Nitric Oxide (NO) significantly impacts energy distribution and chemical processes in the mesosphere and lower thermosphere (MLT). During geomagnetic storms, a substantial influx of energy in the thermosphere leads to an increase in NO infrared emissions. Accurately predicting the radiative flux of Nitric Oxide is crucial for understanding the thermospheric energy budget, particularly during extreme space weather events. With advancements in computational techniques, machine learning (ML) has become a highly effective tool for space weather forecasting. This effort becomes even more worthwhile considering the availability of two decades of continuous NO infrared emissions measurement by TIMED/SABER, along with several other key thermospheric variables. We present the scheme of development of an ML-based predictive model for Nitric Oxide Infrared Radiative Flux (NOIRF). Various ML algorithms have been tested for better predictive ability, and an optimized model (NOEMLM) has been developed for the study of NOIRF. This model is able to extract the underlying relationships between the input features and effectively predict the NOIRF. The NOEMLM predictions have very good agreements with SABER observation during quiet time as well as geomagnetic storms. In comparison with the existing TIEGCM model, NOEMLM has very good performance, especially during extreme space weather conditions. The results of this study suggest that utilizing geomagnetic and space weather indices with ML/AI can serve as superior parameters for studying the upper atmosphere, as compared to focusing on specific species having complex chemical processes and associated uncertainties in constituents. ML techniques can effectively carry out the analysis with greater ease than traditional chemical studies.

It is well-known that equatorial plasma bubbles (EPBs) are highly correlated to the post-sunset rise of the ionosphere on a climatological basis. However, when proceeding to the daily EPB development, what controls the day-to-day/longitudinal variability of EPBs remains a puzzle. In this study, we investigate the underlying physics responsible for the day-to-day/longitudinal variability of EPBs using the Sami3 is A Model of the Ionosphere (SAMI3) and the Whole Atmosphere Community Climate Model with thermosphere-ionosphere eXtension (WACCM-X). Simulation results on October 20, 22, and 24, 2020 were presented. SAMI3/WACCM-X self-consistently generated midnight EPBs on October 20 and 24, displaying irregular and regular spatial distributions, respectively. However, EPBs are absent on October 22. We investigate the role of gravity waves on upwelling growth and EPB development and discuss how gravity waves contribute to the distributions of EPBs. Of particular significance is that we found the westward wind associated with solar terminator waves and gravity waves causes midnight vertical drift enhancement and collisional shear instability, which provides conditions favorable for upwelling growth and EPB development. The converging and diverging winds associated with solar terminator waves and midnight temperature maximum also affect the longitudinal distribution of EPBs. The absence of EPBs on October 22 is related to the weak upward drift induced by weak westward wind associated with solar terminator waves.

The Hunga Tonga Hunga-Ha’apai (HTHH) volcanic eruption on 15 January 2022 injected water vapor and SO2 into the stratosphere. Several months after the eruption, significantly stronger westerlies, and a weaker Brewer-Dobson circulation developed in the stratosphere of the Southern Hemisphere and were accompanied by unprecedented temperature anomalies in the stratosphere and mesosphere. In August 2022 the Sounding of the Atmosphere using Broadband Emission Radiometry (SABER) satellite instrument observed record-breaking temperature anomalies in the stratosphere and mesosphere that alternate signs with altitude. Ensemble simulations carried out with the Whole Atmosphere Community Climate Model (WACCM6) indicate that the strengthening of the stratospheric westerlies explains the mesospheric temperature changes. The stronger westerlies cause stronger westward gravity wave drag in the mesosphere, accelerating the mesospheric mean meridional circulation. The stronger mesospheric circulation, in turn, plays a dominant role in driving the changes in mesospheric temperatures. This study highlights the impact of large volcanic eruptions on middle atmospheric dynamics and provides insight into their long-term effects in the mesosphere. On the other hand, we could not discern a clear mechanism for the observed changes in stratospheric circulation. In fact, an examination of the WACCM ensemble reveals that not every member reproduces the large changes observed by SABER. We conclude that there is a stochastic component to the stratospheric response to the HTHH eruption.

The ability of satellite instruments to accurately observe long-term changes in atmospheric temperature depends on many factors including the absolute accuracy of the measurement, the stability of the calibration of the instrument, the stability of the satellite orbit, and the stability of the numerical algorithm that produces the temperature data. We present an example of algorithm instability recently discovered in the temperature dataset from the SABER instrument on the NASA TIMED satellite. The instability resulted in derived temperatures that were substantially colder than anticipated from mid-December 2019 to mid-2022. This algorithm-induced change in temperature over one to two years corresponded to the expected change over several decades from increasing anthropogenic CO2. This paper highlights the importance of algorithm stability in developing Geospace Data Records (GDRs) for Earth’s mesosphere and lower thermosphere. A corrected version (Version 2.08) of the temperatures from SABER is described.

