Spatial Drift Dynamics of Shovelnose Sturgeon and Pallid Sturgeon Prelarvae in the Transition Zone of Ft. Peck Reservoir

Habitats in reservoir headwaters may cause high mortality of sturgeon prelarvae. Short inter-reservoir reaches export drifting prelarvae from hatch locations into reservoirs. However, flooded vegetation could entrain prelarvae. We used 2 day post hatch (dph) shovelnose sturgeon (Scaphirhynchus platorynchus) and 1-dph pallid sturgeon (Scaphirhynchus albus) to determine the spatial dynamics of drifting prelarvae.We released 220,000 2-dph shovelnose sturgeon 4 km upstream of Ft. Peck Reservoir and 135,000 1-dph pallid sturgeon 2.5 km upstream of the reservoir the following day. We recaptured shovelnose sturgeon prelarvae with nets deployed along three transects of the transition zone and within the headwaters of the reservoir.We sampled 5148.2 m3 of water and recaptured 323 prelarval shovelnose sturgeon for a recapture rate of 0.14 percent. Fifty-nine percent of recaptured prelarvae were recaptured from the thalweg, 12 percent from the flooded vegetation-main channel interface, 9 percent from the channel border, and 19 percent from the zero-velocity area of Ft. Peck Reservoir. We recaptured pallid sturgeon prelarvae with nets deployed along one transect of the transition zone and within the headwaters of the reservoir. We sampled 6608.5 m3 of water and recaptured 397 pallid sturgeon prelarvae for a recapture rate of 0.29 percent. Twenty one percent of prelarvae were recaptured within the thalweg, 0.25 percent were recaptured along the channel margins, and 79 percent from the zero-velocity area of Ft. Peck Reservoir. Although recapture rates were low, the majority of prelarvae were captured in the thalweg and transported to the headwaters of Ft. Peck Reservoir. The drift dynamics observed in this study provide a springboard for further research

Ensemble downscaling in coupled solar wind-magnetosphere modeling for space weather forecasting

Advanced forecasting of space weather requires simulation of the whole Sun-to-Earth system, which necessitates driving magnetospheric models with the outputs from solar wind models. This presents a fundamental difficulty, as the magnetosphere is sensitive to both large-scale solar wind structures, which can be captured by solar wind models, and small-scale solar wind “noise,” which is far below typical solar wind model resolution and results primarily from stochastic processes. Following similar approaches in terrestrial climate modeling, we propose statistical “downscaling” of solar wind model results prior to their use as input to a magnetospheric model. As magnetospheric response can be highly nonlinear, this is preferable to downscaling the results of magnetospheric modeling. To demonstrate the benefit of this approach, we first approximate solar wind model output by smoothing solar wind observations with an 8 h filter, then add small-scale structure back in through the addition of random noise with the observed spectral characteristics. Here we use a very simple parameterization of noise based upon the observed probability distribution functions of solar wind parameters, but more sophisticated methods will be developed in the future. An ensemble of results from the simple downscaling scheme are tested using a model-independent method and shown to add value to the magnetospheric forecast, both improving the best estimate and quantifying the uncertainty. We suggest a number of features desirable in an operational solar wind downscaling scheme

Influences of various magnetospheric and ionospheric current systems on geomagnetically induced currents around the world

Ground-based observations of geomagnetic field (B field) are usually a superposition of signatures from different source current systems in the magnetosphere and ionosphere. Fluctuating B fields generate geoelectric fields (E fields), which drive geomagnetically induced currents (GIC) in technological conducting media at the Earth's surface. We introduce a new Fourier integral B field model of east/west directed line current systems over a one-dimensional multilayered Earth in plane geometry. Derived layered-Earth profiles, given in the literature, are needed to calculate the surface impedance, and therefore reflection coefficient in the integral. The 2003 Halloween storm measurements were Fourier transformed for B field spectrum Levenberg-Marquardt least squares inversion over latitude. The inversion modeled strengths of the equatorial electrojets, auroral electrojets, and ring currents were compared to the forward problem computed strength. It is found the optimized and direct results match each other closely and supplement previous established studies about these source currents. Using this model, a data set of current system magnitudes may be used to develop empirical models linking solar wind activity to magnetospheric current systems. In addition, the ground E fields are also calculated directly, which serves as a proxy for computing GIC in conductor-based networks

Exploring predictive performance: A reanalysis of the geospace model transition challenge

The Pulkkinen et al. (2013) study evaluated the ability of five different geospace models to predict surface dB/dt as a function of upstream solar drivers. This was an important step in the assessment of research models for predicting and ultimately preventing the damaging effects of geomagnetically induced currents. Many questions remain concerning the capabilities of these models. This study presents a reanalysis of the Pulkkinen et al. (2013) results in an attempt to better understand the models’ performance. The range of validity of the models is determined by examining the conditions corresponding to the empirical input data. It is found that the empirical conductance models on which global magnetohydrodynamic models rely are frequently used outside the limits of their input data. The prediction error for the models is sorted as a function of solar driving and geomagnetic activity. It is found that all models show a bias toward underprediction, especially during active times. These results have implications for future research aimed at improving operational forecast models.Key PointsGeospace models of dB/dt frequently underpredict dB/dtOf five models tested, the SWMF is least likely to underpredict dB/dtEmpirical conductance models used by global MHD are frequently used outside their range of validityPeer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/136305/1/swe20406.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/136305/2/swe20406_am.pd

Atypical Neurophysiology Underlying Episodic and Semantic Memory in Adults with Autism Spectrum Disorder

Individuals with autism spectrum disorder (ASD) show atypicalities in episodic memory (Boucher et al. in Psychological Bulletin, 138 (3), 458-496, 2012). We asked participants to recall the colours of a set of studied line drawings (episodic judgement), or to recognize line drawings alone (semantic judgement). Cycowicz et al. (Journal of Experimental Child Psychology, 65, 171-237, 2001) found early (300 ms onset) posterior old-new event-related potential effects for semantic judgements in typically developing (TD) individuals, and occipitally focused negativity (800 ms onset) for episodic judgements. Our results replicated findings in TD individuals and demonstrate attenuated early old-new effects in ASD. Late posterior negativity was present in the ASD group, but was not specific to this time window. This non-specificity may contribute to the atypical episodic memory judgements characteristic of individuals with ASD

Geomagnetically induced currents: science, engineering, and applications readiness

This paper is the primary deliverable of the very first NASA Living With a Star Institute Working Group, Geomagnetically Induced Currents (GIC) Working Group. The paper provides a broad overview of the current status and future challenges pertaining to the science, engineering, and applications of the GIC problem. Science is understood here as the basic space and Earth sciences research that allows improved understanding and physics-based modeling of the physical processes behind GIC. Engineering, in turn, is understood here as the “impact” aspect of GIC. Applications are understood as the models, tools, and activities that can provide actionable information to entities such as power systems operators for mitigating the effects of GIC and government agencies for managing any potential consequences from GIC impact to critical infrastructure. Applications can be considered the ultimate goal of our GIC work. In assessing the status of the field, we quantify the readiness of various applications in the mitigation context. We use the Applications Readiness Level (ARL) concept to carry out the quantification