Currently, there is scientific consensus that higher spatial resolution also increases the accuracy of models that model the effects of climate change; however, to what extent is still largely unknown. Higher spatial resolution typically comes at a high price in terms of computational time and hardware requirements. It is therefore of utmost importance to better understand what higher resolutions actually bring in terms of new insights for modeling climate change impacts.
We will use the coarse resolution standard dataset (W5E5) for climate change impact models. A variety of models examining climate change impacts have already been computed using this data as a baseline. This has the advantage that data from several models with a coarse resolution are already available. The W5E5 dataset is scaled to 1km spatial resolution using the CHELSA methodology.
Models already computed at coarse resolution will then be additionally computed again at high spatial resolution to allow direct comparison of the effects of high resolution in a standardized comparison. We will compare the results of different models computed at either low or high spatial resolution, and investigate the performance improvement of increasing the spatial resolution of important environmental variables such as temperature, or precipitation in climate impact models.
Models that capture the impacts of climate change are often already established in their specific disciplines. However, cross-disciplinary comparisons are still lacking, and many questions remain about how confident we are in estimating climate change impacts on natural and human-dominated systems. Given the current pace of climate change, some of these questions will need to be answered fairly soon. While scientific expectations for high-resolution climate data for climate impact models are high, we still do not know the extent to which increasingly high-resolution models can actually better estimate climate change impacts. Answering this question will provide new insights into how best to mitigate or adapt to climate change in the future.
Using COST action instruments to link the work packages. The core analysis will be done at WSL. Through short scientific missions, climate change impact models from two other institutions will be integrated into the study. By conducting a workshop at the ISIMIP meeting we will additionally reach out to the larger impact modelling community.
Aside from the terrestrial biodiversity models, we will run three additional climate change impact models which are implemented at our collaboration institutions. Each of these three models is already implemented at the respective institution and runs can be implemented in a short time, as only a change in the climate forcing data is needed in this case. We will use the scientific short mission instrument from within the COST action PROCLIAS to fund short trips of the requested postdoc to these institutions to work together with the respective institution on the implementation of the respective model. Two such short missions are planned, one to work on LPJ-GUESS at BikF in Frankfurt, and one to the PIK in Potsdam to work on the 4C forest model and the SWIM hydrological model.
2022 - 2023