Practical formulas for the refraction coefficient

Knowledge of the actual refraction coefficient is essential in leveling surveys and precise electromagnetic distance measurement reduction. The most common method followed by the surveyor for its determination is based on the use of simultaneous reciprocal zenith observations. The commonly used formula is only an approximation valid for approximately horizontal sightings, whereas the exact geometric solution turns out to be very complicated so that an iterative computation procedure is suggested instead. In the present paper, the goal is to derive a compact formula from the complete solution that is easy to implement and retains the necessary accuracy for horizontal and slanted sightings. In addition, the paper will also focus on the common situation for the surveyor where isolated observations have to be done and no partially compensating procedures—e.g., leap-frog or middle point—are possible. If temperature vertical profiles are unknown then the refraction coefficient cannot be reliably determined. Some surveyors may customarily use then an average value, e.g., k 5 0:13, perhaps being unaware of the risks involved in such simplistic assumption. In the present paper, it is also a goal to present a useful and simple formula for approximately estimating the refraction coefficient in terms of easily accessible parameters to correct the bulk of the refraction effect in single observations, always bearing in mind that determination of the refraction coefficient by means of a model may turn out to be somewhat inaccurate, but still better than the blind use of a universal k.The authors are grateful to the editor and the anonymous reviewers for their valuable suggestions, corrections, and comments that helped improve the original manuscript. This research is funded by the Spanish Ministry of Science and Innovation (Grant No. AYA2011-23232).Baselga Moreno, S.; García-Asenjo Villamayor, L.; Garrigues Talens, P. (2014). Practical formulas for the refraction coefficient. Journal of Surveying Engineering. 140(2):1-5. https://doi.org/10.1061/(ASCE)SU.1943-5428.0000124S15140

Excitation of tall auroral rays by ohmic heating in field-aligned current filaments at F region heights

The formation of tall red rays in the ionosphere has been a longstanding unresolved problem of auroral physics. These rays are pencil-like structures which can extend from 150 km at their base to as high as 600 km. At these heights it is very difficult to deposit sufficient power in order to account for the luminosity of tall rays. This work examines ohmic heating by collisional processes in strong field-aligned current sheets to account for visible tall rays. The mechanism is demonstrated by two-dimensional simulation in a fully self-consistent treatment of the ionosphere and coupling to the magnetosphere. We find that a filamentary current density of about 600 µAm-2 over about ten seconds can pump sufficient energy into the ambient oxygen atoms to produce visible auroral red rays. The ohmic heating leads to an electron temperature in excess of 10,000 K in the upper F-region

25‐Second Determination of 2019 Mw 7.1 Ridgecrest Earthquake Coseismic Deformation

We have developed a global earthquake monitoring system based on low‐latency measurements from more than 1000 existing Global Navigational Satellite System (GNSS) receivers, of which nine captured the 2019 Mw 6.4 Ridgecrest, California, foreshock and Mw 7.1 mainshock earthquakes. For the foreshock, coseismic offsets of up to 10 cm are resolvable on one station closest to the fault, but did not trigger automatic offset detection. For the mainshock, GNSS monitoring determined its coseismic deformation of up to 70 cm on nine nearby stations within 25 s of event nucleation. These 25 s comprise the fault rupture duration itself (roughly 10 s of peak moment release), another 10 s for seismic waves and displacement to propagate to nearby GNSS stations, and a few additional seconds for surface waves and other crustal reverberations to dissipate sufficiently such that coseismic offset estimation filters could reconverge. Latency between data acquisition in the Mojave Desert and positioning in Washington State averaged 1.4 s, a small fraction of the fault rupture time itself. GNSS position waveforms for the two closest stations that show the largest dynamic and static displacements agree well with postprocessed time series. Mainshock coseismic ground deformation estimated within 25 s of origin time also agrees well with, but is ∼10% smaller than, deformation estimated using 48 hr observation windows, which may reflect rapid postseismic fault creep or the cumulative effect of nearly 1000 aftershocks in the 48 hr following the mainshock. GNSS position waveform shapes, which comprise a superposition of dynamic and static displacements, are well modeled by frequency–wavenumber synthetics for the Hadley–Kanamori 1D crustal structure model and the U.S. Geological Survey finite‐rupture distribution and timing. These results show that GNSS seismic monitoring performed as designed and offers a new means of rapidly characterizing large earthquakes globally