One-dimensional nonlinear phononic crystals have been assembled from periodic diatomic chains of stainless steel cylinders alternated with Polytetrafluoroethylene spheres. This system allows dramatic changes of behavior (from linear to strongly nonlinear) by application of compressive forces practically without changes of geometry of the system. The relevance of classical acoustic band-gap, characteristic for chain with linear interaction forces and derived from the dispersion relation of the linearized system, on the transformation of single and multiple pulses in linear, nonlinear and strongly nonlinear regimes are investigated with numerical calculations and experiments. The limiting frequencies of the acoustic band-gap for investigated system with given precompression force are within the audible frequency range (20–20,000 Hz) and can be tuned by varying the particle’s material properties, mass and initial compression. In the linear elastic chain the presence of the acoustic band-gap was apparent through fast transformation of incoming pulses within very short distances from the chain entrance. It is interesting that pulses with relatively large amplitude (nonlinear elastic chain) exhibit qualitatively similar behavior indicating relevance of the acoustic band gap also for transformation of nonlinear signals. The effects of an in situ band-gap created by a mean dynamic compression are observed in the strongly nonlinear wave regime.

Two or more spatio-temporally co-located meteorological/climatological extremes (co-occurring extremes) place far greater stress on human and ecological systems than any single extreme could. This was observed during the California drought of 2011–2015 where multiple years of negative precipitation anomalies occurred simultaneously with positive temperature anomalies resulting in California’s worst drought on observational record. The large-scale drivers which modulate the occurrence of extremes in two or more variables remains largely unexplored. Using California wintertime (November–April) temperature and precipitation as a case study, we apply a novel, nonparametric conditional probability distribution method that allows for evaluation of complex, multivariate, and nonlinear relationships that exist among temperature, precipitation, and various indicators of large-scale climate variability and change. We find that multivariate variability and statistics of temperature and precipitation exhibit strong spatial variation across scales that are often treated as being homogeneous. Further, we demonstrate that the multivariate statistics of temperature and precipitation are highly non-stationary and therefore require more robust and sophisticated statistical techniques for accurate characterization. Of all the indicators of the large-scale climate conditions we studied, the dipole index explains the greatest fraction of multivariate variability in the co-occurrence of California wintertime extremes in temperature and precipitation.

Tree-ring carbon isotope discrimination (Δ¹³C) and oxygen isotopes (δ¹⁸O) collected from white pine (Pinus strobus) trees adjacent to Lake Superior show potential to produce the first winter-specific paleoclimate reconstruction with inter-annual resolution for this region. Isotopic signatures from 1976 to 2015 were strongly linked to antecedent winter minimum temperatures (T_min), Lake Superior peak ice cover, and regional to continental-scale atmospheric winter pressure variability including the North American Dipole. The immense thermal inertia of Lake Superior underlies the unique connection between winter conditions and tree-ring Δ¹³C and δ¹⁸O signals from the following growing season in trees located near the lake. By combining these signals, we demonstrate feasibility to reconstruct variability in T_min, ice cover, and continental-scale atmospheric circulation patterns (r ≥ 0.65, P < 0.001).

With the advent of the Heliophysics/Geospace System Observatory (H/GSO), a complement of multi-spacecraft missions and ground-based observatories to study the space environment, data retrieval, analysis, and visualization of space physics data can be daunting. The Space Physics Environment Data Analysis System (SPEDAS), a grass-roots software development platform (www.spedas.org), is now officially supported by NASA Heliophysics as part of its data environment infrastructure. It serves more than a dozen space missions and ground observatories and can integrate the full complement of past and upcoming space physics missions with minimal resources, following clear, simple, and well-proven guidelines. Free, modular and configurable to the needs of individual missions, it works in both command-line (ideal for experienced users) and Graphical User Interface (GUI) mode (reducing the learning curve for first-time users). Both options have "crib-sheets," user-command sequences in ASCII format that can facilitate record-and-repeat actions, especially for complex operations and plotting. Crib-sheets enhance scientific interactions, as users can move rapidly and accurately from exchanges of technical information on data processing to efficient discussions regarding data interpretation and science. SPEDAS can readily query and ingest all International Solar Terrestrial Physics (ISTP)-compatible products from the Space Physics Data Facility (SPDF), enabling access to a vast collection of historic and current mission data. The planned incorporation of Heliophysics Application Programmer's Interface (HAPI) standards will facilitate data ingestion from distributed datasets that adhere to these standards. Although SPEDAS is currently Interactive Data Language (IDL)-based (and interfaces to Java-based tools such as Autoplot), efforts are under-way to expand it further to work with python (first as an interface tool and potentially even receiving an under-the-hood replacement). We review the SPEDAS development history, goals, and current implementation. We explain its "modes of use" with examples geared for users and outline its technical implementation and requirements with software developers in mind. We also describe SPEDAS personnel and software management, interfaces with other organizations, resources and support structure available to the community, and future development plans.

Electronic supplementary material

The online version of this article (10.1007/s11214-018-0576-4) contains supplementary material, which is available to authorized users.