A New Perspective on Global Warming Attribution based Solely on Data Modeling

The earth's climate of the past few decades is anomalous; global warming is apparent. Many methods have been used to study the climate change and most results pointed the human activity as the main cause of the global warming although some people are still sceptical about the conclusion. This paper proposes a global warming attribution method based solely on data modeling, which applies system identification technology to earth climate research in an attempt to identify the main causes of global warming. Recorded and reconstructed climatic data with sampling time of one year are used in dynamic model identification. Three system inputs are used: solar activity, anthropic (human) activity and volcanic activity; the system output is the global mean temperature. Models using different data sets and different lengths are identified. Good models are defined as models that agree with the thermal dynamic law and that have good fitting of the data. Many good models can be obtained using the available climate data sets. The simulation studies of good models all indicates that the anthropic (human) activity is the major cause of the recent global warming.