# northamerica_mexico_mexi025 - Creel International Airport - 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.
#
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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/4835
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# Description/Documentation lines begin with #
# Data lines have no #
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# Archive: Tree Rings
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# Contribution_Date
#	Date: 2016-01-07
#--------------------
# Title
#	Study_Name: northamerica_mexico_mexi025 - Creel International Airport - 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: Creel International Airport
#	Location:
#	Country: Mexico
#	Northernmost_Latitude: 27.7
#	Southernmost_Latitude: 27.7
#	Easternmost_Longitude: -107.62
#	Westernmost_Longitude: -107.62
#	Elevation: 2200 m
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# Data_Collection
#	Collection_Name: northamerica_mexico_mexi025B
#	Earliest_Year: 1741
#	Most_Recent_Year: 1993
#	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":"3.40592644397","T2":"14.6568847775","M1":"0.0232137148628","M2":"0.529587135155"}}
#--------------------
# Species
#	Species_Name: Douglas fir
#	Species_Code: PSME
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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
#
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# Data:
# Data lines follow (have no #)
# Data line format - tab-delimited text, variable short name as header
# Missing Values: nan
#
age	trsgi
1741	1.086
1742	0.564
1743	1.005
1744	1.136
1745	0.92
1746	1.321
1747	1.314
1748	0.856
1749	1.228
1750	1.118
1751	1.022
1752	0.711
1753	0.713
1754	0.772
1755	0.715
1756	1.051
1757	0.873
1758	0.706
1759	0.792
1760	0.679
1761	0.705
1762	0.702
1763	0.458
1764	0.844
1765	0.805
1766	0.747
1767	0.806
1768	0.722
1769	1.151
1770	1.138
1771	1.038
1772	0.603
1773	0.76
1774	0.903
1775	0.89
1776	0.995
1777	1.022
1778	0.933
1779	1.089
1780	1.005
1781	0.96
1782	0.944
1783	0.877
1784	1.173
1785	0.644
1786	0.865
1787	0.827
1788	1.008
1789	0.748
1790	0.764
1791	1.233
1792	1.197
1793	1.275
1794	1.112
1795	1.172
1796	1.494
1797	0.971
1798	0.77
1799	0.956
1800	1.156
1801	0.706
1802	0.943
1803	0.98
1804	0.991
1805	0.732
1806	1.018
1807	1.053
1808	0.769
1809	0.895
1810	0.97
1811	0.985
1812	0.847
1813	1.17
1814	1.139
1815	1.211
1816	1.458
1817	1.182
1818	1.254
1819	0.893
1820	0.649
1821	0.852
1822	0.997
1823	1.25
1824	1.104
1825	1.198
1826	0.903
1827	1.333
1828	1.083
1829	1.297
1830	1.113
1831	0.73
1832	0.751
1833	1.172
1834	1.004
1835	0.996
1836	1.103
1837	1.023
1838	0.872
1839	1.144
1840	0.779
1841	0.816
1842	0.852
1843	0.985
1844	1.179
1845	1.093
1846	1.01
1847	0.892
1848	1.071
1849	1.049
1850	1.112
1851	0.988
1852	1.282
1853	1.112
1854	0.7
1855	0.669
1856	1.172
1857	0.82
1858	1.2
1859	0.994
1860	0.625
1861	1.136
1862	0.76
1863	0.807
1864	0.978
1865	1.002
1866	1.102
1867	1.098
1868	1.103
1869	1.487
1870	1.172
1871	1.107
1872	1.196
1873	1.12
1874	1.016
1875	1.165
1876	0.903
1877	0.923
1878	0.823
1879	0.881
1880	0.684
1881	1.131
1882	1.118
1883	1.085
1884	0.978
1885	1.224
1886	1.017
1887	0.661
1888	1.346
1889	1.34
1890	1.093
1891	0.888
1892	0.711
1893	0.356
1894	0.684
1895	1.101
1896	1.029
1897	1.077
1898	1.086
1899	0.866
1900	1.177
1901	1.055
1902	0.745
1903	1.359
1904	0.652
1905	1.433
1906	1.254
1907	0.968
1908	0.956
1909	0.904
1910	0.565
1911	0.773
1912	0.89
1913	1.029
1914	1.018
1915	1.007
1916	0.783
1917	0.825
1918	0.799
1919	1.159
1920	1.138
1921	0.79
1922	0.953
1923	0.893
1924	1.318
1925	0.863
1926	1.406
1927	1.014
1928	1.413
1929	0.757
1930	1.077
1931	1.105
1932	1.055
1933	1.289
1934	0.725
1935	1.039
1936	0.834
1937	0.793
1938	1.066
1939	0.67
1940	1.006
1941	0.945
1942	1.026
1943	0.74
1944	1.316
1945	0.813
1946	0.675
1947	1.206
1948	0.844
1949	1.087
1950	0.956
1951	0.487
1952	1.066
1953	0.728
1954	0.43
1955	0.784
1956	0.645
1957	0.7
1958	0.955
1959	0.806
1960	0.94
1961	0.901
1962	0.975
1963	0.796
1964	1.019
1965	0.871
1966	1.098
1967	0.917
1968	1.456
1969	1.084
1970	1.16
1971	0.948
1972	1.233
1973	1.476
1974	0.676
1975	1.297
1976	0.737
1977	1.094
1978	0.535
1979	1.338
1980	0.351
1981	1.379
1982	0.522
1983	1.201
1984	1.061
1985	1.339
1986	0.818
1987	1.355
1988	0.946
1989	0.981
1990	0.959
1991	1.047
1992	1.387
1993	1.084