L. C. Gardner

Terdiurnal Oscillations in OH Meinel Rotational Temperatures for Fall Conditions at Northern Mid- latitude Sites

High-precision (∼0.5 K) measurements of OH Meinel (M) (6,2) rotational temperatures above the Bear Lake Observatory, UT (42°N, 112°W) during October 1996 have revealed an interesting and unexpected mean nocturnal pattern. Ten quality nights (>100 h) of data have been used to form a mean night for autumnal, near-equinoctial conditions. The mean temperature and RMS variability associated with this mean night were 203 ± 5 K and 2.4 K, respectively, and compare very favorably with expectations based on Na-lidar measurements of mean tidal temperature perturbations over Urbana, IL (40°N, 88°W) during the fall 1996. Furthermore, this comparison shows that the 8-h tide was the dominant source of the mean nocturnal temperature variability in the OH M region during this period. Additional data, obtained at Fort Collins, CO (41°N, 105°W) in November 1997, illustrate the occurrence of an 8-h component of OH temperature variability about two months after the equinox and show that daily amplitudes as high as ≅15 K are possible.

Large amplitude perturbations in mesospheric OH Meinel and 87‐Km Na lidar temperatures around the autumnal equinox

Two high-precision CEDAR instruments, an OH Mesospheric Temperature Mapper (MTM) and a Na Temperature Lidar, have been used to investigate seasonal variability in the mid-latitude temperature at ∼87 km altitude over the western USA. Here we report the observation of a large perturbation in mesospheric temperature that occurs shortly after the autumnal equinox in close association with the penetration of planetary-wave energy from the troposphere into the mesosphere. This perturbation has been observed on three occasions and exhibits a departure of up to ∼25–30 K from the nominal seasonal trend during a disturbed period of ∼2 weeks. Such behavior represents a dramatic transient departure from the seasonal trend expected on the basis of current empirical models. These novel results coupled with a recent TIME-GCM modeling study [Liu et al., 2000] provide important insight into the role of planetary waves in mesospheric variability during the equinox periods.

Long-period Wave Signatures in Mesospheric OH Meinel (6,2) Band Intensity and Rotational Temperature at Mid-latitudes

Abstract A high performance imaging system has been used to investigate the signature of long-period, ∼8-hr, wave-like oscillations evident in the OH Meinel (6,2) band emission (peak altitude ∼87 km) during the fall and early winter months. The measurements were made from two mid-latitude sites in the western USA during 1996/7. Previous investigations of the induced temperature perturbations (amplitude and phase) suggest that many of these events exhibit characteristics akin to the mid-latitude terdiurnal tide (Pendleton, 2000). To further investigate the origin of these waves we have performed an initial investigation using the Krassovsky ratio (η) method, to determine the amplitude ratio of the induced perturbations in the zenith OH emission intensity and rotational temperature and to study their phase relationship (φ). A range of values for the magnitude and phase of η were found with a mean value of |η| = 6 ± 2 (range ∼2–10), and φ = −51° ± 21° (range −11° to −94°) with the temperature perturbation always leading the intensity wave. These results are in good agreement with existing high-latitude studies of distinct 8-hr oscillations in the literature. However, comparison with realistic gravity wave and terdiurnal tidal model computations reveal a conflicting situation where the observed negative phase results point more towards a long-period gravity wave interpretation rather than a terdiurnal tide.

Ensemble Modeling with Data Assimilation Models: A New Strategy for Space Weather Specifications, Forecasts, and Science

The Earth’s Ionosphere-Thermosphere-Electrodynamics (I-T-E) system varies markedly on a range of spatial and temporal scales and these variations have adverse effects on human operations and systems, including high-frequency communications, over-the-horizon radars, and survey and navigation systems that use Global Positioning System (GPS) satellites. Consequently, there is a need to elucidate the underlying physical processes that lead to space weather disturbances and to both mitigate and forecast near-Earth space weather.

Global Assimilation of Ionospheric Measurements‐Gauss Markov model: Improved specifications with multiple data types

The Earths ionosphere is a highly dynamic region that is almost constantly in a state of flux. Solar radiation, geomagnetic activity, chemical reactions, and natural dynamics all act to perturb the state of the ionosphere. The ionosphere changes on time scales of hours to days, with the fine-scale ionospheric structures that are frequently observed lacking in global physics-based models due to time step and spatial resolution constraints. To properly specify the ionosphere, data are needed, thus data assimilation. The Utah State University Global Assimilation of Ionospheric Measurements-Gauss Markov (GAIM-GM) model uses a data assimilation method to correct a physics-based model of the ionosphere using five different data types, divided into nine different data sources. Multiple data types are necessary because the data from any individual data source will not be sufficient for global reconstructions. The GAIM-GM specification (in real time) can then be used to correct for ionospheric propagation delays, thereby improving geolocation and communications. The focus here is to show the quantitative effects that multiple data types have on GAIM-GM ionospheric specifications for a relatively quiet day (19 April) in 2012.

