Assessment of add-value of dynamical downscaling in Japan

Climate effects caused by human activities will continue for centuries and natural climate influences have always been a risk. Mitigation is a complex, uncertain approach and will need at least several decades. It is necessary, therefore, to put adaptation together immediately. The impacts and potential applications of interest to the stakeholders are mostly at regional and local scales as the essential resources of water, food, energy, human health, and ecosystem function respond to regional and local climate. Users of climate scenarios produced by global climate models with coarse grid-spacing involve an inadequate mismatch of spatial scale. Downscaling technique is used to obtain the regional climate scenarios, especially in regions of complex topography, coastlines, and in regions with highly heterogeneous land surface covers where those results are highly sensitive to fine spatial scale climate processes. Dynamical and statistical downscaling techniques available for generating regional climate information have the respective strengths and weaknesses. We quantified the confidence and uncertainties of Type-2, Type-3, and Type-4 dynamical downscaling where the lateral and bottom boundary conditions were obtained from Japanese 25-year ReAnalysis (JRA-25), AGCM (AMIP run) and CGCM (CMIP run) respectively. We assessed the value (skill) added by the downscaling to a climate simulation in Japan and regional future changes. Based on the lesson learning from the multi-downscaling project in Japan (S5-3), “added value” and "predictability" of downscaling and new research programs of "Research Program on Climate Change Adaptation (RECCA)" and "Program for Risk Information on Climate Change" to provide scientific knowledge for sustainable development by adapting to climate change is discussed.