the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
The 4DEnVar-based weakly coupled land data assimilation system for E3SM version 2
Pengfei Shi
Bin Wang
Kai Zhang
Samson M. Hagos
Shixuan Zhang
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Climate models are crucial for predicting climate change in detail. This paper proposes a balanced approach to improving their accuracy by combining traditional process-based methods with modern artificial intelligence (AI) techniques while maximizing the resolution to allow for ensemble simulations. The authors propose using AI to learn from both observational and simulated data while incorporating existing physical knowledge to reduce data demands and improve climate prediction reliability.
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mass-fluxterm. These adjustments enhance the model's performance, offering more reliable temperature and surface flux estimates.
Large volcanic eruptions deposit material into the upper-atmosphere, which is capable of altering temperature and wind patterns of the Earth's atmosphere for years following. This research describes a new method of simulating these effects in an idealized, efficient atmospheric model. A volcanic eruption of sulfur dioxide is described with a simplified set of physical rules, which eventually cools the planetary surface. This model has been designed as a testbed for climate attribution studies.