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Results for “ionosphere GPS data assimilation”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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10 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS2004

Assimilative modeling of low latitude ionosphere

In this paper we present an observation system simulation experiment for modeling low-latitude ionosphere using a 3-dimensional (3-D) global assimilative ionospheric model (GAIM). The experiment is conducted to test the effectiveness of GAIM with a 4-D variational approach (4DVAR) in estimation of the ExB drift and thermospheric wind in the magnetic meridional planes simultaneously for all longitude or local time sectors. The operational Global Positioning System (GPS) satellites and the ground-based global GPS receiver network of the International GPS Service are used in the experiment as the data assimilation source. 'The optimization of the ionospheric state (electron density) modeling is performed through a nonlinear least-squares minimization process that adjusts the dynamical forces to reduce the difference between the modeled and observed slant total electron content in the entire modeled region. The present experiment for multiple force estimations reinforces our previous assessment made through single driver estimations conducted for the ExB drift only.

data assimilation↗
NASA NTRS1999

Capabilities and Limitations of Radio Occultation Measurements for Ionosphere Monitoring

The paper: (1) describes the range of capabilities of GPS radio occultation missions in ionospheric research: (a) ionospheric profiling; (b) ionospheric imaging; (c) ionospheric data assimilation; and (d) measurement of scintillation. (2) Identify strengths and weaknesses of measurements: (a) coverage; (b) resolution; and (c) uniqueness of solution.

Hajj, G. A.↗
NASA NTRS2013

Ionospheric Simulation System for Satellite Observations and Global Assimilative Model Experiments - ISOGAME

Modeling and imaging the Earth's ionosphere as well as understanding its structures, inhomogeneities, and disturbances is a key part of NASA's Heliophysics Directorate science roadmap. This invention provides a design tool for scientific missions focused on the ionosphere. It is a scientifically important and technologically challenging task to assess the impact of a new observation system quantitatively on our capability of imaging and modeling the ionosphere. This question is often raised whenever a new satellite system is proposed, a new type of data is emerging, or a new modeling technique is developed. The proposed constellation would be part of a new observation system with more low-Earth orbiters tracking more radio occultation signals broadcast by Global Navigation Satellite System (GNSS) than those offered by the current GPS and COSMIC observation system. A simulation system was developed to fulfill this task. The system is composed of a suite of software that combines the Global Assimilative Ionospheric Model (GAIM) including first-principles and empirical ionospheric models, a multiple- dipole geomagnetic field model, data assimilation modules, observation simulator, visualization software, and orbit design, simulation, and optimization software.

Pi, Xiaoqing↗
NASA NTRS2017

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 total electron content (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 December 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 (total electron content unit, 1 TECU = 1016 el m2) (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.

Shim, J. S.↗
NASA NTRS1997

Correction of Single Frequency Altimeter Measurements for Ionosphere Delay

This study is a preliminary analysis of the accuracy of various ionosphere models to correct single frequency altimeter height measurements for Ionospheric path delay. In particular, research focused on adjusting empirical and parameterized ionosphere models in the parameterized real-time ionospheric specification model (PRISM) 1.2 using total electron content (TEC) data from the global positioning system (GPS). The types of GPS data used to adjust PRISM included GPS line-of-sight (LOS) TEC data mapped to the vertical, and a grid of GPS derived TEC data in a sun-fixed longitude frame. The adjusted PRISM TEC values, as well as predictions by IRI-90, a climatotogical model, were compared to TOPEX/Poseidon (T/P) TEC measurements from the dual-frequency altimeter for a number of T/P tracks. When adjusted with GPS LOS data, the PRISM empirical model predicted TEC over 24 1 h data sets for a given local time to with in a global error of 8.60 TECU rms during a midnight centered ionosphere and 9.74 TECU rms during a noon centered ionosphere. Using GPS derived sun-fixed TEC data, the PRISM parameterized model predicted TEC within an error of 8.47 TECU rms centered at midnight and 12.83 TECU rms centered at noon. From these best results, it is clear that the proposed requirement of 3-4 TECU global rms for TOPEX/Poseidon Follow-On will be very difficult to meet, even with a substantial increase in the number of GPS ground stations, with any realizable combination of the aforementioned models or data assimilation schemes.

