Journal Article

Potential Predictability of the Madden‐Julian Oscillation in a Superparameterized Model

Kuang, Zhiming, Weidman, Sarah

2023

Overview

The Madden‐Julian Oscillation (MJO) is a promising target for improving sub‐seasonal weather forecasts. Current forecast models struggle to simulate the MJO due to imperfect convective parameterizations and mean state biases, degrading their forecast skill. Previous studies have estimated a potential MJO predictability 5–15 days higher than current forecast skill, but these estimates also use models with parameterized convection. We perform a perfect‐model predictability experiment using a superparameterized global model in which the convective parameterization is replaced by a cloud resolving model. We add a second “silent” cloud resolving component to the control simulation that independently calculates convective‐scale processes using the same large‐scale forcings. The second set of convective states are used to initialize forecasts, representing uncertainty on the convective scale. We find a potential predictability of the MJO of 35–40 days in boreal winter using a single‐member ensemble forecast. Plain Language Summary The Madden‐Julian Oscillation is a convective signal in the tropics that has the potential to improve 10‐40‐day weather forecasts. Current weather forecast models struggle to simulate the MJO, leading to a lower forecast skill than many studies estimate could be possible. We use a model with a comparatively good representation of the MJO that calculates convection information with a cloud permitting model. We modify this multiscale model's structure to generate MJO forecasts for its own MJO. Results from these forecasts suggest that the MJO in this model could be predictable up to 35–40 days using a single‐member ensemble forecast, which is 5–10 days longer than current state‐of‐the‐art forecasts. Key Points A novel approach is used to conduct perfect‐model predictability experiments using a superparameterized global model A single ensemble member model with superparameterized convection finds a potential Madden‐Julian Oscillation predictability of 35–40 days Resulting predictability estimates are comparable to those from current state‐of‐the‐art multiple ensemble member forecasting models

• Publisher: John Wiley & Sons, Inc,Wiley
• Subject: Control simulation / Convection / Ensemble forecasting / Experiments / Forecasting models / Forecasting skill / Madden-Julian oscillation / Parameterization / predictability / Seasonal forecasting / Simulation / superparameterization / Weather forecasting