Utah State University Global Assimilation Research Articles

Variable Responses of Equatorial Ionosphere During Undershielding and Overshielding Conditions

AbstractThis study tests the common assumption that the whole of the equatorial ionospheric F region responds uniformly to both undershielding prompt penetration and overshielding fields. Few recent studies have reported that the bottomside response to geomagnetic storms can differ significantly from that of the topside ionosphere. In this investigation, using vertical drift measurements from Jicamarca incoherent scatter radar in the altitude range of about 200 to 900 km, F region response to the space weather event on 9 November 2004 is studied. It is found that the F region showed large altitudinal variations in vertical drifts only under the influence of overshielding field. Such variations were negligible during undershielding prompt penetration conditions. In a first of its kind of study, direct observations of continuous altitudinal variations in vertical plasma drifts have been used to understand the response of F region ionosphere. This differential response to external drivers has a direct impact on the plasma transportations in the ionosphere and thus on estimating satellite drags. The observations are compared with the widely used ionosphere/thermosphere models: Thermosphere Ionosphere Electrodynamics General Circulation Model and Utah State University Global Assimilation of Ionospheric Measurements. It is found that contrary to observations, the Thermosphere Ionosphere Electrodynamics General Circulation Model shows very small altitudinal gradients in vertical drifts during both undershielding and overshielding conditions. Also, significant difference in the electron transportation especially at the bottomside between two models is adverted. Based on the observations, possible underlying physical processes of asymmetric interhemispheric potentials, different scale sizes of R1 and R2 current systems and different propagation modes for penetrating undershielding and overshielding fields are proposed.

Modeling the Midlatitude Ionosphere Storm‐Enhanced Density Distribution With a Data Assimilation Model

AbstractThe Utah State University Global Assimilation of Ionospheric Measurements‐Gauss Markov model has been used to investigate the distribution of ionospheric plasma during storm times over the continental United States. Storm periods dramatically increase the effects of space weather on the ionosphere and upper atmosphere, leading to impacts on over‐the‐horizon radars, Global Positioning System location determination, spacecraft charging, power grid overloads, and disruption of the Federal Aviation Administration Wide Area Augmentation System to name a few. Four storm periods were investigated where strong storm‐enhanced densities (SEDs) were present: two strong, October 2003 and November 2003, and two moderate, August 2010 and August 2011. It was found that a fundamental difference in the SED formation exists between the strong and moderate storms. For the strong storms, the SED was formed from the plasma in the northern equatorial anomaly crest, with the plasma in the SED channel lifting the closer it came to the high latitudes. For the moderate storms, the SED appeared to be unconnected to the northern anomaly crest but was rather produced locally in the SED channel, along with no corresponding increase in layer height associated with the SED evident in the model.

Regional 3‐D ionospheric electron density specification on the basis of data assimilation of ground‐based GNSS and radio occultation data

AbstractIn this paper, a regional 3‐D ionospheric electron density specification over China and adjacent areas (70°E–140°E in longitude, 15°N–55°N in latitude, and 100–900 km in altitude) is developed on the basis of data assimilation technique. The International Reference Ionosphere (IRI) is used as a background model, and a three‐dimensional variational technique is used to assimilate both the ground‐based Global Navigation Satellite System (GNSS) observations from the Crustal Movement Observation Network of China (CMONOC) and International GNSS Service (IGS) and the ionospheric radio occultation (RO) data from FORMOSAT‐3/COSMIC (F3/C) satellites. The regional 3‐D gridded ionospheric electron densities can be generated with temporal resolution of 5 min in universal time, horizontal resolution of 2° × 2° in latitude and longitude, and vertical resolution of 20 km between 100 and 500 km and 50 km between 500 and 900 km. The data assimilation results are validated through extensive comparison with several sources of electron density information, including (1) ionospheric total electron content (TEC); (2) Abel‐retrieved F3/C electron density profiles (EDPs); (3) ionosonde foF2 and bottomside EDPs; and (4) the Utah State University Global Assimilation of Ionospheric Measurements (USU‐GAIM) under both geomagnetic quiet and disturbed conditions. The validation results show that the data assimilation procedure pushes the climatological IRI model toward the observation, and a general accuracy improvement of 15–30% can be expected. Thecomparisons also indicate that the data assimilation results are more close to the Center for Orbit Determination of Europe (CODE) TEC and Madrigal TEC products than USU‐GAIM. These initial results might demonstrate the effectiveness of the data assimilation technique in improving specification of local ionospheric morphology.