Assessing space weather modeling capability is a key element in improving existing models and developing new ones. In order to track improvement of the models and investigate impacts of forcing, from the lower atmosphere below and from the magnetosphere above, on the performance of ionosphere-thermosphere models, we expand our previous assessment for 2013 March storm event [Shim et al., 2018]. In this study, we evaluate new simulations from upgraded models (Coupled Thermosphere Ionosphere Plasmasphere Electrodynamics (CTIPe) model version 4.1 and Global Ionosphere Thermosphere Model (GITM) version 21.11) and from NCAR Whole Atmosphere Community Climate Model with thermosphere and ionosphere extension (WACCM-X) version 2.2 including 8 simulations in the previous study. A simulation of NCAR Thermosphere-Ionosphere-Electrodynamics General Circulation Model version 2 (TIE-GCM 2) is also included for comparison with WACCM-X. TEC and foF2 changes from quiet-time background are considered to evaluate the model performance on the storm impacts. For evaluation, we employ 4 skill scores: Correlation coefficient (CC), root-mean square error (RMSE), ratio of the modeled to observed maximum percentage changes (Yield), and timing error(TE). It is found that the models tend to underestimate the storm-time enhancements of foF2 (F2-layer critical frequency) and TEC (Total Electron Content) and to predict foF2 and/or TEC better in the North America but worse in the Southern Hemisphere. The ensemble simulation for TEC is comparable to results from a data assimilation model (Utah State University-Global Assimilation of Ionospheric Measurement (USU-GAIM)) with differences in skill score less than 3% and 6% for CC and RMSE, respectively.

The January 2022 Hunga Tonga–Hunga Haʻapai eruption was one of the most explosive volcanic events of the modern era, producing a vertical plume which peaked > 50km above the Earth. The initial explosion and subsequent plume triggered atmospheric waves which propagated around the world multiple times. A global-scale wave response of this magnitude from a single source has not previously been observed. Here we show the details of this response, using a comprehensive set of satellite and ground-based observations to quantify it from surface to ionosphere. A broad spectrum of waves was triggered by the initial explosion, including Lamb waves5,6 propagating at phase speeds of 318.2+/-6 ms-1 at surface level and between 308+/-5 to 319+/-4 ms-1 in the stratosphere, and gravity waves propagating at 238+/-3 to 269+/-3 ms-1 in the stratosphere. Gravity waves at sub-ionospheric heights have not previously been observed propagating at this speed or over the whole Earth from a single source. Latent heat release from the plume remained the most significant individual gravity wave source worldwide for >12 hours, producing circular wavefronts visible across the Pacific basin in satellite observations. A single source dominating such a large region is also unique in the observational record. The Hunga Tonga eruption represents a key natural experiment in how the atmosphere responds to a sudden point-source-driven state change, which will be of use for improving weather and climate models.

Geomagnetically induced currents (GICs) at middle latitudes have received increased attention after reported power-grid disruptions due to geomagnetic disturbances. However, quantifying the risk to the electric power grid at middle latitudes is difficult without understanding how the GIC sensors respond to geomagnetic activity on a daily basis. Therefore, in this study the question “Do measured GICs have distinguishable and quantifiable long- and short-period characteristics?” is addressed. The study focuses on the long-term variability of measured GIC, and establishes the extent to which the variability relates to quiet-time geomagnetic activity. GIC quiet-day curves (QDCs) are computed from measured data for each GIC node, covering all four seasons, and then compared with the seasonal variability of Thermosphere-Ionosphere- Electrodynamics General Circulation Model (TIE-GCM)-simulated neutral wind and height-integrated current density. The results show strong evidence that the middle-latitude nodes routinely respond to the tidal-driven Sq variation, with a local time and seasonal dependence on the the direction of the ionospheric currents, which is specific to each node. The strong dependence of GICs on the Sq currents demonstrates that the GIC QDCs may be employed as a robust baseline from which to quantify the significance of GICs during geomagnetically active times and to isolate those variations to study independently. The QDC-based significance score computed in this study provides power utilities with a node-specific measure of the geomagnetic significance of a given GIC observation. Finally, this study shows that the power grid acts as a giant sensor that may detect ionospheric current systems.

