Title: Deep learning reveals moisture as the primary predictability source of MJO
Abstract: The Madden-Julian Oscillation (MJO) is the dominant mode of tropical intraseasonal variability that interacts with many other Earth system phenomena. The prediction skill of the MJO in many operational models is lower than its potential predictability, partly due to our limited understanding of its predictability source. Here, we investigate the source of the MJO predictability by combining machine learning (ML) with a 1200-year-long Community Earth System Model version 2 (CESM2) simulation. A Convolutional Neural Network (CNN) for MJO prediction is first trained using the CESM2 simulation and then fine-tuned using observation via transfer learning. The source of MJO predictability in the CNN is examined via eXplainable Artificial Intelligence (XAI) methods that quantify the relative importance of the input variable. Our CNN outperforms previous ML models and many operational forecasts with the prediction skill of about 25 days. The XAI methods highlight precipitable water anomalies over the Indo-Pacific warm pool as key precursors of the subsequent MJO development for 1-3 weeks forecast lead times. Our results suggest that a realistic representation of moisture dynamics is crucial for accurate MJO prediction.
Biography: Daehyun Kim is an Associate Professor in Atmospheric Sciences in the Department of Atmospheric Sciences at the University of Washington. His research interests include tropical meteorology, climate dynamics, cloud physics, and earth system modeling. He earned his B.S. in 2003 and his Ph.D. 2010 in Atmospheric Sciences from Seoul National University. He then joined Columbia University as a Postdoctoral Research Scientist from 2010-2012 and a Lamont Assistant Research Professor from 2012-2014 at the Lamont-Doherty Earth Observatory. He then joined the faculty in the Department of Atmospheric Sciences at the University of Washington, Seattle, in 2014. He is the recipient of the 2020 Atmospheric Sciences Teaching Award from the Department of Atmospheric Sciences at the University of Washington, the 2017 Distinguished Scholar Award from the Korean Meteorological Society, and the 2012 James R. Holton Junior Scientist Award from the American Geophysical Union.