Articles | Volume 19, issue 12
https://doi.org/10.5194/gmd-19-5689-2026
https://doi.org/10.5194/gmd-19-5689-2026
Development and technical paper
 | 
30 Jun 2026
Development and technical paper |  | 30 Jun 2026

Improvement of the Rnnmm-type climate index approach with a spatio-temporal model based on the Hawkes process

Fidel Ernesto Castro Morales, Antonio Marcos Batista do Nascimento, Marina Silva Paez, Daniele Torres Rodrigues, and Carla de Moraes Apolinário

Model code and software

STprocHawkes: Repository for Spatio-Temporal Hawkes Process Models Projeto-CNPq-Clima https://doi.org/10.5281/zenodo.15652279

STprocPoisson: Spatio-Temporal Non-homogeneous Poisson Process Models Projeto-CNPq-Clima https://doi.org/10.5281/zenodo.15651335

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Short summary
This study introduces a new method to better understand extreme rainfall events by considering that heavy rain often occurs in clusters over time. Using rainfall records from northern Brazil, we developed and tested a statistical approach that improved prediction accuracy compared with existing methods. The results can support more reliable climate risk assessments and help improve planning for disaster prevention and climate change adaptation.
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