%0 Generic %A Myerscough, Keith W. %A Frank, Jason %A Leimkuhler, Benedict %D 2017 %T highest_e1_d-1_HJ_Lagrange_long.mat from Observation-based correction of dynamical models using thermostats %U https://rs.figshare.com/articles/dataset/highest_e1_d-1_HJ_Lagrange_long_mat_from_Observation-based_correction_of_dynamical_models_using_thermostats/4524758 %R 10.6084/m9.figshare.4524758.v1 %2 https://ndownloader.figshare.com/files/7320956 %K sampling %K statistical estimation %K thermostat %K statistical fluid dynamics %X Models used in simulation may give accurate short-term trajectories but distort long-term (statistical) properties. In this work, we augment a given approximate model with a control law (a ‘thermostat’) that gently perturbs the dynamical system to target a thermodynamic state consistent with a set of prescribed (possibly evolving) observations. As proof of concept, we provide an example involving a point vortex fluid model on the sphere, for which we show convergence of equilibrium quantities (in the stationary case) and the ability of the thermostat to dynamically track a transient state. %I The Royal Society