Nonstationary, long memory and anti-persistence in several climatological time series data

In this article we examine the stochastic behaviour of several daily datasets describing sun (total irradiance at the top of the atmosphere and sunspot numbers) and various climatological anomaly series by looking at their orders of integration. We use a testing procedure that permits us to consider fractional degrees of integration. The tests are valid under general forms of serial correlation and deterministic trends and do not require estimation of the fractional differencing parameter. Results show that the series are all nonstationary, with increments that might be stationary for those variables affecting sun, and anti-persistent for those affecting air temperatures.     

Persistence of Methane Emission in OECD Countries for 1750–2014: a Fractional Integration Approach

Environmental Modeling & Assessment - Anthropogenic methane emission is the most important greenhouse gas, after CO2 emission. However, various aspects of methane emission have not been...