The need to understand and predict the earth’s evolving climate has never been more imperative. Being a complex system, a single model cannot capture all relevant features of the weather and climate systems. To address this, researchers approach the problem from multiple viewpoints combining ground and satellite-based observations, recent advances in scientific computing and machine learning, and an ever-increasing list of earth system models of varying complexity describing different physical processes. Combining these methodologies into a consistent picture is the “model hierarchy problem”.
This interdisciplinary workshop brings together researchers with expertise in dynamical systems, machine learning, data assimilation and earth science to discuss ways to consistently model the climate across spatial and temporal scales. It will also work to solidify connections between mathematically convenient descriptions of the climate with physical properties, while spurring an advancement in the mathematical understanding of the hierarchy problem and associated issues of risk assessment due to climate change. The workshop will also be a forum to nucleate a community of researchers in India to address these challenges by stimulating scientific collaboration with similar communities internationally.
