Aims & Scope
Present and future global warming research must be increasingly based on big datasets at terabyte and exabyte scales from diverse sources (e.g. climate, ocean, economy, energy, ecosystem dynamics, industry, agriculture, environment, public's attitude/knowledge surveys). The "International Journal of Big Data Mining for Global Warming" is an inter-disciplinary journal dedicated to the publication of high-quality research articles, review articles, letters, case studies and book reviews in all aspects of global warming through traditional mining methods (statistical, spectral, numerical, simulating, LCA, 3E, etc.) and non-traditional mining methods (neural networks, deep learning, cloud computing, etc.) of these big datasets.Topics to be covered by International Journal of Big Data Mining for Global Warming will include, but will not be limited to:
- Monitoring, diagnosis, and predictions of global warming trends and their impacts;
- Applications of artificial neural networks and deep learning in weather, climate and disaster predictions;
- Data-driven ecological/environmental impact assessments within the context of global warming impacts;
- Mining of big datasets of carbon footprinting of products and services as integrated within carbon taxation/trading schemes;
- Applications of cloud computing and distributed storage in climate and earth system modelling;
- Data-driven uncertainty analyses for climate prediction and their impacts on policy design and governance within governmental, industrial and institutional contexts;
- Data-driven resource management and utilization to combat global warming and meet ambitious climate goals;
- Survey and data mining for international governance, political obstacles, education, societal perceptions of global warming mitigation and adaption in short and long term perspectives.
- Integrated, interdisciplinary data mining to combat, reduce and prevent global warming and its impacts.