A dependence modelling study of extreme rainfall in Madeira Island |
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| Institution: | 1. Faculty of Exact Sciences and Engineering, University of Madeira, Penteada Campus, 9000-390 Funchal, Madeira Is., Portugal;2. CEAUL – Center of Statistics and Applications, University of Lisbon, Campo Grande, 1749-016 Lisbon, Portugal;3. CIMO – Mountain Research Centre, ESA/IPB, 5300-253 Bragança, Portugal;4. ICAAM – Institute of Mediterranean Agricultural and Environmental Sciences, University of Évora, Mitra Campus, 7002-554 Évora, Portugal;5. PPG-CLIAMB – INPA/UEA and RHASA – Laboratory for Water Resources and Satellite Altimetry, Amazonas State University, 69050-020 Manaus, AM, Brazil;1. State Key Laboratory of Electronic Thin Films and Integrated Devices, University of Electronic Science and Technology of China (UESTC), Chengdu, 610054, China;4. Department of Electrical Engineering, University of South Africa, Pretoria 0001, South Africa;1. Department of Geoinformation Photogrammetry and Remote Sensing of Environment, Faculty of Mining Surveying and Environmental Engineering, AGH University of Science and Technology, Poland;2. Department of Hydraulic and Sanitary Engineering, The Section of Hydraulic Engineering, Faculty of Environmental Engineering and Spatial Management, Poznan University of Life Sciences, Poland;3. Department of Ecology and Environmental Protection, Faculty of Environmental Engineering and Spatial Management, Poznan University of Life Sciences, Poland;4. Institute of Civil Engineering and Geoengineering, Faculty of Environmental Engineering and Spatial Management, Poznan University of Life Sciences, Poland;5. Department of Forest Management, Faculty of Forestry, Poznan University of Life Sciences, Poland;1. Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China;2. Beijing Key Laboratory of Environmental Damage Assessment and Remediation, Beijing, China;3. University of Chinese Academy of Sciences, Beijing 100049, China;4. Key Laboratory of Engineering Oceanography, Second Institute of Oceanography, SOA, Hangzhou 310012, China;1. College of Life Sciences, China Jiliang University, Hangzhou 730000, PR China;2. School of Natural Sciences and Psychology, Liverpool John Moores University, Liverpool L3 3AF, UK;1. National Center for Atmospheric Research, P.O. Box 3000, Boulder, CO 80307, USA;2. School of Civil Engineering and Geosciences, Newcastle University, Newcastle-upon-Tyne, UK;3. Exeter Climate Systems, Mathematics Research Institute, University of Exeter, Exeter, UK;4. Willis Research Network, 51 Lime Street, London EC3M 7DQ, UK |
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| Abstract: | The dependence between variables plays a central role in multivariate extremes. In this paper, spatial dependence of Madeira Island's rainfall data is addressed within an extreme value copula approach through an analysis of maximum annual data. The impact of altitude, slope orientation, distance between rain gauge stations and distance from the stations to the sea are investigated for two different periods of time. The results obtained highlight the influence of the island's complex topography on the spatial distribution of extreme rainfall in Madeira Island. |
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| Keywords: | Statistics of extremes Kendall's tau Copula functions Extreme rainfall |
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