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With support from the U.S. Department of Energy (DOE) Solar Energy Technologies Office (SETO), the National Renewable Energy Laboratory (NREL) partnered with Peak Reliability to evaluate the impact of the August 21, 2017 total solar eclipse on the reliability and grid operations in the Western Electricity Coordinating Council (WECC) territory.
Abstract This paper presents a comparison of modeled and measured electron densities for the 21 August 2017 solar eclipse across the USA. The location of the instrument was (43.81°N, 247.32°E) where the maximum obscuration of 99.6% occurred at 17.53 hr UT on 21 August. The solar apparent time was 9.96 hr, and the duration of the eclipse was 2.7 hr. It was found that if it is assumed that there are no chromosphere emissions at totality, ~30% coronal emission remaining at totality gave the best fit to the electron density variation at 150 km. The 30% coronal emission estimate has uncertainties associated with respect to uncertainties in the solar spectrum, the measured electron density, and the amount of chromosphere emissions remaining at totality. The agreement between the modeled and measured electron densities is excellent at 150 km with the assumed 30% coronal emission at totality. At other altitudes, the agreement is very good, but the altitude profile would be improved if the model peak electron density ( N m F 2 ) decayed more slowly to better match the data. The minimum N m F 2 in the model occurs ~10 min after totality when it decreases to 0.55 from its noneclipse value. The minimum of the N m F 2 data occurs between 6 and 10 min after totality but is ~15% larger. The total electron content decreases to 0.65 of its preeclipse value. These relative changes agree well with those predicted by others prior to the eclipse.
With support from the U.S. Department of Energy (DOE) Solar Energy Technologies Office (SETO), the National Renewable Energy Laboratory (NREL) partnered with Peak Reliability to evaluate the impact of the August 21, 2017 total solar eclipse on the reliability and grid operations in the Western Electricity Coordinating Council (WECC) territory.
Rapid changes in solar radiative forcing influence heat, scalar and momentum fluxes and thereby shift the trajectory of near-surface atmospheric transitions. Surface fluxes are difficult to obtain during atmospheric transitions by either bulk or eddy-covariance methods because both techniques assume quasi-stationarity in an atmospheric state and require sufficiently long blocks of data, typically on the order of 10–30 min, to obtain statistically significant results. These computational requirements limit the temporal resolution of atmospheric processes that researchers can examine using traditional measurement techniques. In this paper, we present a novel observational approach to calculate surface fluxes at sub-minute temporal resolutions.
Eddy fluxes and meteorology data are reported at high temporal resolution for three flux tower sites in Mid-Missouri before, during, and after the Total Solar Eclipse of August 21, 2017. Mid-Missouri experienced up to 2 minutes and 40 seconds of totality at around solar noon during the eclipse (Fig. 1). The sites are located in deciduous oak-hickory forest, native prairie, and soybean ecosystems (Table 1 and Fig. 3). Eddy fluxes were computed using a wavelet-based approach that permitted the calculation of two-minute mean fluxes without losing low frequency flux contributions (Fig. 2). During the eclipse, standard meteorological variables were sampled and recorded at 5 second intervals. The two-minute means of fluxes and meteorology are reported. This data product includes three data files in NetCDF (*.nc) format, three data dictionary files and a file-level metadata file in comma separate (*.csv) format, and a user guide in PDF (*.pdf) format.
QuarkNet High School teachers and students perform experiments with cosmic ray muons. Their data is available to all on the i2u2.org site; enable measurements of muon flux, speed, and lifetime. The pandemic restricted access to many detectors, so QuarkNet provided virtual resources allowing users to carry out simpler experiments with already uploaded data. Some QuarkNet high school groups have also carried out more complex projects, e.g. Solar Eclipse 2017, MUSE at Fermilab, storm tracking, and g-2, that required assembling entire physics collaborations.
On 21 August 2017, a solar eclipse occurred over the continental United States resulting in a rapid reduction and subsequent increase of solar radiation over a large region of the country. The eclipse’s effect on the land-atmosphere system is documented in unprecedented detail using a unique array of sensors deployed at three sites in north-central Oklahoma. The observations showed that turbulent fluxes of heat and momentum at the surface responded quickly to the change in solar radiation. The decrease in the sensible heat flux resulted in a decrease in the air temperature below 200 m, and a large decrease in turbulent motions throughout the boundary layer. Furthermore, the turbulent mixing in the boundary layer lagged behind the change in the surface fluxes, and this lag depended on the height above the surface. The turbulent motions increased and the convective boundary layer was reestablished as the sensible heat flux recovered.
