Does Relative SST Matter? Seasonal and Spatial Differences Between ONI and RONI Associations with Philippine Rainfall
Abstract The El Niño-Southern Oscillation (ENSO) is an important driver of interannual climate variability, influencing tropical circulation and rainfall. However, its relationship with Philippine rainfall varies seasonally and spatially. This study compared the associations of the Oceanic Niño Index (ONI) and Relative Oceanic Niño Index (RONI) with seasonal rainfall anomalies across 37 Philippine synoptic stations using observations from 1961 to 2026. Results revealed predominantly negative correlations during the early and late parts of the year, with weaker and more spatially heterogeneous relationships during the middle of the year. Climate-type comparisons further highlighted geographic differences, particularly during Jun-Jul-Aug (JJA), when Type I stations exhibited positive median correlations for both indices, unlike Types II and III. The relative strength of the indices varied across seasonal windows: RONI showed stronger network-level absolute correlations during Dec–Feb (Δ|r| = +0.048) and Jan–Mar (+ 0.067), whereas ONI was favored during Apr–Jun (− 0.060). These seasonal differences remained statistically significant after false-discovery-rate adjustment and were consistent across the tested bootstrap block lengths. However, no comparable advantage was established for the remaining seasons. Overall, neither index consistently outperformed the other throughout the year. These findings provide region-specific evidence relevant to the interpretation of ENSO–rainfall relationships and the evaluation of alternative ENSO indices in tropical climate research.
Authors
- Jeremiah Morales (ORCID: https://orcid.org/0009-0006-6246-2034)
Institutions
- Philippine Atmospheric, Geophysical, and Astronomical Services Administration (PH)
Publication Details
- Journal
- Research Square
- Published
- 2026-11-02
- DOI
- https://doi.org/10.21203/rs.3.rs-11558293/v1
- Primary Topic
- Climate variability and models
- Type
- preprint