Abstract: We first demonstrate the embedding of a Gaussian Process emulator of high resolution convection processes within a coarse climate numerical model. It leads to a reduction of some of the well know biases in climate modelling. We then present a new type of emulator of any feed forward multi-physics system, by linking GP emulators of individual simulators, with large gains over the composite emulator of the whole system. The Deep Gaussian Process (DGP) is then presented as a surrogate that shares the structure of the linked emulator but enables the emulation of highly non-linear simulators without the knowledge of individual sub-processes. We then examine sharp changes in the outputs a computer simulator. These often indicate bifurcations or critical transitions within the investigated system, e.g. laminar v. turbulent behavior in fluid dynamics. An efficient approach that localizes these changes using DGPs with a minimal number of evaluations is introduced. We demonstrate the efficacy and efficiency of the proposed framework on the Rayleigh–Bénard convection.