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Heliophysics model outputs are increasingly accessible, but typically are not usable by the majority of the community unless directly collaborating with the relevant model developers. Prohibitive factors include complex file output formats, cryptic metadata, unspecified and often customized coordinate systems, and non-linear coordinate grids. Some pockets of progress exist, giving interfaces to various simulation outputs, but only for a small set of outputs and typically not with open-source, freely available packages. Additionally, the increasing array of tools built upon these sporadic interfaces are typically model-specific. We present Kamodo’s model-agnostic satellite flythrough capabilities as the solution to the utilization barrier for heliophysics model outputs. Developed at the Community Coordinated Modeling Center, these flythrough capabilities are built in Python upon a network of model-agnostic interfaces developed in collaboration with model developers, providing interpolation results the community can trust. Kamodo’s flythrough capabilities present the user with a growing variety of flythrough tools based upon a rapidly expanding library of heliophysics model outputs in several domains, currently including a variety of Ionosphere-Thermosphere-Mesosphere and global magnetosphere model outputs. Each capability is designed to be easily accessible via simplistic model-agnostic syntax, with the entire package freely available in the cloud on Github. Here, we describe the tools developed, include several sample applications for common science questions, demonstrate interoperability with selected packages, and summarize ongoing developments.

We propose a system to analyze and contextualize simulations of coronal mass ejections. As current simulation techniques require manual input, uncertainty is introduced into the simulation pipeline leading to inaccurate predictions that can be mitigated through ensemble simulations. We provide the space weather analyst with a multi-view system providing visualizations to: 1. compare ensemble members against ground truth measurements, 2. inspect time-dependent information derived from optical flow analysis of satellite images, and 3. combine satellite images with a volumetric rendering of the simulations. This three-tier workflow provides experts with tools to discover correlations between errors in predictions and simulation parameters, thus increasing knowledge about the evolution and propagation of coronal mass ejections that pose a danger to Earth and interplanetary travel.

[1] In this paper we describe a coupled model of Earth's magnetosphere that consists of the Lyon-Fedder-Mobarry (LFM) global magnetohydrodynamics (MHD) simulation, the MIX ionosphere solver and the Rice Convection Model (RCM) and report some results using idealized inputs and model parameters. The algorithmic and physical components of the model are described, including the transfer of magnetic field information and plasma boundary conditions to the RCM and the return of ring current plasma properties to the LFM. Crucial aspects of the coupling include the restriction of RCM to regions where field-line averaged plasma-β≤ 1, the use of a plasmasphere model, and the MIX ionosphere model. Compared to stand-alone MHD, the coupled model produces a substantial increase in ring current pressure and reduction of the magnetic field near the Earth. In the ionosphere, stronger region-1 and region-2 Birkeland currents are seen in the coupled model but with no significant change in the cross polar cap potential drop, while the region-2 currents shielded the low-latitude convection potential. In addition, oscillations in the magnetic field are produced at geosynchronous orbit with the coupled code. The diagnostics of entropy and mass content indicate that these oscillations are associated with low-entropy flow channels moving in from the tail and may be related to bursty bulk flows and bubbles seen in observations. As with most complex numerical models, there is the ongoing challenge of untangling numerical artifacts and physics, and we find that while there is still much room for improvement, the results presented here are encouraging.

The optical properties of periodic and nonperiodic arrays of aligned multiwalled carbon nanotubes are presented. Experimental analysis indicates a complex optical response that is attributed to both the individual carbon nanotube scatterers and also to the array ensembles. These studies indicate that by controlling the geometry and spacing of the arrays, it is possible to create structures that respond very strongly to specific wavelengths or bands of wavelengths. Structures such as these may form the basis for numerous applications in energy conversion. This would include highly efficient solar energy conversion as well as sensitive, finely tuned detectors that can respond to predetermined wavelength bands ranging from the ultraviolet to the infrared region. Experimental, theoretical and modeled results are discussed as they apply to these applications. Challenges and issues are discussed.

Spectroscopic observations are presented for carbon nanotubes grown on silicon and quartz substrates in a hexagonal honeycomb configuration using self-assembly nanosphere lithography and plasma enhanced chemical vapor deposition method. A white light source is used as an incident beam and light reflected from the surface of the carbon nanotubes results in a distinctive signature in the reflected spectrum. A comparison of non-periodic arrays and periodic arrays of carbon nanotubes show that the reflectance signature is only observed when the carbon nanotubes are oriented in a periodic array. Further observations regarding the light antenna effect observed in nonperiodic arrays are also reported. Theoretical curves show good agreement to experimentally observed phenomena. The unique optical properties of the arrays combined with the excellent mechanical and electrical properties of carbon nanotubes indicate that these materials may find many uses in the field of optoelectronics.