High-frequency (e.g., 10 Hz) eddy covariance measurements are typically used to estimate fluxes at the land–atmosphere interface at timescales of 15–60 min. These multivariate data contain information about the interdependency at high frequency between the interacting variables such as wind, humidity, temperature, and CO 2 . We use data at 10 Hz from an eddy covariance instrument located at 25 m above agricultural land in the Midwestern US, which offers an opportunity to move beyond the traditional spectral analyses to explore causal dependency among variables. In this study, we quantify the structure of inter-dependencies of interacting variables at high frequency represented by a directed acyclic graph (DAG). We compare DAGs to investigate changes in structural differences in causal interactions. We then apply a distance-based classification and -means clustering approach to identify the evolution of the causal structure represented by a DAG. Our method selects an unbiased number of clusters of similar structures and characterizes the similarities and differences between them. We explore a range of dynamic behavior using data from a clear sky day and during a solar eclipse in 2017. Our results show well-defined clusters of similar causal dependencies as the system evolves. Furthermore, our approach provides a methodological framework to understand how causal dependence in turbulence manifests in high-frequency data when represented through a DAG.
Abstract Mid‐Missouri experienced up to 2 min 40 s of totality at around solar noon during the total eclipse of 2017. We conducted the Mid‐Missouri Eclipse Meteorology Experiment to examine land‐atmosphere interactions during the eclipse. Here, research examining the eclipse responses in three contrasting ecosystems (forest, prairie, and soybeans) is described. There was variable cloudiness around first and fourth contacts (i.e., the start and end of partial solar obscuration) at the forest and prairie; however, solar irradiance ( K ↓ ) signals during the eclipse were relatively clean. Unfortunately, the eclipse forcing at the soybean field was contaminated by convective activity, which decreased K ↓ beginning about an hour before first contact and exposed the field to cold outflow ~30 min before second contact. Turbulence was suppressed during the eclipse at all sites; however, there was also an amplified signal at the soybean field during the passage of a gust front. The standard deviations of the horizontal and vertical wind velocities and friction velocities decreased by ~75% at the forest (aerodynamically rough), and ~60% at the prairie (aerodynamically smooth). The eddy fluxes of energy were highly coherent with the solar forcing with the latent and sensible heat fluxes approaching 0 W/m 2 and changing in direction, respectively. For the prairie site, we estimated a canopy‐scale time constant for the surface conductance light response of 10 min. Although the eclipse imparted large forcings on surface energy balances, the air temperature response was relatively muted (1.5–2.5 °C decrease) due to the absence of topographic effects and the relatively moist land and atmosphere.
Conventional approaches for modeling human mobility pattern often focus on human activity and movement dynamics in their regular daily lives and cannot capture changes in human movement dynamics in response to large-scale events. With the rapid advancement of information and communication technologies, many researchers have adopted alternative data sources (e.g., cell phone records, GPS trajectory data) from private data vendors to study human movement dynamics in response to large-scale natural or societal events. Big geosocial data such as georeferenced tweets are publicly available and dynamically evolving as real-world events are happening, making it more likely to capture the real-time sentiments and responses of populations. However, precisely-geolocated geosocial data is scarce and biased toward urban population centers. In this research, we developed a big geosocial data analytical framework for extracting human movement dynamics in response to large-scale events from publicly available georeferenced tweets. The framework includes a two-stage data collection module that collects data in a more targeted fashion in order to mitigate the data scarcity issue of georeferenced tweets; in addition, a variable bandwidth kernel density estimation(VB-KDE) approach was adopted to fuse georeference information at different spatial scales, further augmenting the signals of human movement dynamics contained in georeferenced tweets. To correct for the sampling bias of georeferenced tweets, we adjusted the number of tweets for different spatial units (e.g., county, state) by population. To demonstrate the performance of the proposed analytic framework, we chose an astronomical event that occurred nationwide across the United States, i.e., the 2017 Great American Eclipse, as an example event and studied the human movement dynamics in response to this event. Finally, this analytic framework can easily be applied to other types of large-scale events such as hurricanes or earthquakes.
The Land-Atmosphere Feedback Experiment (LAFE; pronounced “la-fey”) deployed several state-of-the-art scanning lidar and remote-sensing systems to the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Climate Research Facility Southern Great Plains (SGP) site. These instruments augmented the ARM instrument suite and collected a data set for studying feedback processes between the land surface and the atmosphere. The novel synergy of remote-sensing systems was applied for simultaneous measurements of land surface fluxes and horizontal and vertical transport processes in the atmospheric convective boundary layer (CBL) (Wulfmeyer et al. 2018). The impact of spatial inhomogeneities of the soil-vegetation continuum on land-atmosphere (L-A) feedback was studied using the scanning capability of the instrumentation. The time period of the observations was August 2017, as large differences in surface fluxes between different fields and bare soil were expected, e.g., pastures versus fields where the wheat has already been harvested. The LAFE strategy involved sampling the surface fluxes over different types of surfaces, and thus the in situ energy balance closure (EBC) stations were placed in fields with different plant covers (e.g., soy bean plants, native grasses, etc.).