Lectura de tesis: "Improvement of seasonal forecasting techniques applied to water resources and forest fire"

  • Autor: Raul Marcos Matamoros
  • Sitio: Sala de Grados "Eduard Fontserè", Facultad de Física.
  • Fecha/Hora: 9 febrer 2016/12:00


  • Presidente: Dr. Jerónimo Lorente Castelló
  • Secretario: Dr. Luis Garrote de Marcos 
  • Vocal: Dr.   Giorgio Boni
  • Sustitutos: Dr. Antonio Parodi; Dra. Maria Rosa Soler


Dra. Mª. del Carmen LLasat  Botija
Dr. Pere Quintana Seguí
Dra. Mª. del Carmen LLasat  Botija (Tutora)


Droughts and wildfires are an inherent problem to the Mediterranean and are likely to worsen if climate change continues. Both hazards are a source of important economic cost, environmental damage and, in the case of wildfires, even life loss. These impacts have encouraged policy- and decision-makers to reduce vulnerability by placing great efforts in the development of mitigation and adaptation strategies. Seasonal forecasting could help with this task by foretelling the behaviour of water resources and wildfire with months in advance.

However, seasonal predictability in extra-tropical latitudes is usually considered rather limited and, consequently, seasonal forecasts are seldom used in decision-making. There are studies, though, suggesting that calibration methods could help to improve the current model's output. Thus, the existing gap between end-user goals and theoretical research needs more work demonstrating the utility of seasonal forecasts. To achieve this objective this thesis has been divided in three sub-objectives: skill assessment, seasonal forecast of water resources and seasonal forecast of forest fires.

The skill assessment comprises an evaluation of the skill of the raw ECMWF System-4 output in Europe, Spain, Catalonia and the Muga river basin; and the study of the impact on the ECMWF System-4 performance of the MOS-analog and linear regression calibrations in comparison to mean bias correction. As for the seasonal forecast of water resources the application has begun with the modelling of the Boadella reservoir in-flow, out-flow and volume anomalies through a multiple linear regression (MLR) procedure. Afterwards, the seasonal predictability of the Boadella predictands has been evaluated through several seasonal forecast approaches. Finally, regarding the seasonal forecast of wildfires the first step has been to model summer (JJAS) burned area in Catalonia through a MLR with antecedent and current year drought conditions. Subsequently, the MLR performance has been tested under different seasonal forecast configurations.