Space weather forecasting with a Multimodel Ensemble Prediction System (MEPS)

The goal of the MEPS program is to improve space weather specification and forecasting with ensemble modeling. Space weather can have detrimental effects on a variety of civilian and military systems and operations, and many of the applications pertain to the ionosphere and upper atmosphere. Space weather can affect over-the-horizon (OTH) radars, HF communications, surveying and navigation systems, surveillance, spacecraft charging, power grids, pipelines, and the FAAs Wide-Area Augmentation System (WAAS). Because of its importance, numerous space weather forecasting approaches are being pursued, including those involving empirical, physics-based, and data assimilation models. Clearly, if there are sufficient data, the data assimilation modeling approach is expected to be the most reliable, but different data assimilation models can produce different results. Therefore, like the meteorology community, we created a Multimodel Ensemble Prediction System (MEPS) for the Ionosphere-Thermosphere-Electrodynamics (I-T-E) system that is based on different data assimilation models [Schunk et al., 2014a, b]. The MEPS ensemble is composed of seven physics-based data assimilation models for the ionosphere, ionosphere-plasmasphere, thermosphere, high-latitude ionosphere-electrodynamics, and mid-low latitude ionosphere-electrodynamics. Hence, multiple data assimilation models can be used to describe each region. A selected storm event that was reconstructed with four different data assimilation models covering the middle and low latitude ionosphere is presented and discussed. In addition, the effect of different data types on the reconstructions is shown.

Terminator field‐aligned currents: A new finding from the Ionospheric Dynamics and Electrodynamics Data Assimilation Model

A new field-aligned current system in the high-latitude ionosphere has been discovered. The finding was based on the reconstructions from the Ionospheric Dynamics and Electrodynamics Data Assimilation Model with the ingestion of ground-based magnetometer measurements. The new current system develops and evolves along the ionospheric terminator, and it is thus termed as the terminator field-aligned currents. This is the first field-aligned current system in the high-latitude ionosphere that is not directly driven by the magnetospheric dynamics and has an ionospheric origin. The study of it will help us to explore the active role of the ionosphere in the magnetosphere-ionosphere coupling and improve the physical understanding of the electrodynamics and plasma dynamics of many small-scale structures in the polar ionosphere.

CEDAR-GEM Challenge for Systematic Assessment of Ionosphere/Thermosphere Models in Predicting TEC During the 2006 December Storm Event

In order to assess current modeling capability of reproducing storm impacts on TEC, we considered quantities such as TEC, TEC changes compared to quiet time values, and the maximum value of the TEC and TEC changes during a storm. We compared the quantities obtained from ionospheric models against ground-based GPS TEC measurements during the 2006 AGU storm event (14-15 Dec., 2006) in the selected eight longitude sectors. We used 15 simulations obtained from eight ionospheric models, including empirical, physics-based, coupled ionosphere-thermosphere and data assimilation models. To quantitatively evaluate performance of the models in TEC prediction during the storm, we calculated skill scores such as RMS error, Normalized RMS error (NRMSE), ratio of the modeled to observed maximum increase (Yield), and the difference between the modeled peak time and observed peak time. Furthermore, to investigate latitudinal dependence of the performance of the models, the skill scores were calculated for five latitude regions. Our study shows that RMSE of TEC and TEC changes of the model simulations range from about 3 TECU (in high latitudes) to about 13 TECU (in low latitudes), which is larger than latitudinal average GPS TEC error of about 2 TECU. Most model simulations predict TEC better than TEC changes in terms of NRMSE and the difference in peak time, while the opposite holds true in terms of Yield. Model performance strongly depends on the quantities considered, the type of metrics used, and the latitude considered.

Jet-Like Structures and Wake in Mg I (518 nm) Images of 1999 Leonid Storm Meteors

Small meteoric fragments are ejected at significant transverse velocities from some (up to ~8%) fast Leonid meteors. We reach this conclusion using low light intensified image measurements obtained during the 1999 Leonid Multi-Instrument Aircraft Campaign. High spatial resolution, narrow band image measurements of the Mg I emission at 518 nm have been used to clearly identify jet-like features in the meteor head that are the same as first observed in white light by LeBlanc et al. (1999). We postulate that these unusual structures are caused by tiny meteoroid fragments (containing metallic grains) being rapidly ejected away from the core meteoroid as the constituent glue evaporates. Marked curvature observed in the jet-like filaments suggest that the parent meteoroids are spinning and as the whirling fragments are knocked away by the impinging air molecules, or by grain-grain collisions in the fragment ensemble, they ablate quickly generating an extended area of structured luminosity up to about 1–2 km from the meteoroid center. Fragments with smaller transverse velocity components are thought to be responsible for the associated beading evident in the wake of these unusual Leonid meteors.

The USU-GAIM-FP data assimilation model for ionospheric specifications and forecasts

Physics-based data assimilation models have been used in meteorology and oceanography for several decades and are now becoming prevalent for specifications and forecasts of the ionosphere. This increased use of ionospheric data assimilation models coincides with the increase in data suitable for assimilation. At USU we have developed several different data assimilation models, including the Global Assimilation on Ionospheric Measurements Gauss-Markov (GAIM-GM) and the Full Physics (GAIM-FP) models. Both models assimilate a variety of different data types, including ground-based GPS/TEC, occultation, bottomside electron density profiles from ionosondes, in-situ electron densities, and space-based UV radiance measurements and provide specifications and forecasts on a spatial grid that can be global, regional, or local. While GAIM-GM is a simpler model that uses a statistical process in the Kalman filter, GAIM-FP is based on a more sophisticated Ensemble Kalman filter technique together with a physics-based ionosphere-plasmasphere model (IPM). The primary GAIM-FP output is in the form of 3-dimensional electron density distributions from 90 km to near geosynchronous altitude but also provides auxiliary information about the global distributions of the self-consistent ionospheric drivers (neutral winds and densities, electric fields). The GAIM-FP model has recently been updated and extended to include the ionospheric D-region and to incorporate bubble information obtained from the SSUSI instruments. Furthermore, additional data types have been added to the list of possible observations that can be assimilated. This list includes slant TEC observations form satellite-to-satellite and satellite-to-ground radio beacons as well as radio occultation data and in situ plasma density observations from generic satellites.