A new method for reconstructing past-climate trends using tree-ring data and kernel smoothing |
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| Affiliation: | 1. Departamento de Estratigrafía y Paleontología, Facultad de Ciencias, Universidad de Granada. Campus Fuentenueva s/n, 18002, Granada, Spain;2. Instituto Geológico y Minero de España (IGME), Ríos Rosas, 23, 28003, Madrid, Spain;3. Faculty of Engineering, Computer and Mathematical Sciences, The University of Adelaide, Australia;1. Climate Change Institute, University of Maine, USA;2. Department of Earth and Atmospheric Sciences, Metropolitan State University of Denver, USA;3. Department of Geography, and the Polar Center, Pennsylvania State University, USA;1. School of Geography and Geosciences, University of St Andrews, Fife, KY16 9AL, UK;2. Lamont-Doherty Earth Observatory of Columbia University, Palisades, New York, 10964, USA;3. The Roslin Institute, University of Edinburgh, Midlothian, EH25 9RG, UK;4. AOC Archaeology Group, Edinburgh, UK;5. Department of Geography, University of Cambridge, Cambridge, UK;6. Swiss Federal Research Institute WSL, Birmensdorf, Switzerland;7. Global Change Research Centre AS CR, Brno, Czechia;8. Department of Environmental Studies, University of Richmond, USA;9. Earth and Environmental Sciences, University of Michigan, USA;10. Department of Earth Sciences, University of Gothenburg, SE-40530, Gothenburg, Sweden;11. Department of Physical Geography, Stockholm University, SE-106 91, Stockholm, Sweden;12. Institute of Geography, University of Innsbruck, Innrain 52, 6020, Innsbruck, Austria;1. Laboratory of Silviculture, Dendrochronology and Climate Change, Department of Forestry Engineering, University of Cordoba. Edf. Leonardo da Vinci, Campus de Rabanales, 14075 Córdoba, Spain;2. Laboratory of Plant Physiology and Soil Culture, Faculty of Nature and Life Sciences, Ibn Khaldoun University, PO Box 80 Zaaroura, Tiaret, Theniet El Had, Tissemsilt, 38200, Algeria;3. Instituto Pirenaico de Ecología (IPE-CSIC), Avda. Montañana 1005, 50192, Zaragoza, Spain;4. Laboratory of Plant Ecology and Environment, Faculty of Biological Sciences, University of Science and Technology HouariBoumediene (USTHB), BP 32 El Alia, Bab Ezzouar, Alger, Algeria;1. Department of Geography, University of Georgia, Athens, GA, 30602, USA;2. Department of Geography, University of Tennessee, Knoxville, TN, 37996, USA;1. National Institute for Research and Development in Forestry "Marin Drăcea", Calea Bucovinei, 73 bis, 725100, Câmpulung Moldovenesc, Romania;2. Icelandic Forest Research, Mógilsá, IS-162 Reykjavík, Iceland;3. Department of Geography, Universităţii 13, 720229, Ștefan cel Mare University of Suceava, Romania;1. AGH University of Science and Technology, A. Mickiewicza Ave. 30, 30-059, Kraków, Poland;2. Institute of Nature Conservation, Polish Academy of Sciences, A. Mickiewicza Ave. 33, 31-120, Kraków, Poland;3. Kazimierza Wielkiego Str. 110/2-3, 30-074, Kraków, Poland;4. W. Szafer Institute of Botany, Polish Academy of Sciences, Lubicz Str. 46, 31-512, Kraków, Poland;5. Pedagogical University, Institute of Geography, Podchorążych Str. 2, 30-084, Kraków, Poland |
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| Abstract: | Mediterranean high-relief karst areas are very vulnerable to changes in temporal patterns of precipitation and temperature. Understanding climate change in these areas requires current climate trends to be assessed within the context of the variability of rainfall and temperature trends in the recent past. A major difficulty is that the instrumental record in these high-relief areas is very limited and the use of data from paleoclimatic proxies, such as tree-ring data, is required to infer past climate variability. Furthermore, for complex relationships between tree-ring data and climatic variables, it is almost impossible to infer past inter-annual variations in temperature or precipitation, and the inference is limited to the reconstruction of low-frequency variability (i.e., the trend). To do so, in this work, we propose a new method based on detecting trends (by kernel smoothing) in tree variables that show maximum correlation with the trends (also estimated by kernel smoothing) of climate variables. This enables a standard regression framework to be established to reconstruct past climate. We have used tree-ring proxy data from Abies pinsapo to evaluate past climate trends in the Sierra de las Nieves karst massif in Southern Spain. Our analysis has found that during the last three hundred years the smoothed mean annual rainfall steadily decreased until the beginning of the 20th century and thereafter it remained more or less constant until the end of the century. On the other hand, the smoothed mean annual temperature has steadily increased since the beginning of the 18th century until recent times. These trends are also suggested by the climate projections for the latter part of the current 21st century. As the study area is a high-relief karst massif of significant hydrologic and ecologic interest, the implications of these trends should be taken into account when formulating effective action plans to mitigate the impact of climate change. |
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| Keywords: | Dendro-climatological analysis Kernel smoothing Climatic change Rainfall Temperature Southern Spain |
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