Temporal Lag Relationship Between Sea Surface Temperature and Fire Hotspot Occurrence in Sumatra During the 2023 Positive Indian Ocean Dipole Event

Technical Summary: Temporal Lag Relationship Between Sea Surface Temperature and Fire Hotspot Occurrence in Sumatra During the 2023 Positive Indian Ocean Dipole Event

Problem Statement
Forest and land fires in Sumatra, Indonesia, are significant environmental hazards driven by climate variability, particularly large-scale ocean-atmosphere interactions like the Indian Ocean Dipole (IOD). While the relationship between positive IOD events (characterized by cool Sea Surface Temperature anomalies in the eastern Indian Ocean) and drought-induced fire activity is well-documented, previous research has largely focused on seasonal or monthly aggregated relationships. There is a notable gap in understanding the specific temporal lag between daily SST variability and daily fire hotspot occurrence. The physical processes linking oceanic forcing to terrestrial fire susceptibility—such as reduced evaporation, suppressed convection, rainfall deficits, and subsequent soil/vegetation drying—are not instantaneous. This study addresses the need to quantify the response time of terrestrial fire systems to oceanic forcing to improve fire risk prediction and early warning systems.

Methodology
The study employed a quantitative time-series analysis covering the period from January 1 to December 31, 2023, a year marked by a strong positive IOD event.

• Data Sources:
  • Sea Surface Temperature (SST): Daily data from the NOAA Optimum Interpolation Sea Surface Temperature (OISST) Version 2.1 dataset. The study focused on the eastern equatorial Indian Ocean (90°E–110°E, 10°S–Equator), the eastern pole of the IOD.
  • Fire Hotspots: Daily hotspot counts within Sumatra provided by the ASEAN Specialized Meteorological Centre (ASMC), derived from satellite-based thermal anomaly detection.
• Data Processing:
  • SST data were spatially cropped and area-averaged to represent conditions in the eastern Indian Ocean.
  • Hotspot data were smoothed using a 7-day moving average filter to reduce high-frequency noise while preserving dominant temporal patterns.
• Statistical Analysis:
  • Temporal Evolution: Daily time-series plots were generated to visualize the progression of SST anomalies and hotspot counts.
  • Correlation Analysis: Pearson correlation coefficients were calculated to assess the linear relationship between SST and hotspots.
  • Lagged Correlation (Cross-Correlation Function - CCF): To identify delayed responses, CCF analysis was performed with lag values ranging from 0 to 90 days. This allowed the researchers to determine if SST changes preceded hotspot occurrences and to quantify the optimal response time.

Key Results

1. SST Evolution: The analysis confirmed substantial cooling in the eastern Indian Ocean during August–October 2023, corresponding to the mature phase of the positive IOD event. SST values dropped to a minimum of approximately 27.3°C in mid-October, forming a distinct "cold-water tongue" along the Sumatra-Java coast.
2. Hotspot Temporal Pattern: Fire activity remained low during the first half of the year when SST was warm. A dramatic increase in hotspot occurrence began in September, peaking in October (with daily counts exceeding 500 on the highest day). This peak coincided with the period of maximum SST cooling but occurred after the initial onset of cooling in July/August.
3. Lagged Relationship:
   • Short-term lags (0–10 days) showed negative correlations, indicating no immediate response of fire activity to SST fluctuations.
   • Correlation strength increased progressively as the lag time increased.
   • The analysis identified a statistically significant maximum Pearson correlation coefficient of r = 0.252 (p < 0.001) at a lag of approximately 60 days.
   • This 60-day lag suggests that SST anomalies influence fire activity indirectly through a sequence of atmospheric and terrestrial processes (reduced evaporation, suppressed convection, rainfall deficits, and environmental drying) rather than through immediate reaction.

Key Contributions

• Quantification of Response Time: The study provides empirical evidence that the response of Sumatran fire hotspots to eastern Indian Ocean SST anomalies is delayed, with a characteristic response window of approximately two months.
• Mechanistic Insight: It elucidates the "environmental memory" of the climate-fire system, demonstrating that fire occurrence is the final stage of a cascading process involving hydrological and ecological adjustments to oceanic forcing.
• Case Study Specificity: The research focuses on the 2023 positive IOD event, a significant climate episode that received less attention regarding hotspot dynamics compared to previous events (e.g., 2015, 2019), thereby addressing existing knowledge gaps.

Significance and Claims
The paper claims that the identified two-month lag highlights the potential of Eastern Indian Ocean SST anomalies as an early-warning indicator for anticipating elevated fire risk in Sumatra. By recognizing that fire activity is a delayed response to oceanic forcing, authorities can potentially incorporate SST monitoring into seasonal forecasting frameworks to anticipate periods of high fire susceptibility before widespread hotspot outbreaks occur.

The authors maintain a modest stance regarding the predictive power of SST alone. They acknowledge that while SST variability is a significant large-scale climatic driver, it does not fully explain hotspot occurrence, which is also influenced by precipitation, peatland hydrology, land-use practices, and anthropogenic ignition sources. Consequently, the study positions SST anomalies as a critical precursor within a broader, multi-factorial framework for fire risk assessment, rather than a sole determinant. The findings contribute to a better understanding of climate-fire interactions in western Indonesia and provide a scientific basis for integrating oceanic indicators into regional fire monitoring and forecasting frameworks.