Interest in the emergence of graminoid vegetation as a dominant ecosystem type across Alaska has recently increased. This is due to both analysis of remotely sensed vegetation products and anecdotal observations from field work. This work serves as a component of a larger effort to provide a framework for the iterative interaction of data collection and simulation modeling. This framework is a means to the end of quantitatively characterizing and testing hypotheses about the linkages among climate, fire and grassland vegetation in Alaskan ecosystems. We use the Kanuti National Wildlife Refuge as a test domain to analyze and implement information from historical data on fire, climate and vegetation. This information is then implemented into the ALFRESCO modeling framework to develop a novel grassland frame. This new model version is then calibrated using the historical data. The most novel result from this work is that anomalously high post-fire dominance by graminoid vegetation appears to be correlated with anomalously high precipitation in the years following fire events. This result is based on very limited data; however it does provide an interesting juxtaposition to the previously developed conceptual model. Future work will focus on the analysis of similar datasets for other regions within Alaska in order to determine if this post-fire climatic signature is robust. The modeling framework developed here allows for a relatively simple assimilation of new data to inform the interactions among fire, climate and graminoid vegetation in Alaska.