Improved subseasonal prediction of South Asian monsoon rainfall using data-driven forecasts of oscillatory modes.

ABSTRACT: Predicting the temporal and spatial patterns of South Asian monsoon rainfall within a season is of critical importance due to its impact on agriculture, water availability, and flooding. The monsoon intraseasonal oscillation (MISO) is a robust northward-propagating mode that determines the active and break phases of the monsoon and much of the regional distribution of rainfall. However, dynamical atmospheric forecast models predict this mode poorly. Data-driven methods for MISO prediction have shown more skill, but only predict the portion of the rainfall corresponding to MISO rather than the full rainfall signal. Here, we combine state-of-the-art ensemble precipitation forecasts from a high-resolution atmospheric model with data-driven forecasts of MISO. The ensemble members of the detail

SUBMITTER: Bach E 

PROVIDER: S-EPMC11009656 | biostudies-literature | 2024 Apr

REPOSITORIES: biostudies-literature