Understanding climate drivers of drought and fire multi-hazards in Indonesian Borneo using climate model and seasonal hindcast ensembles

<p>Fires occurring over the peatlands in Indonesian Borneo accompanied by droughts have posed devastating impacts on human health, livelihoods, economy and the natural environment, and their prevention requires a comprehensive understanding of climate-associated risk. We want to strengthen the possibility of early warning triggers of drought, which is a strong predictor of the prevalence of fires, and evaluate the climate risk relevant to the formulation of long-term policies to eliminate fires. Although it is widely known that the droughts are often associated with El Ni&#241;o events, the onset process of El Ni&#241;o and thus the drought precursors and their possible changes under the future climate are not clearly understood. Here we use a causal network approach to quantify the strength of teleconnections to droughts at a seasonal timescale shown in (1) observational and reanalysis data (2) CMIP6 models and (3) seasonal hindcasts. We consider two drivers of JJA droughts identified through literature review and causal analysis, namely Ni&#241;o 3.4 SST in JJA (abbreviated as ENSO) and SST anomaly over the eastern North Pacific to the east of the Hawaiian Islands (abbreviated as Pacific SST) in MAM. The observational and reanalysis data proves that the droughts are strongly linked to ENSO variability, with drier years corresponding to El Ni&#241;o conditions, and droughts can be predicted with a lead time of three months based on their associations with Pacific SST, with higher SST preceding drier conditions. We find that some CMIP6 models are showing unrealistic amounts of JJA rainfall and underestimate drought risks in Indonesian Borneo and their teleconnections, owing to the underestimation of ENSO amplitude and overestimation of local convections. Under the SSP585 scenario, the CMIP6 multi-model ensembles show significant increase in both the maximum number of consecutive dry days in the Indonesian Borneo region in JJA (p = 0.006) and its linear association with Pacific SST in MAM (p = 0.001) from year 2061 &#8211; 2100 compared with the historical baseline. On the other hand, seasonal hindcast models are (1) overestimating the variability of maximum number of consecutive dry days, (2) showing varied skills in simulating the mean rainfall and drought indicators, and (3) underestimating the teleconnections to Borneo droughts, making it difficult to assess the likelihood of unprecedented drought and fire risk under El Ni&#241;o conditions. Our study agrees with previous studies regarding the limited skill of fire risk prediction by state-of-the-art seasonal forecasting models, with their shortfalls caused by a lack of proper representation of relevant teleconnections.</p>