Modeled integrated responses of ppERK1 and ppERK2 of normal and elevated ERK1 and ERK2 levels (Figure 5b)

The present dataset contain source data for Figure 5b from Schilling et al., 2009. Cell fate decisions are regulated by the coordinated activation of signalling pathways such as the extracellular signal-regulated kinase (ERK) cascade, but contributions of individual kinase isoforms are mostly unknown. The authors combined quantitative data from erythropoietin-induced pathway activation in primary erythroid progenitor (colony-forming unit erythroid stage, CFU-E) cells with mathematical modelling, in order to predict and experimentally confirmed a distributive ERK phosphorylation mechanism in CFU-E cells. The authors found evidences that double-phosphorylated ERK1 attenuates proliferation beyond a certain activation level, whereas activated ERK2 enhances proliferation with saturation kinetics. They show integrated responses of double-phosphorylated ERK1 and ERK2 that were calculated for different Epo concentrations for the original model as well as for models with elevated ERK1 or ERK2 levels.

Sea ice thickness distribution (ITD) Model for the Arctic, links to NetCDF files

Sea ice models contain many different parameterizations of which one of the most commonly used is a subgrid-scale ice thickness distribution (ITD). The effect of this model component and the associated ice strength formulation on the reproduction of observed Arctic sea ice is assessed. To this end the model's performance in reproducing satellite observations of sea ice concentration, thickness and drift is evaluated. For an unbiased comparison, different model configurations with and without an ITD are tuned with an automated parameter optimization. The original combination of ITD and ice strength parameterization does not lead to better results than a simple single category model. Yet changing to a simpler ice strength formulation, which depends linearly on the mean ice thickness across all thickness categories, allows to clearly improve the model-data misfit when using an ITD. In the original formulation, the ice strength depends strongly on the number of thickness categories, so that introducing more categories can lead to thicker albeit weaker ice on average.