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Quantifying changes in climate variability and extremes: Pitfalls and their overcoming

MPG-Autoren
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Sippel,  Sebastian
Empirical Inference of the Earth System, Dr. Miguel D. Mahecha, Department Biogeochemical Integration, Dr. M. Reichstein, Max Planck Institute for Biogeochemistry, Max Planck Society;
IMPRS International Max Planck Research School for Global Biogeochemical Cycles, Max Planck Institute for Biogeochemistry , Max Planck Society;

/persons/resource/persons76340

Zscheischler,  Jakob
Empirical Inference of the Earth System, Dr. Miguel D. Mahecha, Department Biogeochemical Integration, Dr. M. Reichstein, Max Planck Institute for Biogeochemistry, Max Planck Society;

/persons/resource/persons62402

Heimann,  Martin
Department Biogeochemical Systems, Prof. M. Heimann, Max Planck Institute for Biogeochemistry, Max Planck Society;

/persons/resource/persons62472

Mahecha,  Miguel D.
Empirical Inference of the Earth System, Dr. Miguel D. Mahecha, Department Biogeochemical Integration, Dr. M. Reichstein, Max Planck Institute for Biogeochemistry, Max Planck Society;

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Zitation

Sippel, S., Zscheischler, J., Heimann, M., Otto, F. E., Peters, J., & Mahecha, M. D. (2015). Quantifying changes in climate variability and extremes: Pitfalls and their overcoming. Geophysical Research Letters, 42(22), 9990-9998. doi:10.1002/2015GL066307.


Zitierlink: http://hdl.handle.net/11858/00-001M-0000-0028-FAC0-3
Zusammenfassung
Hot temperature extremes have increased substantially in frequency and magnitude over past decades. A widely used approach to quantify this phenomenon is standardizing temperature data relative to the local mean and variability of a reference period. Here we demonstrate that this conventional procedure leads to exaggerated estimates of increasing temperature variability and extremes. For example, the occurrence of “two-sigma extremes” would be overestimated by 48.2% compared to a given reference period of 30 years with time-invariant simulated Gaussian data. This corresponds to an increase from a 2.0% to 2.9% probability of such events. We derive an analytical correction revealing that these artifacts prevail in recent studies. Our analyses lead to a revision of earlier reports: For instance, we show that there is no evidence for a recent increase in normalized temperature variability. In conclusion, we provide an analytical pathway to describe changes in variability and extremes in climate observations and model simulations.