We present a first-principles-based coronal mass ejection (CME) model suitable for both scientific and operational purposes by combining a global magnetohydrodynamics (MHD) solar wind model with a flux rope-driven CME model. Realistic CME events are simulated self-consistently with high fidelity and forecasting capability by constraining initial flux rope parameters with observational data from GONG, SOHO/LASCO, and STEREO/COR. We automate this process so that minimum manual intervention is required in specifying the CME initial state. With the newly developed data-driven Eruptive Event GeneratorGibson-Low (EEGGL), we present a method to derive Gibson-Low (GL) flux rope parameters through a handful of observational quantities so that the modeled CMEs can propagate with the desired CME speeds near the Sun. A test result with CMEs launched with different Carrington rotation magnetograms are shown. Our study shows a promising result for using the first-principles-based MHD global model as a forecasting tool, which is capable of predicting the CME direction of propagation, arrival time, and ICME magnetic field at 1 AU (see companion paper by Jin et al. 2016b). Subject headings: interplanetary medium -magnetohydrodynamics (MHD)methods: numerical -solar wind -Sun: corona -Sun: coronal mass ejections (CMEs)

The Comprehensive Assessment of Models and Events using Library Tools (CAMEL) framework leverages existing Community Coordinated Modeling Center services: Run‐on‐Request postprocessing tools that generate model time series outputs and the new Community Coordinated Modeling Center Metadata Registry that describes simulation runs using Space Physics Archive Search and Extract metadata. The new CAMEL visualization tool compares the modeled time series with observational data and computes a suite of skill scores such as Prediction Efficiency, Root‐Mean‐Square Error, and Symmetric Signed Percentage Bias. Model‐data pairs used for skill calculations are obtained considering a user‐selected maximum difference between the time of observation and the nearest model output. The system renders available data for all locations and time periods selected using interactive visualizations that allow the user to zoom, pan, and pick data values along traces. Skill scores are reported for each selected event or aggregated over all events for all participating model runs. Separately, scores are reported for all locations (satellites or stations) and for each location individually. We are building on past experiences with model‐data comparisons of magnetosphere and ionosphere model outputs from GEM2008, GEM‐CEDAR Electrodynamics Thermosphere Ionosphere, and the SWPC Operational Space Weather Model challenges. The CAMEL visualization tool is demonstrated using three validation studies: (a) Wang‐Sheeley‐Arge heliosphere simulations compared against OMNI solar wind data, (b) ground magnetic perturbations from several magnetosphere and ionosphere electrodynamics models as observed by magnetometers, and (c) electron fluxes from several ring current simulations compared to Radiation Belt Storm Probes Helium Oxygen Proton Electron instrument measurements, integrated over different energy ranges.

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One of the critical challenges for large area cadmium zinc teUuride (CdZnTe) detector arrays is obtaining material capable of uniform imaging and spectroscopic response. Two complementary nondestructive techniques for characterizing bulk CdZnTe have been developed to identify material with a uniform response. The first technique, infrared transmission imaging, allows for rapid visualization of bulk defects. The second technique, x-ray spectral mapping, provides a map of the material spectroscopic response when it is configured as a planar detector. The two techniques have been used to develop a correlation between bulk defect type and detector performance. The correlation allows for the use of infrared imaging to rapidly develop wafer mining maps. The mining of material free of detrimental defects has the potential to dramatically increase the yield and quality of large area CdZnTe detector arrays.

Progress in space weather research and awareness needs community-wide strategies and procedures to evaluate our modeling assets. Here we present the activities of the Ambient Solar Wind Validation Team embedded in the COSPAR ISWAT initiative. We aim to bridge the gap between model developers and end-users to provide the community with an assessment of the state-of-the-art in solar wind forecasting. To this end, we develop an open online platform for validating solar wind models by comparing their solutions with in situ spacecraft measurements. The online platform will allow the space weather community to test the quality of state-of-the-art solar wind models with unified metrics providing an unbiased assessment of progress over time. In this study, we propose a metadata architecture and recommend community-wide forecasting goals and validation metrics. We conclude with a status update of the online platform and outline future perspectives.