Weather and temperatures vary in ways that are difficult to explain and predict precisely. In this article we review data on temperature variations in the past as well possible reasons for these variations. Subsequently, we review key properties of global climate models and statistical analyses...

We analyze the price dynamics of European allowances and international carbon credits in the second phase of the European carbon market. We develop and use a model combining fundamental drivers associated with the demand for quotas by installations and risk-return considerations related to the...

Outlying observations can bias regression estimates, requiring the use of robust estimators. Comparing robust estimates to those obtained using OLS is a common robustness check, however, such comparisons have been mostly informal due to the lack of available tests. Here we introduce a formal...

Evidence-based policy of global warming is best relying on a relevant sample of data. We choose a sample of annual data from 1959 to-date to provide some statistically robust stylized facts about the relationships between actual CO2 and temperature. Visually, there is a clear upward trend in...

Carbon abatement efforts in China are penetrating to sub-national level. Zhejiang province, as the 4th wealthy region in China and important player in global market (e.g., textiles, cloth, petroleum and chemical products), lacks in-depth study of its climate change mitigation efforts, especially...

This research uses annual time series data on CO2 emissions in India from 1960 to 2017, to model and forecast CO2 using the Box – Jenkins ARIMA approach. Our diagnostic tests indicate that India CO2 emission data is I (2). The study presents the ARIMA (2, 2, 0) model. The diagnostic tests...

Calculation of vegetation indices, especially Normalized Difference Vegetation Index (NDVI), has become one of the most successful, popular and traditional attempts in biogeographical research methods, because NDVI has certain advantages over other vegetation indices or band combinations. The...

Problem: How to help practitioners, academics, and decision makers use experimental research findings to substantially reduce forecast errors for all types of forecasting problems. Methods: Findings from our review of forecasting experiments were used to identify methods and principles that lead...

Econometric studies for global heating have typically used regional or global temperature averages to study its long memory properties. One typical explanation behind the long memory properties of temperature averages is cross-sectional aggregation. Nonetheless, formal analysis regarding the...

The logistic function is one of the most useful mathematical models that can be utilised for various practical, real-life data, such as forecasting sea ice extent. This study aims to determine what logistic function is and how it can help forecast a time series problem, as in our case, a sea ice...