Subseasonal forecasting of weather and climate requires an in-depth understanding of climate processes. Understanding and predicting the Madden-Julian Oscillation (MJO) has been a foundational step forward toward providing decision-makers with advanced warning of extreme weather events. Over the past decade, the process understanding and modeling community has made significant improvements in predicting the MJO. New research results from a project led by Hyemi Kim, a Stony Brook University scientist co-funded by NOAA Research’s Modeling, Analysis, Predictions and Projections (MAPP) Program, analyzes these important improvements. The study identifies the causes of improvement, factors that influence prediction sensitivity, and recommendations for the future of MJO prediction research.
View the preliminary accepted version of the paper here.
The Modeling, Analysis, Predictions, and Projections (MAPP) Program is a competitive research program in NOAA Research’s Climate Program Office. MAPP’s mission is to enhance the Nation’s and NOAA’s capability to understand, predict, and project variability and long-term changes in Earth’s system and mitigate human and economic impacts. To achieve its mission, MAPP supports foundational research, transition of research to applications, and engagement across other parts of NOAA, among partner agencies, and with the external research community. MAPP plays a crucial role in enabling national preparedness for extreme events like drought and longer-term climate changes. For more information, please visit www.cpo.noaa.gov/MAPP.
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