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A new experiment for the mesurement of the magnetic moment and the g-factor of the Helium-3 nucleus is currently unter construction at the Max Planck Institute for Nuclear Physics. 3He+ as well as 3He2+ will be investigated in a speci_cally designed Penning trap. The relative uncertainty of these measured values shall be 1 ppb or better. To achieve this level of precision, very stable experimental parameters are required. Therefore external disturbance of the Penning trap's high magnetic field should be shielded by a specific coil. To use the magentic ux conservation in superconducting circuits, the geometry of the coil was in the context of this thesis optimized and its ideal length was estimated. The accordingly constructed self shielding coil was then testet using a cold head and a shielding factor of S = 52 +/- 4 as well as a good spatial stability of it was verfied. Because these results were effected by the use of an inhomogeneous external field, the coil was subsequently tested after installing it into the superconducting magnet with an ion stored in a Penning trap. Here the high shielding factor of the magnet itself caused difficulties. The final result S = 78 +∞-74 is inaccurate, but still good shielding characteristics and therefore an integral part of the magnetic field stability of the 3He-experiment was ensured.

While weather forecasting models can be tested by performing and evaluating many hindcasts, the limited observational record restricts the degree to which climate projections can be evaluated. Therefore a question of interest is: to what degree can we evaluate the potential skill of a climate model's response to forcing by assessing the reliability of short‐range weather and seasonal forecasts produced by the same model? We address this question using a dynamical systems framework. We use linear response theory to provide the mean climate response of a general dynamical system to a small external forcing. We relate this response to the reliability of initial value forecasts. We find that, in order to capture the mean climate response, the forecast model must correctly represent the slowest evolving modes of variability in the system. The reliability of forecasts on seasonal and longer time‐scales, which is sensitive to the representation of these slow modes, could therefore indicate if the forecast model has the correct climate sensitivity and so will respond correctly to an applied external forcing. In this way, the skill of initialized forecasts could act as an ‘emergent constraint’ on climate sensitivity. However, we also highlight that unreliable seasonal forecasts do not necessarily indicate an incorrect climate projection. This is because correctly representing rapidly evolving modes is also necessary for reliable seasonal forecasts.