Quantification and prediction of compound dry and hot events

The overarching goal is to undertake a novel investigation of compound drought and hot event driver’s quantification, and prediction at various spatial and temporal scales by integrating statistical physics, wavelet analysis, complex networks and artificial intelligence-based machine learning.

  • Work package-1: Understanding physical process driving the compound event using causal networks
  • Work package-2: Assessing predictability and prediction skill of compound events on sub-seasonal to seasonal (s2s) time scale using advanced machine learning tools grounded on novel information developed through causal networks.
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