We report on the mountain top observation of three terrestrial gamma‐ray flashes (TGFs) that occurred during the summer storm season of 2021. To our knowledge, these are the first TGFs observed in a mountaintop environment and the first published European TGFs observed from the ground. A gamma‐ray sensitive detector was located at the base of the Säntis Tower in Switzerland and observed three unique TGF events with coincident radio sferic data characteristic of TGFs seen from space. We will show an example of a “slow pulse” radio signature (Cummer et al., 2011,
We show that atmospheric gravity waves can generate plasma ducts and irregularities in the plasmasphere using the coupled SAMI3/WACCM‐X model. We find the equatorial electron density is irregular as a function of longitude which is consistent with CRRES measurements (Clilverd et al., 2007,
- Award ID(s):
- 1931415
- NSF-PAR ID:
- 10468846
- Publisher / Repository:
- DOI PREFIX: 10.1029
- Date Published:
- Journal Name:
- Geophysical Research Letters
- Volume:
- 50
- Issue:
- 20
- ISSN:
- 0094-8276
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
more » « less
Abstract https://doi.org/10.1029/2011GL048099 ; Lu et al., 2011,https://doi.org/10.1029/2010JA016141 ; Pu et al., 2019,https://doi.org/10.1029/2019GL082743 ; Pu et al., 2020,https://doi.org/10.1029/2020GL089427 ), a −EIP (Lyu et al., 2016,https://doi.org/10.1002/2016GL070154 ; Lyu et al., 2021,https://doi.org/10.1029/2021GL093627 ; Wada et al., 2020,https://doi.org/10.1029/2019JD031730 ), and a double peak TGF associated with an extraordinarily powerful and complicated positive‐polarity sferic, where each TGF peak is possibly preceded by a short burst of stepped leader emission. -
more » « less
Abstract The polar
F region ionosphere frequently exhibits sporadic variability (e.g., Meek, 1949,https://doi.org/10.1029/JZ054i004p00339 ; Hill, 1963,https://doi.org/10.1175/1520‐0469(1963)020<0492:SEOLII>2.0.CO;2 ). Recent satellite data analysis (Noja et al., 2013,https://doi.org/10.1002/rds.20033 ; Chartier et al., 2018,https://doi.org/10.1002/2017JA024811 ) showed that the high‐latitudeF region ionosphere exhibits sporadic enhancements more frequently in January than in July in both the northern and southern hemispheres. The same pattern has been seen in statistics of the degradation and total loss of GPS service onboard low‐Earth orbit satellites (Xiong et al. 2018,https://doi.org/10.5194/angeo‐36‐679‐2018 ). Here, we confirm the existence of this annual pattern using ground GPS‐based images of TEC from the MIDAS algorithm. Images covering January and July 2014 confirm that the high‐latitude (>70 MLAT)F region exhibits a substantially larger range of values in January than in July in both the northern and southern hemispheres. The range of TEC values observed in the polar caps is 38–57 TECU (north‐south) in January versus 25–37 TECU in July. First‐principle modeling using SAMI3 reproduces this pattern, and indicates that it is caused by an asymmetry in plasma levels (30% higher in January than in July across both polar caps), as well as 17% longer O+plasma lifetimes in northern hemisphere winter, compared to southern hemisphere winter. -
more » « less
Abstract The objective of this comment is to correct two sets of statements in Litwin et al. (2022,
https://doi.org/10.1029/2021JF006239 ), which consider our research work (Bonetti et al., 2018,https://doi.org/10.1098/rspa.2017.0693 ; Bonetti et al., 2020,https://doi.org/10.1073/pnas.1911817117 ). We clarify here that (a) the specific contributing area is defined in the limit of an infinitesimal contour length instead of the product of a reference contour width (Bonetti et al., 2018,https://doi.org/10.1098/rspa.2017.0693 ), and (b) not all solutions obtained from the minimalist landscape evolution model of Bonetti et al. (2020,https://doi.org/10.1073/pnas.1911817117 ) are rescaled copies of each other. We take this opportunity to demonstrate that the boundary conditions impact the obtained solutions, which has not been considered in the dimensional analysis of Litwin et al. (2022,https://doi.org/10.1029/2021JF006239 ). We clarify this point by using dimensional analysis and numerical simulations for a square domain, where only one horizontal length scale (the side lengthl ) enters the physical law. -
more » « less
Abstract We introduce a new framework called Machine Learning (ML) based Auroral Ionospheric electrodynamics Model (ML‐AIM). ML‐AIM solves a current continuity equation by utilizing the ML model of Field Aligned Currents of Kunduri et al. (2020,
https://doi.org/10.1029/2020JA027908 ), the FAC‐derived auroral conductance model of Robinson et al. (2020,https://doi.org/10.1029/2020JA028008 ), and the solar irradiance conductance model of Moen and Brekke (1993,https://doi.org/10.1029/92gl02109 ). The ML‐AIM inputs are 60‐min time histories of solar wind plasma, interplanetary magnetic fields (IMF), and geomagnetic indices, and its outputs are ionospheric electric potential, electric fields, Pedersen/Hall currents, and Joule Heating. We conduct two ML‐AIM simulations for a weak geomagnetic activity interval on 14 May 2013 and a geomagnetic storm on 7–8 September 2017. ML‐AIM produces physically accurate ionospheric potential patterns such as the two‐cell convection pattern and the enhancement of electric potentials during active times. The cross polar cap potentials (ΦPC ) from ML‐AIM, the Weimer (2005,https://doi.org/10.1029/2004ja010884 ) model, and the Super Dual Auroral Radar Network (SuperDARN) data‐assimilated potentials, are compared to the ones from 3204 polar crossings of the Defense Meteorological Satellite Program F17 satellite, showing better performance of ML‐AIM than others. ML‐AIM is unique and innovative because it predicts ionospheric responses to the time‐varying solar wind and geomagnetic conditions, while the other traditional empirical models like Weimer (2005,https://doi.org/10.1029/2004ja010884 ) designed to provide a quasi‐static ionospheric condition under quasi‐steady solar wind/IMF conditions. Plans are underway to improve ML‐AIM performance by including a fully ML network of models of aurora precipitation and ionospheric conductance, targeting its characterization of geomagnetically active times. -
more » « less
Abstract Recent advances in remote sensing of solar‐induced chlorophyll fluorescence (SIF) have garnered wide interest from the biogeoscience and Earth system science communities, due to the observed linearity between SIF and gross primary productivity (GPP) at increasing spatiotemporal scales. Three recent studies, Maguire et al., (2020,
https://doi.org/10.1029/2020GL087858 ), He et al. (2020,https://doi.org/10.1029/2020GL087474 ), and Marrs et al. (2020,https://doi.org/10.1029/2020GL087956 ) highlight a nonlinear relationship between fluorescence and photochemical yields and show empirical evidence for the decoupling of SIF, stomata, and the carbon reactions of photosynthesis. Such mechanistic studies help advance our understanding of what SIF is and what it is not. We argue that these findings are not necessarily contradictory to the linear SIF‐GPP relationship observed at the satellite scale and provide context for where, when, and why fluorescence and photosynthesis diverge at smaller spatiotemporal scales. Understanding scale dependencies of remote sensing data is crucial for interpreting SIF as a proxy for GPP.
