Seasonal Comparison of the Wildfire Emissions in Southern African Region during the Strong ENSO Events of 2010/11 and 2015/16 Using Trend Analysis and Anomaly Detection

Abstract

This study investigates the wildfire biomass-burning emission levels during strong El Niño–southern oscillation (ENSO) events of 2010–2011 (characterized by a strong La Niña event) and 2015–2016 (characterized by a strong El Niño event) over the southern African region. Specifically, the biomass-burning parameters of black carbon (BC), carbon monoxide (CO) and sulfur dioxide (SO2) were investigated. Of interest in the current study was the strong El Niño (2015–2016) and La Niña (2010–2011) events during the main fire seasons in southern Africa, i.e., June–July–August (JJA) and September–October–November (SON). Furthermore, the study looks at how meteorological parameters (temperature and precipitation) are influenced by the two strong ENSO events. The sequential Mann–Kendall (SQMK) test is used to study the long-term trends of the emission and meteorological parameters. Anomaly detection on the long-term emission trends and meteorological parameters are performed using the seasonal and trend decomposition loess (STL) and generalized extreme studentized deviate (GESD). Overall, the results show higher emission levels of SO2, CO, and BC during the JJA season compared to the SON season. The SQMK results show an increasing trend of SO2, CO, and BC over time, indicating an increase in the amount of biomass burning. The GESD showed significant anomalies for BC, SO2, and CO emanating from the two strong El Niño and La Niña events. On the other hand, no significant anomalies were detected for temperature and precipitation. The results in this study highlight the significant effect of strong ENSO events on wildfire emissions, thus retrospectively showing the potential effect of future events, especially in the context of climate change.

Keywords

• ENSO
• wildfires
• southern Africa
• remote sensing
• sea surface temperature