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Open Access Publications from the University of California

Satellite observations of terrestrial water storage provide early warning information about drought and fire season severity in the Amazon

  • Author(s): Chen, Yang
  • Velicogna, Isabella
  • Famiglietti, James S
  • Randerson, James T
  • et al.

 Fire risk in the Amazon can be predicted several months before the onset of the dry season using sea surface temperatures in the tropical north Atlantic and tropical Pacific. The lead times between ocean state and the period of maximum burning (4–11 months) may enable the development of forecasts with benefits for forest conservation, yet the underlying physical and biological mechanisms responsible for these temporal offsets are not well known. Here, we examined the hypothesis that year-to-year variations in soil water recharge during the wet season modify atmospheric water vapor and fire behavior during the following dry season. We tested this hypothesis by analyzing terrestrial water storage observations from the Gravity Recovery and Climate Experiment (GRACE), active fires from the Moderate Resolution Imaging Spectroradiometer (MODIS), and several other satellite and atmospheric reanalysis datasets during 2002–2011. We found that terrestrial water storage deficits preceded severe fire seasons across the southern Amazon. The most significant relationships between monthly terrestrial water storage and the sum of active fires during the dry season occurred during April–August (p < 0.02), corresponding to 1–5 month lead times before the peak month of burning (September). Analysis of other datasets provided evidence for a cascade of processes during drought events, with lower cumulative precipitation (and higher cumulative evapotranspiration) in the wet season substantially reducing terrestrial water storage, and subsequently, surface and column atmospheric water vapor. Our results suggest that terrestrial water storage observations from GRACE have the potential to improve fire season forecasts for the southern Amazon.

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