Quantifying and Modeling Climate Time Series

This book details techniques for collecting statistical signals of climate variability and change. It explains the difference between short and long range variability in daily total solar irradiance and air temperature series.

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"Quantifying and Modeling Climate Time Series: An Empirical Approach" provides readers with analytical skills based on useful stochastic processes and two functions that quantify the temporal variability of time series. It shows and explains how daily series for basic climate variable, total solar irradiance (TSI) at the top of the atmosphere and air temperature at various spatial averaging level have been quantified. Also made clear is the crucial difference between the series short and long range variability. Focusing on long range variability enables geoscientists to fit a nonstationary integrated moving-average model to represent the daily TSI and air temperature series. A principal virtue of the model is its divisibility into a sum of white noise and random walk. Further, this empirical approach makes possible estimation of the relative importance of stationarity in the model and approximation of the variability range in long temperature series.