DSSAT is widely used to simulate the potential impacts of environmental factors on agricultural and natural ecosystems. An especially active area of application is in understanding the potential impacts of climate change. Simulations have been a major data source for Intergovernmental Panel on Climate Change (IPCC) assessments for agriculture (Gitay et al., 2001; Easterling et al., 2007). As early as the second IPCC assessment report, extensive use was made of crop growth modeling (Reilly et al., 1996). More recently, DSSAT models have been widely used by members of the Agricultural Modeling Intercomparison and Improvement Project (AgMIP), whose research has contributed to more recent IPCC and related assessments.

Ignoring whether a given model realistically simulations production for a given environment and suite of management practices, the mechanics of simulating crop responses to specific changes in temperature, CO2 or other abiotic factors may appear straightforward: one provides the model with initial field conditions (e.g., for soil moisture and nitrogen status), crop information (cultivar characteristics, planting arrangement, and fertilization and irrigation, if any), and the daily weather and [CO2] data corresponding to the historic, current or future scenarios of interest; the simulation is then run, and the outputs are compared to those of other simulations where different initial conditions, management practices, or weather and [CO2] scenarios were used.

In practice, simulating impacts of climate change involves numerous issues of data availability and quality and of scaling from global climate change data to the plot scale, where crop models typically operate. Furthermore, models have limitations relating to processes they consider, contrasting with the real-world complexity of cropping systems.