Using Idealized GCM Simulations to Reconstruct and Interpret Past Precipitation Change

Thursday, 18 December 2014
Michael P Erb1, Charles S Jackson1, Anthony J Broccoli2 and David W Lea3, (1)University of Texas, Institute for Geophysics, Austin, TX, United States, (2)Rutgers University New Brunswick, New Brunswick, NJ, United States, (3)UCSB, Santa Barbara, CA, United States
Climate changes over the past few million years have been driven by a variety of concurrent forcings, such as changes in orbit, greenhouse gas concentrations, and growth and decay of ice sheets, among others. However, understanding the precise roles of each of these forcings in driving aspects of the climate system, such as tropical precipitation, can be difficult to determine from snapshot simulations or proxy records alone. To better investigate the roles of each forcing in influencing tropical precipitation, and to investigate the degree to which past changes may be regarded as a linear combination of responses to individual forcings, idealized simulations are run with the GFDL CM2.1, a coupled atmosphere-ocean GCM, to isolate the climate response to each forcing. By scaling and combining these idealized simulations, linear reconstructions of past climate can be made. Comparison of these linear reconstructions with snapshot simulations at the mid-Holocene and last glacial maximum show that the linear reconstructions do a reasonable job approximating many aspects of tropical precipitation change in the model, although some mismatches do exist. In regions where a linear reconstruction does a good job replicating precipitation changes, the components of the reconstruction can offer insight into the mechanisms driving the change. Monsoons are well captured by the linear reconstructions, and respond strongly to precession at the mid-Holocene and greenhouse gases and ice sheets at the LGM. The idealized simulations help isolate the influence of each forcing so that cause and effect relationships may be more easily explored. Linear reconstructions can also be compared against tropical proxy records to help test hypotheses of past precipitation change.