Climate Observations (eBook)

Climate Observations: Data Quality Control and Time Series Homogenization pulls together the different phases of the production of high-quality climatic datasets, allowing interested readers to obtain a coherent picture on the complexity and importance of this task. There are several new methods of time series homogenization, each very complex and fast developing. The thematic discussion of the production of high quality climatic datasets provides the opportunity to reduce errors, including the careful installation of meteorological instruments, the application of strict observing rules and inspections, and the use of sophistically developed statistical software to detect and remove errors or biases. This book is intended for professionals working on climate data management at the national meteorological services, for the users of observed climatic data, and for students and researchers studying atmospheric and climate science. Members of the Royal Meteorological Society are eligible for a 35% discount on all Developments in Weather and Climate Science series titles. See the RMetS member dashboard for the discount code. - Describes the research tasks and tools for which the reliability and accuracy of climatic data is particularly important - Includes case studies to provide real-world context to the research presented in the book - Features benchmark datasets that have been used for testing the stable operation and efficiency of homogenization methods - Explains the use of semiautomatic quality control software, recently developed effective homogenization methods, their testing, and related new concepts and statistical tools

Peter Domonkos is a Hungarian climatologist living in Spain since 2009. He is expert on statistical climatology, analysis of extreme climatic events, data quality control and time series homogenization. He is member of the Hungarian Meteorological Society and secretary of ESPERE (Environmental Science for Everybody Round the Earth). Between 2009 - 2015 Dr. Domonkos was a researcher of the University Rovira i Virgili (Tarragona, Spain), and is a free researcher since then. He has been developed an automatic homogenization method (ACMANT), which was found to be one of the most accurate methods by various international test experiments. Between 2013 and 2015 he led 4 international trainings on time series homogenization, sponsored by the World Meteorological Organization. He has 104 printed scientific publications.

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Climate Observations: Data Quality Control and Time Series Homogenization pulls together the different phases of the production of high-quality climatic datasets, allowing interested readers to obtain a coherent picture on the complexity and importance of this task. There are several new methods of time series homogenization, each very complex and fast developing. The thematic discussion of the production of high quality climatic datasets provides the opportunity to reduce errors, including the careful installation of meteorological instruments, the application of strict observing rules and inspections, and the use of sophistically developed statistical software to detect and remove errors or biases. This book is intended for professionals working on climate data management at the national meteorological services, for the users of observed climatic data, and for students and researchers studying atmospheric and climate science. Members of the Royal Meteorological Society are eligible for a 35% discount on all Developments in Weather and Climate Science series titles. See the RMetS member dashboard for the discount code. - Describes the research tasks and tools for which the reliability and accuracy of climatic data is particularly important- Includes case studies to provide real-world context to the research presented in the book- Features benchmark datasets that have been used for testing the stable operation and efficiency of homogenization methods- Explains the use of semiautomatic quality control software, recently developed effective homogenization methods, their testing, and related new concepts and statistical tools