Volatility in atmospheric temperature variability

Abstract

Using detrended fluctuation analysis (DFA), we study the scaling properties of the volatility time series $V_i=|T_{i+1}-T_i|$ of daily temperatures $T_i$ for ten chosen sites around the globe. We find that the volatility is long range power-law correlated with an e xponent $\gamma$ close to 0.8 for all sites considered here. We use this result to test the scaling performance of several state-of-the art global climate models and find that the models do not reproduce the observed scaling behavior.

10 pages, 3 figures. Accepted for publication in Physica A

References in corpus (1)

• Global climate models violate scaling of the observed atmospheric variability

Cited by in corpus (3)

• Multifractal Analysis of Polyalanines Time Series
• Inferring long memory using extreme events
• Appropriateness of correlated first order auto-regressive processes for modeling daily temperature records