RIMES research on climate change deepens understanding of climate variability, potential impacts, and coping strategies
RIMES identifies global climate models that are consistent with observed climate data and trends over the region. Dynamical and statistical downscaling techniques are then used to generate climate scenarios for selected time slices for the country. Evaluation is then undertaken against the baseline climatology.
RIMES develops tools, models, and methods to enhance the scale and relevance of climate information from the global scale (low resolution) to the regional and local level (high resolution) for assessing potential climate impacts among the Member States. The demand and need for climate downscaling at higher resolution are increasing because of its importance in estimating the potential impacts of climate change and will be useful in national planning.
Following are the techniques employed at RIMES
- Dynamical: a nested regional climate model (RCM)
- Statistical: statistical relationships between the large-scale climatic state and local variations derived from historical data records.
- Climate control: Approach for modulating GCM output with high-resolution topographic layers and parameters that act as local climate controls using GIS tools
- Analogue Method: Using examples from historical information to anticipate future extremes of climate states