# northamerica_usa_wa014 - Windy Meadows - 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:
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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/2918
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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_wa014 - Windy Meadows - 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: Windy Meadows
#	Location:
#	Country: United States
#	Northernmost_Latitude: 45.32
#	Southernmost_Latitude: 45.32
#	Easternmost_Longitude: -118.8
#	Westernmost_Longitude: -118.8
#	Elevation: 1071 m
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# Data_Collection
#	Collection_Name: northamerica_usa_wa014B
#	Earliest_Year: 1684
#	Most_Recent_Year: 1975
#	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":"3.50010191062","T2":"15.4379034029","M1":"0.0220740428915","M2":"0.527533396349"}}
#--------------------
# Species
#	Species_Name: ponderosa pine
#	Species_Code: PIPO
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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
1684	1.182
1685	1.1
1686	1.415
1687	1.21
1688	0.974
1689	0.728
1690	0.885
1691	0.924
1692	1.153
1693	1.596
1694	1.036
1695	1.522
1696	1.274
1697	1.072
1698	0.797
1699	1.075
1700	1.079
1701	0.855
1702	1.087
1703	1.176
1704	1.33
1705	0.971
1706	0.658
1707	0.901
1708	0.595
1709	0.654
1710	1.117
1711	0.999
1712	1.255
1713	0.863
1714	1.015
1715	1.357
1716	1.377
1717	0.826
1718	0.705
1719	0.618
1720	0.825
1721	0.757
1722	0.769
1723	1.106
1724	0.878
1725	0.74
1726	1.072
1727	1.339
1728	0.878
1729	1.373
1730	1.247
1731	1.315
1732	1.514
1733	1.394
1734	0.943
1735	1.26
1736	0.87
1737	0.995
1738	1.459
1739	1.455
1740	0.837
1741	0.672
1742	0.877
1743	0.989
1744	0.937
1745	1.11
1746	1.067
1747	0.912
1748	0.882
1749	0.951
1750	1.607
1751	1.374
1752	1.159
1753	0.917
1754	0.678
1755	1.143
1756	0.64
1757	0.581
1758	0.774
1759	0.617
1760	0.867
1761	1.308
1762	1.048
1763	1.272
1764	0.839
1765	0.989
1766	1.321
1767	1.16
1768	0.885
1769	0.918
1770	1.221
1771	0.91
1772	0.889
1773	1.282
1774	0.997
1775	1.151
1776	0.827
1777	0.694
1778	0.844
1779	0.886
1780	0.82
1781	0.839
1782	0.184
1783	0.612
1784	0.585
1785	0.652
1786	0.665
1787	0.476
1788	0.718
1789	1.049
1790	0.88
1791	1.284
1792	0.775
1793	0.949
1794	0.822
1795	0.683
1796	0.746
1797	0.378
1798	0.597
1799	0.91
1800	0.838
1801	0.752
1802	0.832
1803	0.894
1804	0.77
1805	0.901
1806	0.726
1807	0.587
1808	0.698
1809	0.99
1810	0.877
1811	0.917
1812	1.116
1813	0.994
1814	1.215
1815	0.963
1816	1.028
1817	0.851
1818	0.936
1819	0.994
1820	0.612
1821	0.893
1822	1.074
1823	0.763
1824	0.945
1825	1.337
1826	1.138
1827	0.801
1828	1.056
1829	0.932
1830	0.746
1831	0.49
1832	0.737
1833	0.91
1834	0.867
1835	0.639
1836	0.666
1837	0.854
1838	1.166
1839	0.976
1840	0.575
1841	0.732
1842	0.807
1843	0.621
1844	0.577
1845	0.878
1846	0.66
1847	0.551
1848	0.628
1849	0.66
1850	0.521
1851	0.844
1852	0.703
1853	0.69
1854	0.803
1855	1.252
1856	1.017
1857	1.028
1858	1.162
1859	0.823
1860	0.749
1861	0.89
1862	0.843
1863	0.848
1864	0.758
1865	0.648
1866	0.583
1867	0.585
1868	0.841
1869	0.647
1870	0.603
1871	0.551
1872	0.474
1873	0.604
1874	0.597
1875	0.669
1876	0.747
1877	1.198
1878	1.108
1879	0.811
1880	0.69
1881	1.01
1882	0.737
1883	0.539
1884	0.508
1885	1.225
1886	0.654
1887	0.725
1888	1.234
1889	0.976
1890	0.78
1891	1.338
1892	1.476
1893	1.186
1894	1.694
1895	1.535
1896	1.437
1897	1.428
1898	1.665
1899	1.155
1900	1.998
1901	1.981
1902	1.583
1903	1.737
1904	1.77
1905	1.258
1906	1.814
1907	1.997
1908	2.1
1909	1.15
1910	1.474
1911	1.42
1912	1.625
1913	2.07
1914	1.701
1915	1.955
1916	2.024
1917	1.331
1918	1.173
1919	1.478
1920	0.882
1921	1.261
1922	1.038
1923	1.228
1924	1.258
1925	1.315
1926	1.287
1927	1.386
1928	1.269
1929	0.87
1930	0.634
1931	0.833
1932	0.775
1933	0.564
1934	1.065
1935	0.812
1936	0.723
1937	0.906
1938	1.162
1939	1.034
1940	0.798
1941	1.374
1942	1.694
1943	0.944
1944	1.006
1945	0.824
1946	1.148
1947	1.42
1948	1.106
1949	0.829
1950	0.891
1951	0.881
1952	1.016
1953	0.933
1954	1.082
1955	1.131
1956	1.033
1957	0.992
1958	0.772
1959	0.651
1960	0.866
1961	0.65
1962	0.511
1963	0.626
1964	0.633
1965	0.811
1966	1.038
1967	0.629
1968	0.461
1969	0.916
1970	0.843
1971	0.858
1972	0.62
1973	0.39
1974	0.297
1975	0.248