Abstract
This study applies Fourier filtering to a combination of rainfall estimates from TRMM and forecasts from the CFSv2. The combined data are filtered for low-frequency (LF, ≥120 days) variability, the MJO, and convectively coupled equatorial waves. The filtering provides insight into the sources of skill for the CFSv2. The LF filter, which encapsulates persistent anomalies generally corresponding with SSTs, has the largest contribution to forecast skill beyond week 2. Variability within the equatorial Pacific is dominated by its response to ENSO, such that both the unfiltered and the LF-filtered forecasts are skillful over the Pacific through the entire 45-day CFSv2 forecast. In fact, the LF forecasts in that region are more skillful than the unfiltered forecasts or any combination of the filters. Verifying filtered against unfiltered observations shows that subseasonal variability has very little opportunity to contribute to skill over the equatorial Pacific. Any subseasonal variability produced by the model is actually detracting from the skill there. The MJO primarily contributes to CFSv2 skill over the Indian Ocean, particularly during March–May and MJO phases 2–5. However, the model misses opportunities for the MJO to contribute to skill in other regions. Convectively coupled equatorial Rossby waves contribute to skill over the Indian Ocean during December–February and the Atlantic Ocean during September–November. Convectively coupled Kelvin waves show limited potential skill for predicting weekly averaged rainfall anomalies since they explain a relatively small percent of the observed variability.
ENSO modulation of tropical Indian Ocean subseasonal variability
