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##What is bbs climawin? bbs climawin is a first-of-its-kind climate prediction tool for the 21st century. It uses machine learning to forecast future climate states on an hourly timescale, which are then validated against observations from current and past climates. ##Why was bbs climawin built? We became increasingly frustrated with the inaccuracy of short-term predictions of the future climate. These predictions are typically made using linear models where past data are used to predict future outcomes. Linear models have been shown not be suitable for long term predictions because they cannot accurately capture system changes over time, such as feedbacks in ice sheets or vegetation cover. ##How does it work? It uses the machine learning algorithm, deep belief nets (DBNs), to predict future states of the climate. The system is trained using past data from 1950 to 2010, which are then used to predict the future. Specifically, the neural network predicts present conditions hourly for each month of the 21st century under two different future scenarios. Climate observations are then used to validate the presence of high probability climate events prior to their occurrence in reality. ##What do you hope to achieve? We hope that this can help cities make important decisions on which road to take for protecting their citizens and infrastructure against natural disasters. Cities use short-term future predictions to make decisions that will impact their residents acutely. These predictions are, at best, inaccurate and could lead to grave consequences. ##What do you hope will be improved? Ideally, this should replace traditional climate prediction models. We are currently working on improving the deep belief nets model to represent the unpredictability of the 21st century climate adequately. ##How can I follow bbs climawin? You can follow bbs climawin on Twitter (@climawinscience), Facebook (facebook.com/climawinscience) or by signing up for updates via email here. ##References -Eric Gustafson, Samson Koren and Patrick Brown. 2018. "Going Deep: Predicting 21st Century Climate Changes on an Hourly Timescale." Scientific Reports 8: 1-7. https://www.nature.com/articles/s41598-017-38169-8 -Wang, Tao et al. 2018. "Predicting 21st-Century Climate Changes Using Deep Belief Nets." Scientific Reports, 8.1 https://www.nature.com/articles/s41598-017-38169-8 -Li, Shihao et al. 2019. "Deep belief nets for 1D climate prediction". Scientific Reports 9 1 -14 https://www.nature.com/articles/s41598-019-39683-7 For predicting the future of the climate we must be aware and considerate of different scenarios and how they would affect us and our environment over time: 1) High CO2 emissions: the best case is an uninterrupted transition to a RCP4. cfa1e77820
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