Predicting the Bz magnetic field embedded within interplanetary coronal mass ejections (ICMEs), also known as the Bz problem, is a key challenge in space weather forecasting. We study the hypothesis that upstream in situ measurements of the sheath region and the first few hours of the magnetic obstacle provide sufficient information for predicting the downstream Bz component. To do so, we develop a predictive tool based on machine learning that is trained and tested on 348 ICMEs from Wind, STEREO‐A, and STEREO‐B measurements. We train the machine learning models to predict the minimum value of the Bz component and the maximum value of the total magnetic field Bt in the magnetic obstacle. To validate the tool, we let the ICMEs sweep over the spacecraft and assess how continually feeding in situ measurements into the tool improves the Bz prediction. We specifically find that the predictive tool can predict the minimum value of the Bz component in the magnetic obstacle with a mean absolute error of 3.12 nT and a Pearson correlation coefficient of 0.71 when the sheath region and the first 4 hr of the magnetic obstacle are observed. While the underlying hypothesis is unlikely to solve the Bz problem, the tool shows promise for ICMEs that have a recognizable magnetic flux rope signature. Transitioning the tool to operations could lead to improved space weather forecasting.

The Colorado Ultraviolet Transit Experiment (CUTE) is a 6U NASA CubeSat carrying on-board a lowresolution (R∼ 2000-3000), near-ultraviolet (2500-3300Å) spectrograph. It has a rectangular primary Cassegrain telescope to maximize the collecting area. CUTE, which is planned for launch in Spring 2020, is designed to monitor transiting extra-solar planets orbiting bright, nearby stars aiming at improving our understanding of planet atmospheric escape and star-planet interaction processes. We present here the CUTE data simulator, which we complemented with a basic data reduction pipeline. This pipeline will be then updated once the final CUTE data reduction pipeline is developed. We show here the application of the simulator to the HD209458 system and a first estimate of the precision on the measurement of the transit depth as a function of temperature and magnitude of the host star. We also present estimates of the effect of spacecraft jitter on the final spectral resolution. The simulator has been developed considering also scalability and adaptability to other missions carrying on-board a long-slit spectrograph. The data simulator will be used to inform the CUTE target selection, choose the spacecraft and instrument settings for each observation, and construct synthetic CUTE wavelength-dependent transit light curves on which to develop the CUTE data reduction pipeline.