MJO Predictive Skill and Impacts in the Navy Earth System Model

One of the main sources of predictability at subseasonal-to-seaonal (S2S) time scales is the Madden-Julian Oscillation (MJO). In the Navy Earth System Model (NESM), the NAVy Global Environmental Model (NAVGEM) is coupled to the Global Ocean Forecast System (GOFS), which consists of the HYbrid Coordinate Ocean Model (HYCOM) and the Los Alamos Community Ice CodE (CICE). Reforecasts out to 45 days initialized 4x weekly from 1999-2017 were performed for the Subseasonal eXperiment (SubX). The ability of the NESM to simulate the MJO is contrasted with other models in the S2S database.

In examining MJO skill in the SubX reforecasts, we compare the real-time multivariate MJO (RMM) index to two new metrics: (1) a time-extended empirical orthogonal function (EOF) using velocity potential and (2) wavenumber-frequency filtered fields. The time-extended EOF is three-dimensional (time-lag, latitude, longitude) and seasonally varying, which allows it to better capture the differences in MJO structure between summer and winter. In addition, because the time-extended EOF excludes the influence of high-frequency signals such as Kelvin waves it is more predictable than the RMM index. Compared to the global MJO indices, the wavenumber-frequency filtering approach is better able to depict regional variations in the skill of the models. We examine how MJO forecast skill relates to systematic biases and errors in MJO phase speed and amplitude in the different models and MJO indices. We also examine the temporal variability of skill and compare high and low skill periods in each of the models. Lastly, differences in MJO skill between the S2S models are related to differences in the ability of the models to predict mid-latitude teleconnections and tropical cyclone activity at S2S time scales.