Magnetic meridional winds in the thermosphere obtained from Global Assimilation of Ionospheric Measurements (GAIM) model

AbstractThermospheric neutral winds play an important part in the dynamics of ionospheric plasma and represent one of the key inputs for ionospheric physics‐based models. Yet wind measurements are scarce and generally lack global coverage and continuity. To help mitigate this shortcoming, a data assimilation model was used to estimate neutral winds in the low‐ and middle‐latitude thermosphere. Seasonal global maps of NmF2 and hmF2 were generated from Constellation Observing System for Meteorology, Ionosphere, and Climate radio occultation measurements for geomagnetically quiet and low solar flux conditions. The maps were assimilated into the Utah State University Global Assimilation of Ionospheric Measurements–Full Physics (GAIM‐FP) model. GAIM‐FP, which uses the physics‐based ionosphere‐plasmasphere model (IPM) and employs an ensemble Kalman filter technique, significantly improved the agreement between the modeled and measured NmF2 and hmF2 globally compared to the IPM. Global quiet time magnetic meridional winds were derived for December and June solstices and March equinox. The morphology of the derived winds was analyzed and validated by comparing with ground‐based measurements and with wind values from the empirical horizontal wind model. GAIM‐FP‐estimated winds were shown to be in good agreement with the wind observations. Furthermore, the sensitivity of the derived winds to uncertain parameters, including the O+‐O collision frequency, neutral composition, number of radio occultations, and data errors, was investigated. The uncertainties were found to have only small effects on the derived winds. The results of this work indicate that thermospheric wind estimation from GAIM‐FP is a valuable tool for wind specification over regions where limited or no wind measurements exist.

Methodology of evaluating the science benefit of various satellite/sensor constellation orbital parameters to an assimilative data forecast model

AbstractA methodology for evaluating the science benefit of adding space weather sensor data from a modest number of small satellites to the Utah State University Global Assimilation of Ionospheric Measurements—Full Physics (GAIM‐FP) model is presented. Three orbital scenarios are presented, two focusing on improved coverage of narrowly specified regions of interest, and one on global coverage of the ionosphere as a whole. An Observing System Simulation Experiment is used to obtain qualitative and quantitative results of the impact of the various orbital scenarios on the ionospheric specifications. A simulated “truth” run of the ionosphere is obtained from a first principle model of the ionosphere/plasmasphere model and used to generate global simulated Global Positioning Satellite total electron content (GPS‐TEC) data as well as in situ plasma density observations. Initially, only GPS data were assimilated by GAIM‐FP, and the results of this limited run were compared to the truth run. Next, the simulated in situ plasma densities corresponding to our three orbital scenarios were assimilated together with the GPS data, and the results were compared to both the truth run and the limited GPS‐TEC only GAIM‐FP run. These model simulations have shown that adding a constellation of small satellites/sensors in addition to global TEC inputs does indeed converge the GAIM‐FP model closer to truth in the situations described.

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

AbstractThe Earth's 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.

The effect of geomagnetic‐storm‐induced enhancements to ionospheric emissions on the interpretation of the TIMED/GUVI O/N2 ratio

