We improved the predictability of the downscaling methods, as accurate long-term seasonal forecast information is a key factor for subsequent successful forest fire prediction. Without a high level of confidence in the quality of the downscaled seasonal climate forecasts, we cannot guarantee the efficacy of the FGHEWS results. As a result, the overall seasonal climate forecasting technique for the EWS combines four different downscaling methods according to the degree of using dynamic prediction data produced by global climate models (GCMs). Since predictability on Borneo Island may differ depending on the target month and selected method, predictability was evaluated using the simple average of all available forecast information.
Figure 1. Schematic diagram of Fire and Haze Early Warning System (FHEWS)
APCC has been collecting monthly precipitation data from multiple dynamic models. Monthly prediction data regridded to 2.5°⨯2.5° resolution based on 13 individual Global Climate Models (GCM) (5 and 8 GCMs with 3-month and 6-month lead forecasts, respectively) were used for bias-correction using the Simple Bias Correction (SBC) method. The table 1 below shows the description of the 13 GCMs used in this FHEWS.
Table 1. List of dynamical seasonal prediction models used in this study
In our system, the SBC method was used to adjust the monthly mean of predicted precipitation by correcting the monthly average of prediction using the average of observations for the same period. The bias-corrected seasonal precipitation forecasts were applied to FHEWS utilizing historical precipitation-fire relationships. APCC developed a forest fire risk rating with four criteria (Low, Moderate, High, and Extreme) for the four provinces in Borneo Island. An analysis of the threshold levels for the study regions was conducted in order to translate the predicted precipitation amount to the forest fire risk ratings. If the forecasted precipitation level dips below the threshold, the FHEWS predicts an increased risk for severe burning, carbon emissions, and transboundary haze. It is important to note that connecting forecasted precipitation to the possible EWS index must be based on region-specific threshold levels. We used the relationship between region-average ASO precipitation and carbon emission data which were derived from APHRODITE’s Water Resources (http://www.chikyu.ac.jp/precip/) and Global Fire Emissions Database (http://www.globalfiredata.org/), respectively. The figure below shows the time series of the 3-month accumulated monthly precipitation and carbon emission levels in the Selatan region (Fig. 2).
Figure 2. Monthly precipitation and carbon emission in Selatan region