Alessandro Attanasio

Testing for linear Granger causality from natural/anthropogenic forcings to global temperature anomalies

In this paper, we analyze the Granger causality from natural or anthropogenic forcings to global temperature anomalies. The lag-augmented Wald test is performed, and its robustness is also evaluated considering bootstrap method. The results show there is no-evidence of Granger causality from natural forcings to global temperature. On the contrary, a detectable Granger causality is found from anthropogenic forcings to global temperature confirming that greenhouse gases have an important role on recent global warming.

Evidence of recent causal decoupling between solar radiation and global temperature

The Sun has surely been a major external forcing to the climate system throughout the Holocene. Nevertheless, opposite trends in solar radiation and temperatures have been empirically identified in the last few decades. Here, by means of an inferential method—the Granger causality analysis—we analyze this situation and, for the first time, show that an evident causal decoupling between total solar irradiance and global temperature has appeared since the 1960s.

Analysis of spontaneous pneumothorax in the city of Cuneo: environmental correlations with meteorological and air pollutant variables

Background and PurposePrimary spontaneous pneumothorax (PSP) tends to cluster. Previous studies have found a correlation between PSP and atmospheric pressure variations or thunderstorms. We conducted this study to analyze the PSP correlations with meteorological variables and the concentrations of air pollutants in the city of Cuneo in Italy (IT).MethodsWe evaluated prospectively 451 consecutive PSP patients treated between 2004 and 2010. For each day within the period analyzed, the meteorological parameters and pollutants data were recorded. Statistical analyses on PSP were done for distribution characteristics, spectral autocorrelation, and spectral analysis. Multivariate regression analyses were performed using artificial neural networks.ResultsAnalysis of annual, seasonal, and monthly distributions showed no significant correlation between PSP and the time series. The spectral analysis showed that PSP events were not random. Correlations between meteorological and environmental variables confirmed that PSP was significantly more likely to occur on warm windy days with high atmospheric pressure and high mean nitrogen dioxide concentration.ConclusionsMeteorological parameters and atmospheric pollutants might explain the cluster onset of PSP.

Examining Granger causality between atmospheric parameters and radon

In this paper, we study the relationship between atmospheric parameters (i.e., temperature and humidity) and radon data. We use the linear Granger causality in order to observe possible connections, on short and mid time scale periods, between radon time series and meteorological parameters that strongly influence radon emissions. The analysis suggests radon emission is not affected by these atmospheric parameters on short periods, while there is an evidence of Granger causality on mid periods.

Measuring persistence in time series of temperature anomalies

Studies on persistence are important for the clarification of statistical properties of the analyzed time series and for understanding the dynamics of the systems which create these series. In climatology, the analysis of the autocorrelation function has been the main tool to investigate the persistence of a time series. In this paper, we propose to use a more sophisticated econometric instrument. Using this tool, we obtain an estimate of the persistence in global land and ocean and hemispheric temperature time series.

Clarifying the Roles of Greenhouse Gases and ENSO in Recent Global Warming through Their Prediction Performance

AbstractIt is well known that natural external forcings and decadal-to-millennial variability drove changes in the climate system throughout the Holocene. Regarding recent times, attribution studies have shown that greenhouse gases (GHGs) determined the trend of temperature (T) in the last half century, while circulation patterns contributed to modify its interannual, decadal, or multidecadal behavior over this period. Here temperature predictions based on vector autoregressive models (VARs) have been used to study the influence of GHGs and El Nino–Southern Oscillation (ENSO) on recent temperature behavior. It is found that in the last decades of steep temperature increase, ENSO shows just a very short-range influence on T, while GHGs are dominant for each forecast horizon. Conversely and quite surprisingly, in the previous quasi-stationary period the influences of GHGs and ENSO are comparable, even at longer range. Therefore, if the recent hiatus in global temperatures should persist into the near future...

Some considerations between radon and earthquakes in the crater of L’Aquila

AbstractThis paper is focused on developing statistical models to analyze the connection between radon emissions and earthquakes. Owing to our personal interest and the large amount of local data available in the period before and after the main shock, we decided to run our analysis on the recent earthquake which affected the Italian city of L’Aquila. We investigated the viability of a statistical method employing radon emissions to predict earthquakes. The results show a possible connection between radon and earthquake, but it is useless, in our opinion, to use this connection to forecast the magnitude of the seismic events.

Modeling Radon Behavior for Characterizing and Forecasting Geophysical Variables at the Atmosphere–Soil Interface

As well known, noble gases are often used as stable tracers in several geophysical environments, due to their basic property of being chemical noninteracting. Among these noble gases, the attention of researchers in the last decades has been focused on radon.