CLIMOD RESEARCH GROUP
Our group focuses on developing climate based model for decision making.
The works use climate indices and local temperatures as model inputs to predict climate and weather related phenomena. Our modeling tools cover multiple regression, fuzzy logic, and neural-networks techniques.
The predictions are then tailored with interactive visualization tools to produce Infectious diseases and geohazard hotspots, coral bleaching and COTS early warning systems, cave-arts management tools, inland and marine protected area and conservation maps. We can view these products as informed-based decisions for managers.
Our Mission
Our mission is to harness the power of climate-based modeling to enhance decision-making processes across various sectors. By integrating climate indices and local temperature data, we aim to provide accurate predictions of climate and weather-related phenomena, empowering stakeholders with the tools they need to address environmental challenges effectively.
Aims
Our aims are (but not limited) to:
1. develop advanced statistical techniques: utilize multiple regression, fuzzy logic, and neural network or machine learning methodologies to create robust climate models that accurately predict weather-related phenomena.
2. enhance decision-making: provide tailored predictions that inform decision-makers about infectious disease outbreaks, geohazard hotspots, coral bleaching events, and other critical environmental issues.
3. create interactive visualization tools: design user-friendly visualization tools that allow stakeholders to easily interpret and utilize model outputs for effective management and planning.
4. support conservation efforts: develop management tools and conservation maps for inland and marine protected areas, facilitating informed decisions that promote biodiversity and ecosystem health.
5. foster collaboration: engage with policymakers, researchers, and community leaders to ensure that our modeling tools and predictions are effectively integrated into real-world decision-making processes.