The nature of Dark Energy, thought to be driving the accelerating expansion of the Universe, is one of the most compelling mysteries in all of science. Determining the equation-of-state of Dark Energy to 1% accuracy is currently a leading goal for many planned cosmological surveys, such as NASA's Wide-Field Infrared Survey Telescope (WFIRST), ESA's Euclid and the Large Synoptic Survey Telescope (LSST). Numerical simulations of structure formation are required to make predictions for these surveys and to help mitigate systematics. My SUNGLASS pipeline (Simulated UNiverses for Gravitational Lensing Analysis and Shear Surveys) is able to produce Monte Carlo suites of numerical simulations and rapidly generates mock weak lensing galaxy shear catalogues. These catalogues are being used to investigate astrophysical systematics, to generate accurate covariance matrices that account for the non-linear nature of the Universe and as an integral part of end-to-end simulation pipelines - each element being essential to the measurement of the Dark Energy equation-of-state to 1% in future telescope missions. In this talk, I will discuss SUNGLASS and its vital role in Dark Energy telescope mission development and analysis.