John received his Ph.D. from the Department of Hydrology and Water Resources at the University of Arizona work in the NASA PARCA program evaluating accumulation variability over the Greenland Ice Sheet. For over 15 years John has been working with Arctic system processes focused on hydrologic and geophysical systems, atmospheric pollutants, and climate forcing variables. His primary research topics are focused on coupling energy transport and climate variability with global hydrologic cycling and dynamics in cryospheric systems. He is currently a professor in the Department of Geosciences at the Unversity of Oslo.
Abstract:
Hydrologic simulation is replete with challenges related to aspects regarding paucity of observational records, choice of model configuration, and availability of forcing data sets. Together, these challenges create significant uncertainty in hydrologic prediction. Shyft is a modeling toolbox that is community developed with the intention of providing tools to not only reduce, but also assess the inherent uncertainty in model simulations. Given the importance of water resources for society, it is critical that hydrologic scientists provide more robust tools for the prediction of climate impacts on water availability. Shyft is a tool developed for the community, open source and freely available, the aim of the software is to provide a toolbox that can be further developed while maintaining high standards and capabilities for operational implementation.