AbstractWe examine the consequence of enhanced atomic oxygen (OI) 135.6 nm emissions due to the recombination of O+ with electrons on the column number density ratio of atomic oxygen to molecular nitrogen (O/N2 ratio) provided by Global Ultraviolet Imager (GUVI) on board the Thermosphere, Ionosphere, Mesosphere Energetics and Dynamics satellite. GUVI O/N2 ratio is derived from the measurements of OI 135.6 nm and N2 Lyman‐Birge‐Hopfield airglow emissions. The OI 135.6 nm emission arises from two sources: photoelectron impact excitation of neutral atomic oxygen and the radiative recombination of O+ with electrons. We estimate the O/N2 ratio disturbance associated with the O+ density enhancement during geomagnetic storms through the case study of the storms on 20 November 2003 and 8 November 2004. The OI 135.6 nm emission enhancement originating from the ionosphere is derived using the Utah State University Global Assimilation of Ionospheric Measurements model ionosphere. Our results show that the O/N2 ratio increase from the equator to middle latitudes during the storm periods is primarily associated with thermospheric neutral composition disturbances. However, the contribution of the OI 135.6 nm emission originating from the ionosphere to the storm time O/N2 ratio increase is substantial in the northern low‐middle latitude regions where severe plasma density enhancements occur during the main phase of the storms. Therefore, the ionospheric contribution should be considered for an accurate assessment of the storm time O/N2 ratio increase at low‐middle latitudes during these large storm events.

Assimilation of ionosonde profiles into a global ionospheric model

The Utah State University Global Assimilation of Ionospheric Measurements (GAIM) ionospheric model has been run for multiday intervals in November 2008 and February/March 2009, to investigate the model's ability to assimilate plasma frequency profiles provided by Digisondes. Ionosondes are currently the only type of assimilation data that can provide information on the profile below the peak of the F2 layer. Attention has been focused on the Republic of South Africa, which has four Digisondes and thus offers a unique validation environment. The model has been run for multiple assimilation data scenarios, some of which include GPS total electron content (TEC) observations, in order to provide benchmarks for testing the profile assimilation. The Hermanus Digisonde was set aside to provide the ground truth, in particular the values of foF2, hmF2, and the width of the F2 layer. The values of these characteristics were also tested at the other three ionosonde sites, since the data assimilation procedures do not usually reproduce the assimilated data exactly. It was found that assimilation of ionosonde data did not improve the accuracy of the GAIM values of foF2 at Hermanus (or Grahamstown) beyond that provided by the GPS TEC data, but these TEC‐only errors were already relatively small. However, the ionosonde‐only errors were smaller than the relatively large TEC‐only errors for Louisvale and Madimbo. Assimilation of ionosonde data did not provide any significant increases in the accuracy of the model values of hmF2 and width of the F2 layer.

Development of an HF selection tool based on the Electron Density Assimilative Model near‐real‐time ionosphere

The Electron Density Assimilative Model (EDAM) has been developed to provide real‐time characterization of the ionosphere. A thin‐client Web‐based ionospheric situational awareness tool, which relies on data from EDAM, has been developed. The tool provides the high‐frequency (HF) maximum usable frequency (MUF) and the optimum working frequency (FOT) on the basis of the current ionospheric electron density grid from EDAM. Two validations are reported. First, EDAM has been tested against a set of vertical ionosondes. The results show performance comparable to that of the Utah State University Global Assimilation of Ionospheric Measurements Gauss–Markov Kalman filter model. Second, MUFs estimated from EDAM were compared with those measured on an oblique path from New Zealand to Australia. Although EDAM demonstrates better performance than a monthly median model in some days, over the whole test period EDAM performed no better than the international reference ionosphere. This can be attributed to the lack of input GPS total electron content (TEC) data near the midpoint of the path and a probable TEC bias in the background model.

Validation of the Utah State University Global Assimilation of Ionospheric Measurements (GAIM) model predictions of the maximum usable frequency for a 3000 km circuit

The accuracy of the Utah State University Global Assimilation of Ionospheric Measurements (GAIM) monthly median values of the maximum usable frequency for an HF communications circuit has been determined for 3000 km circuits centered on Australian ionosonde locations for March and April 2004. The accuracy is discussed in terms of foF2, M(3000)F2, and the product MUF(3000)F2 = foF2 * M(3000)F2. Ground truth is provided by hourly values of foF2 and M(3000)F2 that have been hand‐scaled from ionograms. In general, the accuracy of the GAIM predictions of foF2 exceeds that for M(3000)F2. Given that M(3000)F2 is a function of the height and shape of the F2 subpeak, it follows that these parameters of the GAIM F2 peak need to be improved. The GAIM errors in foF2 are quite large at Learmonth during the day, even though Learmonth is a digital ionospheric sounding systems (DISS) station that provides real‐time data to GAIM. We interpret these errors in terms of limitations of the current GAIM model. Comparisons of the GAIM errors in the monthly median MUF(3000)F2 with those given by the propagation prediction program Advanced Stand Alone Prediction System (ASAPS) show that the GAIM errors are generally somewhat greater than the ASAPS errors, but we consider GAIM's performance to be creditable given that most of the data available for assimilation is GPS total electron content observations. Overall, the daytime GAIM errors are 3 MHz or 10%, while the nighttime errors are 3 MHz or 16%. On average, the GAIM errors are about 3/2 the ASAPS errors during the day and twice the ASAPS errors at night.