The Antarctic stratospheric sudden warming (SSW) occurred on August 30, 2019, and was a vortex displacement minor warming event. We investigated variations in gravity waves (GWs) before and after this rare Antarctic SSW event using two satellite measurements (AIRS and CIPS) and reanalysis data (GEOS-5 FP). The observations showed that the GW activities decreased after the SSW onset, with a weakening of zonal wind. The decrease in GW activity coincided with a reversal of the zonal wind around September 8 in GEOS-5 FP. The temporal variation of GWs was similar to that of Arctic GWs during vertex displacement minor SSWs. The decline in GW activities was probably caused by wind filtering and polar night jet breaking. However, the GW activities over the Andes and the Antarctic peninsula decreased at the onset, although the westly wind was 40–60 ms-1. This decrease could have been caused by wave saturation.

The explosive eruption of the Hunga-Tonga volcano in the southwest Pacific at 0415UT on 15 January 2022 triggered gigantic atmospheric disturbances with surface air pressure wave propagating around the globe in Lamb mode. In space, concentric traveling ionosphere disturbances (CTIDs) are also observed as a manifestation of air pressure acoustic waves in New Zealand ~0500UT and Australia ~0630UT. As soon as the wave reached central Australia ~0800UT, CTIDs appeared simultaneously in the northern hemispheres through magnetic field line conjugate effect, which is much earlier than the arrival of the air pressure wave to Japan after 1100UT. Combining observations over Australia and Japan between 0800-1000UT, CTIDs with characteristics of phase velocities of 320-390 m/s are observed, matching with the dispersion relation of Lamb mode. The arrival of atmospheric Lamb wave to Japan later created in situ CTIDs showing the same Lamb mode characteristics as the earlier arriving CTIDs.

The Tonga volcano eruption of 15 January 2022 unleashed a variety of atmospheric perturbations, coinciding with the recovery phase of a geomagnetic storm. The ensuing thermospheric variations created rare display of extreme poleward-expanding conjugate plasma bubbles seen in the rate of total electron content index (ROTI) over 100-150°E. This is associated with fluctuations in FORMOSAT-7/COSMIC-2 (F7/C2) ion-density measurements and spread-F signatures in ionograms, reaching ~40°N geographic latitude. This was preceded by an unusually strong pre-reversal enhancement (PRE) in the global ionospheric specification (GIS) electron density profiles derived from F7/C2 observations. The GIS further revealed a decrease of equatorial ionization anomaly (EIA) crest density due to the storm impact. A sharp decrease of E-region conductivity by volcano-induced waves, combined with enhanced F-region wind over EIA with less ion-drag apparently intensified the PRE. The strong PRE and seed perturbations from the volcano-induced waves likely further triggered super plasma bubble activity.

A mountain wave with a significant brightness temperature amplitude and ~500 km horizontal wavelength was observedover the Southern Andes on 24–25 July 2017 in AIRS/Aqua satellite data. In the MERRA-2 reanalysis data, a mesoscale vortex-like pattern appeared to the west of the Andes at 2 km, and the wind flowed over the Andes. VIIRS/Suomi-NPP did not detect the mountain waves; however, it observed concentric ring-like waves in the nightglow emissions at ~87 km with ~100 km wavelengths on the same night over and leeward of the Southern Andes. A ray tracing analysis showed that the mountain waves propagated to the east of the Andes, where concentric ring-like waves appeared while mountain waves broke. Therefore, the concentric ring-like waves were likely secondary gravity waves generated by momentum deposition that accompanied mountain wave breaking. These results provide the first direct evidence for secondary gravity waves generated by momentum deposition.

We examine characteristics of the seasonal variation of thermospheric composition using column number density ratio ∑O/N2 observed by the NASA Global Observations of Limb and Disk (GOLD) mission from low-mid to mid-high latitudes. We found that the ∑O/N2 seasonal variation is hemispherically asymmetric: in the southern hemisphere, it exhibits the well-known annual and seminal pattern, with highs near the equinoxes, and primary and secondary lows near the solstices. In the northern hemisphere, it is dominated by an annual variation, with a minor semiannual component with the highs shifting towards the wintertime. We also found that the durations of the December and June solstice seasons in terms of ∑O/N2 are highly variable with longitude. Our hypothesis is that ion-neutral collisional heating in the equatorial ionization anomaly region, ion drag, and auroral Joule heating play substantial roles in this longitudinal dependency. Finally, the rate of change in ∑O/N2 from one solstice season to the other is dependent on latitude, with more dramatic changes at higher latitudes.