# northamerica_mexico_mexi032 - Mesa de Campanero - 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/4899
#
# Description/Documentation lines begin with #
# Data lines have no #
#
# Archive: Tree Rings
#--------------------
# Contribution_Date
#	Date: 2016-01-07
#--------------------
# Title
#	Study_Name: northamerica_mexico_mexi032 - Mesa de Campanero - 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.
#------------------
# 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: Mesa de Campanero
#	Location:
#	Country: Mexico
#	Northernmost_Latitude: 28.33
#	Southernmost_Latitude: 28.33
#	Easternmost_Longitude: -109.05
#	Westernmost_Longitude: -109.05
#	Elevation: 2160 m
#--------------------
# Data_Collection
#	Collection_Name: northamerica_mexico_mexi032B
#	Earliest_Year: 1834
#	Most_Recent_Year: 1993
#	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":"4.74554715412","T2":"15.046433845","M1":"0.0227374073892","M2":"0.322715196286"}}
#--------------------
# Species
#	Species_Name: fir
#	Species_Code: ABSP
#--------------------
# 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
1834	1.361
1835	1.362
1836	1.031
1837	1.132
1838	0.865
1839	1.241
1840	0.842
1841	0.696
1842	0.921
1843	1.127
1844	1.163
1845	0.979
1846	1.067
1847	0.738
1848	0.993
1849	1.039
1850	1.232
1851	0.966
1852	1.096
1853	1.017
1854	0.897
1855	0.623
1856	0.833
1857	0.478
1858	1.119
1859	0.781
1860	0.795
1861	0.918
1862	0.723
1863	1.091
1864	0.812
1865	1.06
1866	0.672
1867	0.94
1868	0.996
1869	1.098
1870	0.868
1871	0.73
1872	0.702
1873	0.911
1874	0.952
1875	0.799
1876	0.819
1877	0.984
1878	0.869
1879	0.932
1880	0.731
1881	0.843
1882	0.821
1883	0.958
1884	0.842
1885	1.052
1886	1.12
1887	0.497
1888	1.375
1889	1.503
1890	0.711
1891	1.49
1892	1.064
1893	0.722
1894	0.554
1895	0.84
1896	0.957
1897	1.041
1898	1.099
1899	0.861
1900	1.165
1901	1.059
1902	0.725
1903	1.182
1904	0.41
1905	0.998
1906	0.962
1907	1.21
1908	1.319
1909	0.799
1910	0.799
1911	0.654
1912	1.082
1913	1.363
1914	1.128
1915	1.284
1916	1.041
1917	1.199
1918	1.331
1919	1.059
1920	1.299
1921	0.686
1922	0.889
1923	0.885
1924	1.094
1925	0.722
1926	1.087
1927	1.117
1928	1.055
1929	0.857
1930	1.278
1931	1.535
1932	1.456
1933	1.094
1934	0.709
1935	0.827
1936	0.821
1937	0.877
1938	0.697
1939	0.55
1940	0.89
1941	0.951
1942	1.049
1943	0.773
1944	0.937
1945	0.683
1946	0.72
1947	0.74
1948	1.112
1949	1.086
1950	0.869
1951	0.793
1952	1.089
1953	0.983
1954	0.636
1955	0.675
1956	0.684
1957	1.617
1958	1.454
1959	1.155
1960	1.252
1961	1.097
1962	1.178
1963	0.792
1964	1.009
1965	0.895
1966	1.079
1967	0.631
1968	0.97
1969	0.969
1970	1.116
1971	0.579
1972	0.826
1973	1.133
1974	0.673
1975	0.871
1976	0.695
1977	1.039
1978	0.817
1979	1.12
1980	0.727
1981	0.982
1982	0.587
1983	1.12
1984	0.787
1985	1.091
1986	0.963
1987	0.78
1988	0.69
1989	0.525
1990	0.586
1991	1.337
1992	1.492
1993	1.661