Utah State University Global Assimilation of Ionospheric Measurements Gauss‐Markov Kalman filter model of the ionosphere: Model description and validation

The Utah State University Gauss‐Markov Kalman Filter (GMKF) was developed as part of the Global Assimilation of Ionospheric Measurements (GAIM) program. The GMKF uses a physics‐based model of the ionosphere and a Gauss‐Markov Kalman filter as a basis for assimilating a diverse set of real‐time (or near real‐time) observations. The physics‐based model is the Ionospheric Forecast Model (IFM), which accounts for five ion species and covers the E region, F region, and the topside from 90 to 1400 km altitude. Within the GMKF, the IFM derived ionospheric densities constitute a background density field on which perturbations are superimposed based on the available data and their errors. In the current configuration, the GMKF assimilates slant total electron content (TEC) from a variable number of global positioning satellite (GPS) ground sites, bottomside electron density (Ne) profiles from a variable number of ionosondes, in situ Ne from four Defense Meteorological Satellite Program (DMSP) satellites, and nighttime line‐of‐sight ultraviolet (UV) radiances measured by satellites. To test the GMKF for real‐time operations and to validate its ionospheric density specifications, we have tested the model performance for a variety of geophysical conditions. During these model runs various combination of data types and data quantities were assimilated. To simulate real‐time operations, the model ran continuously and automatically and produced three‐dimensional global electron density distributions in 15 min increments. In this paper we will describe the Gauss‐Markov Kalman filter model and present results of our validation study, with an emphasis on comparisons with independent observations.

Extreme longitudinal variability of plasma structuring in the equatorial ionosphere on a magnetically quiet equinoctial day

We investigate the extreme longitudinal variability of equatorial scintillation under quiet magnetic conditions during 22–23 March 2002. Scintillation Network Decision Aid (SCINDA) observations show intense activity in the South American–Atlantic sector during local evening hours, whereas an absence of scintillation is seen in the far east Asian sector. Ground‐ and space‐based measurements from SCINDA, the Global Ultraviolet Imager (GUVI), TOPEX, and a chain of GPS receivers are used in combination with the Utah State University Global Assimilation of Ionospheric Measurements (USU‐GAIM) model to explore the relationship between the large‐scale ionization distribution and small‐scale irregularities at low latitudes in both the scintillating and nonscintillating longitude sectors. Our analysis shows that there are significant differences in the evolution of the ionization distributions during the evening hours, which are likely the result of differences in the daytime and postsunset vertical plasma drift in the two sectors. This study demonstrates the importance of USU‐GAIM as a new tool for investigating longitudinal as well as day‐to‐day variability that is observed in the large‐scale distribution of the ionosphere and how this relates to the occurrence of scintillation.

Validation study of the Ionosphere Forecast Model using the TOPEX total electron content measurements

As a part of the validation program in the Utah State University Global Assimilation of Ionospheric Measurement (GAIM) project, a newly improved Ionosphere Forecast Model (IFM) was systematically validated by using a large database of TOPEX total electron content (TEC) measurements. The TOPEX data used for the validation are for the period from August 1992 to March 2003, and the total number of 18‐s averaged data is close to 11 million. This model validation work covers a wide range of seasonal (winter, summer, and equinox) and solar (low‐F10.7, median F10.7, and high‐F10.7) conditions as well as all UT variations with the focus on nonstorm time TEC. The validation results indicate that the features of the spatial distribution of the IFM TEC are systematically consistent with those of the TOPEX TEC. The differences between the IFM TEC and the TOPEX TEC are within 20% for almost all locations and conditions. For many conditions, the differences are even below 10%.