4.6 Article

Seasonal forecasting of fire over Kalimantan, Indonesia

Journal

NATURAL HAZARDS AND EARTH SYSTEM SCIENCES
Volume 15, Issue 3, Pages 429-442

Publisher

COPERNICUS GESELLSCHAFT MBH
DOI: 10.5194/nhess-15-429-2015

Keywords

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Funding

  1. Open University Research Investment Fellowship scheme
  2. NERC QUEST programme (FireMAFS: Fire Modelling and Forecasting System project) [NE/F001681/1]
  3. Copernicus program
  4. EU FP7 project MACC-II [283576]
  5. NERC [NE/F00169X/1, NE/F001681/1, NE/F001592/1] Funding Source: UKRI
  6. Natural Environment Research Council [NE/F001592/1, NE/F00169X/1, NE/F001681/1] Funding Source: researchfish

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Large-scale fires occur frequently across Indonesia, particularly in the southern region of Kalimantan and eastern Sumatra. They have considerable impacts on carbon emissions, haze production, biodiversity, health, and economic activities. In this study, we demonstrate that severe fire and haze events in Indonesia can generally be predicted months in advance using predictions of seasonal rainfall from the ECMWF System 4 coupled ocean-atmosphere model. Based on analyses of long, up-to-date series observations on burnt area, rainfall, and tree cover, we demonstrate that fire activity is negatively correlated with rainfall and is positively associated with deforestation in Indonesia. There is a contrast between the southern region of Kalimantan (high fire activity, high tree cover loss, and strong non-linear correlation between observed rainfall and fire) and the central region of Kalimantan (low fire activity, low tree cover loss, and weak, non-linear correlation between observed rainfall and fire). The ECMWF seasonal forecast provides skilled forecasts of burnt and fire-affected area with several months lead time explaining at least 70% of the variance between rainfall and burnt and fire-affected area. Results are strongly influenced by El Nino years which show a consistent positive bias. Overall, our findings point to a high potential for using a more physical-based method for predicting fires with several months lead time in the tropics rather than one based on indexes only. We argue that seasonal precipitation forecasts should be central to Indonesia's evolving fire management policy.

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