Schreiner, William S.↗
NASA NTRS1994

Ionospheric calibration for single frequency altimeter measurements

This study is a preliminary analysis of the effectiveness (in terms of altimeter calibration accuracy) of various ionosphere models and the Global Positioning System (GPS) to calibrate single frequency altimeter height measurements for ionospheric path delay. In particular, the research focused on ingesting GPS Total Electron Content (TEC) data into the physical Parameterized Real-Time Ionospheric Specification Model (PRISM), which estimates the composition of the ionosphere using independent empirical and physical models and has the capability of adjusting to additional ionospheric measurements. Two types of GPS data were used to adjust the PRISM model: GPS receiver station data mapped from line-of-sight observations to the vertical at the point of interest and a grid map (generated at the Jet Propulsion Laboratory) of GPS derived TEC in a sun-fixed longitude frame. The adjusted PRISM TEC values, as well as predictions by the International Reference Ionosphere (IRI-90), a climatological (monthly mean) model of the ionosphere, were compared to TOPEX dual-frequency TEC measurements (considered as truth) for a number of TOPEX sub-satellite tracks. For a 13.6 GHz altimeter, a Total Electron Content (TEC) of 1 TECU 10(exp 16) electrons/sq m corresponds to approximately 0.218 centimeters of range delay. A maximum expected TEC (at solar maximum or during solar storms) of 10(exp 18) electrons/sq m will create 22 centimeters of range delay. Compared with the TOPEX data, the PRISM predictions were generally accurate within the TECU when the sub-satellite track of interest passed within 300 to 400 km of the GPS TEC data or when the track passed through a night-time ionosphere. If neither was the case, in particular if the track passed through a local noon ionosphere, the PRISM values differed by more than 10 TECU and by as much as 40 TECU. The IRI-90 model, with no current ability to unseat GPS data, predicted TEC to a slightly higher error of 12 TECU. The performance of PRISM is very promising for predicting TEC and will prove useful for calibrating single frequency altimeter height measurements for ionospheric path delay. When adjusted to the GPS line-of-sight data the PRISM URSI empirical model predicted TEC over a day's period to within a global error of 8.60 TECU rms during a nighttime ionosphere and 9.74 TECU rms during the day. When adjusted to the GPS derived TEC grid, the PRISM parametrized model predicted TEC to within an error of 8.47 TECU rms for a nighttime ionosphere and 12.83 TECU rms during the day. However, the grid cannot be considered globally due to the lack of sufficient numbers of GPS stations and large latitude gaps in GPS data. It is the opinion of the authors that using the PRISM model and adjusting to the global sun-fixed TEC grid regenerated with a localized weighted interpolation offers the best possibility of meeting the 10 TECU global rms (or 2 cm at 13.6 GHz) ionosphere range correction accuracy requirement of TOPEX/Poseidon and should be the subject of further study. However, it is clear that the anticipated requirement of 34 TECU global rms for TOPEX/Poseidon Follow-On (corresponding to the TOPEX/Poseidon performance) can not be met with any realizable combination of existing models and data assimilation schemes.

Schreiner, William S.↗
NASA NTRS2023

The Ionospheric Three-Dimensional Electron Density Variations Induced by the 21 August 2017 Total Solar Eclipse by Using Global Ionospheric Specification

Global Ionospheric Specification (GIS) is based on the Gauss–Markov Kalman filter to assimilate the slant total electron content (TEC) observed from ground-based GPS receivers and space-based radio occultation instrumentations in order to reconstruct three-dimensional (3D) ionospheric electron density structure, and it can remotely sense and monitor the weather condition in space. In this study, five minutes of high temporal resolution GIS is implemented in order to reconstruct the 3D electron density structure on the 21 August 2017 total solar eclipse and analyze the variations induced by the moon’s shadow. To obtain more information of the ionosphere, from the extend 2200 GPS stations on the continental United States, are added for assimilation. The results show the ionosphere peak height (hmF2) uplift was 30–50 km altitude in latitude 25–40°N, and that the electron density depletion at higher altitudes (400 km) has a more noticeable time delay than at low altitudes (200 km), especially in low-latitude regions.

Ionosphere↗