From Perturbed Parameter Ensemble of a Global Climate Model to Glacier Streamflow Modeling
This is a two-part presentation with two separate topics, presented by Trude Eidhammer from National Center for Atmospheric Research (NCAR), USA.
1) Efficient and accurate model parameter estimation is a challenge in many different climate research groups. There has been renewed interest in parameter estimation methods, in part due to recent scientific advancements in computational capacity and machine learning. For example, to evaluate parameterizations in models, simulations have often been performed with only one change to one parameterization at the time. This is highly inefficient and can be both time-consuming and computationally costly. Here she will present results from a Perturbed Parameter Ensemble (PPE) using CESM-CAM6, where the parameter values are determined with the Latin Hypercube sampling technique. Utilizing the Latin hypercube sampling technique reduces the needed number of ensembles, while making sure the entire parameter space is used. Machine learning can then be used to fill out the density of parameter combinations to evaluate their impacts on climate related model outputs.
2) A detailed, physically based one dimensional, column snowpack model (Crocus)¬ has been incorporated into the hydrological model WRF-Hydro. This allows for direct surface mass balance simulation of glaciers and subsequent modeling of meltwater discharge from glaciers. This new system (WRF-Hydro/Glacier) has been successfully evaluated over a glacier in Southern Norway (Hardangerjøkulen). The WRF-Hydro/Glacier system reproduced the glacier surface winter/summer and net mass balance, snow depth, surface albedo and glacier runoff well compared to observations. The improved estimation of albedo has an appreciable impact on the discharge from the glacier during late summer. The WRF-Hydro/Glacier system has recently been implemented into the National Water Model system version to run over Alaska at 1 km grid spacing. Along with evaluation of WRF-Hydro/Glacier over Hardangerjøkulen, results from simulations over Alaska will be shown.
Ice Flow as an Indicator of Ice Thickness?
Elana Reilly (UiB) will present her master's thesis «Ice Flow as an Indicator of Ice Thickness?»
Her advisors are Dr. Basile de Fleurian, Professor Kerim H. Nisancioglu and Professor Emeritus John Inge Svendsen. The sensor committee consists of Professor Jakob C. Yde (HVL Sogndal) and Professor Andreas Bron (Department of Biological Sciences, UiB).