Proceedings of the 2015 Winter Simulation Conference L. Yilmaz, W. K. V. Chan, I. Moon, T. M. K. Roeder, C. Macal, and M. D. Rossetti, eds. WHERE DOES COMPUTATIONAL MODELING OF CLIMATE-INDUCED MIGRATION STAND AND WHAT CHALLENGES STILL NEED TO BE OVERCOME Charlotte Till Arizona State University 900 S. Cady Mall Tempe, AZ 85287-2402, USA Jamie Haverkamp University of Maine 5773 S Stevens Hall Orono, ME 04469, USA Devin White, Budhendra Bhaduri Oak Ridge National Laboratory 1 Bethel Valley Road Oak Ridge, TN 37831, USA ABSTRACT Climate change has the potential to displace large populations in many parts of the developed and devel- oping world. Understanding why, how, and when migrants decide to move is critical to successful plan- ning within national and international organizations. Computational modeling techniques are one way to explore planning options and investigate consequences in simulated digital environments. While model- ing is a powerful tool, it presents both opportunities and challenges both for model consumers, and the teams who create them. This poster seeks to lay a foundation for both groups. It does so by providing an overview of pertinent climate-induced migration research, describing different types of models, how to select the most relevant one(s) for your problem, highlighting three different perspectives on how to ob- tain data to use in said model(s). Finally two attempted projects will illustrate the challenges of this work and how they can be overcome. 1 LITERATURE OVERVIEW Projected climate change scenarios could become catalysts for conflict that in turn could worsen security risks both nationally and internationally (Board, 2014). Such conflicts will impact many areas including infrastructure, access to resources, quality of life, and will range in scale and severity. The types of infor- mation required to explore these challenges do not currently exist consistently on large enough scales. Undaunted, a growing number of researchers are starting to contribute work, and a number are imple- menting computational approaches. There is no right answer when it comes to computational modeling of complex systems, only groupings of possibilities to be explored. Contributions by social scientists bring critically needed perspectives about different climate-change-related issues (Agrawal et al., 2012). Over the past 20 years the number of publications addressing climate-related human migration is increasing. This is encouraging: the questions being asked are becoming more involved, the methods implemented to address them are broadening, and there is now demand for new tools to be developed to continue gains. Publications range from small-scale efforts right the way through to massive international undertakings. Researchers, interest groups, and stakeholders are coming together and realizing we really do not know how climate change-migration systems work, and it is well past time we did. 2 WHICH MODEL SHOULD BE IMPLEMENTED? The adoption of computational modeling and simulation by the social sciences is a relatively new phe- nomenon, only now gaining some acceptance 20 years after its first implementations. A recent publication by Kelly et al (2013) summarizes five commonly used computational approaches: 1) Systems Dynamics, 2) Bayesian networks, 3) Coupled Component Models, 4) Agent-Based Models and 5) Knowledge-Based Models (also known as Expert Systems). Before any approach is chosen researchers should ask three questions: What is the purpose of the model? What types of data are available to develop and specify the model? And, who are the model users? Depending on the answer to these questions, and more, some ap- 3230 978-1-4673-9743-8/15/$31.00 ©2015 IEEE