	1.002
1734	0.125
1735	0.829
1736	0.571
1737	0.087
1738	0.243
1739	0.437
1740	0.555
1741	0.627
1742	0.582
1743	0.793
1744	0.761
1745	0.879
1746	0.852
1747	1.103
1748	1.093
1749	1.295
1750	0.864
1751	1.169
1752	1.18
1753	0.929
1754	0.977
1755	0.964
1756	1.022
1757	1.261
1758	1.228
1759	1.06
1760	1.256
1761	1.225
1762	1.447
1763	1.369
1764	1.192
1765	1.189
1766	1.007
1767	1.244
1768	1.176
1769	1.086
1770	1.197
1771	1.214
1772	1.12
1773	1.44
1774	1.386
1775	1.539
1776	1.385
1777	1.244
1778	1.205
1779	0.692
1780	0.911
1781	0.984
1782	0.937
1783	1.176
1784	1.15
1785	1.201
1786	1.223
1787	1.205
1788	1.349
1789	1.098
1790	1.224
1791	1.314
1792	0.547
1793	0.495
1794	0.419
1795	0.561
1796	0.444
1797	0.61
1798	0.81
1799	0.885
1800	0.502
1801	0.299
1802	0.335
1803	0.417
1804	0.634
1805	0.756
1806	0.594
1807	0.616
1808	0.711
1809	1.088
1810	1.069
1811	1.197
1812	0.831
1813	0.729
1814	1.002
1815	1.212
1816	0.791
1817	0.373
1818	0.694
1819	0.76
1820	0.654
1821	0.759
1822	0.819
1823	0.906
1824	0.846
1825	0.691
1826	1.04
1827	1.038
1828	1.05
1829	0.916
1830	0.907
1831	1
1832	0.968
1833	1.062
1834	1.199
1835	1.353
1836	0.955
1837	1.179
1838	1.11
1839	0.982
1840	1.054
1841	1.093
1842	0.988
1843	1.106
1844	0.961
1845	1.033
1846	1.345
1847	1.05
1848	1.022
1849	1.367
1850	1.151
1851	1.15
1852	1.167
1853	1.289
1854	1.262
1855	1.225
1856	1.341
1857	1.02
1858	0.76
1859	0.895
1860	1.051
1861	1.139
1862	0.958
1863	0.886
1864	0.966
1865	0.762
1866	0.85
1867	0.999
1868	1.022
1869	1.238
1870	1.075
1871	1.212
1872	1.177
1873	1.335
1874	1.037
1875	1.124
1876	1.301
1877	1.42
1878	0.5
1879	0.678
1880	0.779
1881	0.776
1882	0.443
1883	0.741
1884	0.867
1885	0.908
1886	0.894
1887	0.739
1888	0.916
1889	0.934
1890	0.895
1891	1.144
1892	1.054
1893	1.143
1894	1.043
1895	1.038
1896	0.815
1897	0.808
1898	0.789
1899	0.911
1900	0.979
1901	1.017
1902	0.933
1903	0.905
1904	0.467
1905	0.612
1906	0.609
1907	0.76
1908	1.013
1909	0.979
1910	0.956
1911	0.92
1912	1.09
1913	1.096
1914	0.942
1915	0.943
1916	0.89
1917	0.881
1918	0.778
1919	1.005
1920	0.813
1921	0.841
1922	0.942
1923	0.853
1924	0.728
1925	0.849
1926	0.975
1927	0.681
1928	0.778
1929	1.073
1930	1.305
1931	0.771
1932	0.934
1933	0.925
1934	0.782
1935	1.112
1936	1.274
1937	1.268
1938	1.237
1939	1.208
1940	1.153
1941	1.245
1942	1.185
1943	1.51
1944	2.086
1945	0.879
1946	1.572
1947	1.618
1948	1.454
1949	0.546
1950	0.918
1951	1.081
1952	1.099
1953	0.003
1954	0.42
1955	0.499
1956	0.545
1957	0.575
1958	0.611
1959	0.702
1960	0.86
1961	0.632
1962	0.923
1963	1.05
1964	1.149
1965	0.949
1966	0.997
1967	1.101
1968	1.074
1969	1.173
1970	1.092
1971	1.005
1972	0.894
1973	1.21
1974	0.888
1975	1.136
1976	1.112
1977	1.227
1978	1.516
1979	1.075
1980	1.102
1981	0.917
1982	0.993
1983	0.757
1984	0.791