Using machine learning algorithms to predict groundwater levels in Indonesian tropical peatlands.

Tropical peatlands play a vital role in the global carbon cycle as large carbon reservoirs and substantial carbon sinks. Indonesia possesses the largest share (65 %) of tropical peat carbon, equal to 57.4 Gt C.

Long-lead prediction of the 2015 fire and haze episode in Indonesia.

We conducted a case study of NCEP CFSv2 seasonal model forecast performance over Indonesia in predicting the dry conditions in 2015 that led to severe fire, in comparison to the non-El Niño dry season conditions of 2016. Forecasts of the Drought Code (DC) component of Indonesia's Fire Danger Rating System were examined across the entire Equatorial Asia region and for the primary burning regions within it. Our results show that early warning lead times of high observed DC in September and October 2015 varied considerably for different regions.