Ensemble-Averaging Resolves Rapid Atmospheric Response to the 2017 Total Solar Eclipse

Abstract

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. High-frequency data from a horizontal, log-spaced array of nine time-synchronized ultrasonic anemometers were used to perform spatial-temporal ensemble averaging and to obtain eddycovariance turbulence fluxes at unprecedented time resolutions. The 2017 Great American Solar Eclipse event provided a "natural experiment" to test the ensembleobservation and averaging approach. A total eclipse is energetically well-constrained and, unlike day/night transitions, is a perturbation that quickly transitions from and back to a state of significant solar forcing, providing an ideal scenario for testing the space-timescales required for surface flux calculations. Additionally, two Doppler lidars and a vertically-oriented Distributed Temperature Sensing (DTS) system provided measurements to characterize near-surface atmospheric conditions. Results show that the ensemble-averaged sensible heat fluxes converged at timescales as short as 15 s. Additional analyses show that the timescale of the connection between the surface and the atmosphere is more rapid than previous measurements have been capable of showing and is on the order of 10 min or less. This experiment demonstrates that ensemble-flux measurements are capable of resolving fluctuations in surface fluxes during rapid atmospheric transitions.

The Response of Spectral Vegetation Indices and Solar‐Induced Fluorescence to Changes in Illumination Intensity and Geometry in the Days Surrounding the 2017 North American Solar Eclipse

“…Hysteresis in PRI was evident on the clear day but not during the eclipse, suggesting that the midafternoon timing of the eclipse may have mitigated the midafternoon temperature and moisture stress typical under clear skies. This is consistent with the findings of Higgins et al (2019), who documented reductions in air temperature throughout the 2017 North American eclipse at three field sites within the path of totality. We also report reduced air temperature and increased relative humidity in Figure 2, which may act as triggers to allow physiological light dissipation mechanisms to relax (Demmig‐Adams, 1990).…”

Assessment and Correction of Solar Radiation Measurements with Simple Neural Networks

“…A complete description of this field experiment was provided in previous publications [47,48]. For a 12-day period-19-31 August-the NR01 radiometer and other sensors were deployed again at the experimental site as part of a large coordinated experiment on atmospheric turbulence during the Great American Eclipse, as described previously [49]. The sensors and periods of operation from which data were used in this study are listed in Table 2.…”

Suitability of fiber-optic distributed temperature sensing to reveal mixing processes and higher-order moments at the forest-air interface

“…A growing body of research has already utilised DTS measurements in atmospheric studies (Keller et al, 2011;Thomas et al, 2012;Euser et al, 2014;de Jong et al, 2015;Sayde et al, 2015;Zeeman et al, 2015;Pfister et al, 2017;Higgins et al, 2018;Schilperoort et al, 2018;Higgins et al, 2019;Izett et al, 2019;Mahrt et al, 2019;Pfister et al, 2019). Bulk of the studies have concentrated on nocturnal flows near the surface (Keller et al, 2011;Thomas et al, 2012;Zeeman et al, 2015;Pfister et al, 2017;Izett et al, 2019;Mahrt et al, 2019;Pfister et al, 2019) and a few have concentrated on transition periods (Higgins et al, 2018(Higgins et al, , 2019. By utilising different DTS measurement configurations, some studies have done distributed wind speed (heated cables) (Sayde et al, 2015;Pfister et al, 2017) or humidity (wetted cables) measurements (Euser et al, 2014;Schilperoort et al, 2018), whereas others have examined the radiation error of the cables (de Jong et al, 2015;Sigmund et al, 2017).…”