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3D Printing of coastal protection Reefs

The Albanian coastline has been declining in recent years due to coastal erosion and uncontrolled...

FIRECAST

Societal exposure to large fires has been increasing in recent years. Our fire forecasting system reveal an untapped and useful burned area predictive ability using seasonal climate models, which can play a crucial role in developing fire management strategies minimising the impact of adverse climate conditions.

Developed by Univ. of Barcelona; Univ. of Murcia; Barcelona Supercomputing Center
FIRECAST is a novel simulation tool for forecasting burned area anomalies through linking seasonal climate predictions with parsimonious empirical climate fire models.

TRL3. Critical function: Proof of concept established
Active is initiated. This includes analytical studies and laboratory studies to physically validate the analytical predictions of separate elements of the technology. Examples include components that are not yet integrated or representative. We assess the forecasting skill of the system as it is a prototype real-time operational forecast system. This seasonal fire forecast system is based on operational dynamical climate forecast systems. In addition, all the forecasts are done by using cross-validation in order to evaluate the predictions as if they were done operationally, including the steps of the bias correction of the seasonal climate data and of the calibration of the fire-climate models. Moreover, to avoid artificial skill, the observed series are de-trended and standardized in each step of the cross-validation, avoiding using observation of the predicted year.

See more information about this level and the TRL and SRL levels.

The main components of the system have been tested separately, and an initial integration exercise has been conducted.

Credits
Collaborators

How does it work?

Our strategy for seasonally forecasting burned area anomalies consists in linking seasonal climate predictions with parsimonious empirical climate–fire models using the standardized precipitation index as the climate predictor for burned area.

Limitations/conditions under which this innovation does not work or is less effective

This innovation may be less effective over data-poor regions such as Africa and South America owing to the uncertainties of the observed near-real-time data.

Added value
The key contribution of this innovation is to provide skillful BA predictions using multi-model seasonal climate predictions at a global scale and for each season separately. The system reveals substantial BA predictability based on antecedent and forecasted climate conditions that can be exploited for fire risk management months ahead.

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Societal exposure to large fires has been increasing in recent years. Our fire forecasting system...

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Purpose and legitimacy: attention and management of the consultation made by the USER who completes the Personal Data of the Contact Form. If the USER gives his/her consent, the contact data will be used to send him/her commercial information.

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Transfer: If the USER gives express consent, the data may be transferred to entities related to ASOCIACIÓN BRIGAID CONNECT or belonging to the ASOCIACIÓN BRIGAID CONNECT GROUP. It will not be necessary to obtain your consent when the transfer is covered by the legitimate interest of the Responsible for the Web.

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