International Reference Ionosphere 2016: From ionospheric climate to real‐time weather predictions

Bilitza, D.; Altadill, D.; Truhlík, Vladimír; Шубин, В.Н.; Galkin, I. A.; Reinisch, B. W.; Huang, Xiangdong

doi:10.1002/2016sw001593

Cited by 879 publications

(594 citation statements)

References 49 publications

Supporting

Mentioning

586

Contrasting

Unclassified

Order By: Relevance

“…Although this analytical expression was obtained for a daytime mid-latitude stationary F 2 -layer, without including the thermospheric wind effects, it gives reasonable h m F 2 values. This is confirmed by a comparison with a modern empirical monthly median h m F 2 model by Shubin (2015) included to the last version of IRI (Bilitza et al, 2017). To check this result we have used the MSIS-86 monthly median values of the thermospheric parameters in equation (3).…”

Section: Discussionmentioning

confidence: 64%

Long-term variations of the upper atmosphere parameters on Rome ionosonde observations and their interpretation

Perrone

Mikhailov

Cesaroni

et al. 2017

J. Space Weather Space Clim.

View full text Add to dashboard Cite

-A recently proposed self-consistent approach to the analysis of thermospheric and ionospheric long-term trends has been applied to Rome ionosonde summer noontime observations for the period. This approach includes: (i) a method to extract ionospheric parameter long-term variations; (ii) a method to retrieve from observed f o F 1 neutral composition (O, O 2 , N 2 ), exospheric temperature, Tex and the total solar EUV flux with l < 1050 Å; and (iii) a combined analysis of the ionospheric and thermospheric parameter long-term variations using the theory of ionospheric F-layer formation. Atomic oxygen, [O] period which is mainly due to atomic oxygen decrease after ∼1990. A linear trend in (dh m F 2 ) 11y estimated over the period is very small and insignificant reflecting the absence of any significant trend in neutral temperature. The retrieved neutral gas density, r atomic oxygen, [O] and exospheric temperature, Tex long-term variations are controlled by solar and geomagnetic activity, i.e. they have a natural origin. The residual trends estimated over the period of ∼5 solar cycles are very small (<0.5% per decade) and statistically.

show abstract

Section: Discussionmentioning

confidence: 64%

Long-term variations of the upper atmosphere parameters on Rome ionosonde observations and their interpretation

Perrone

Mikhailov

Cesaroni

et al. 2017

J. Space Weather Space Clim.

View full text Add to dashboard Cite

show abstract

“…More importantly, the ionosphere is highly dynamic and can exhibit disparate characteristics from one day to the next. The International Reference Ionosphere 2016 modelh ′ and̄curves are determined at the GCP midpoint location for NML-OX on 4 October 2017 (Bilitza et al, 2016). Finally, Earth's background magnetic field, and thus ionosphere, have unique characteristics depending on latitude and longitude.…”

Section: Comparison To Past Workmentioning

confidence: 99%

VLF Remote Sensing of the D Region Ionosphere Using Neural Networks

Gross

Cohen

2020

JGR Space Physics

View full text Add to dashboard Cite

Narrowband very low frequency (VLF) remote sensing has proven to be a useful tool for characterizing the ionosphere's D region (60-to 90-km altitude) electron density. This work expands upon single transmitter-receiver pair electron density profile inference methods to create a more generalized narrowband VLF remote sensing method that concurrently resolves a two-parameter electron density profile for an arbitrary number of transmitter-receiver pairs. A target function is constructed to take in a single time step of narrowband amplitude and phase observations from an arbitrary number of transmitter and receiver combinations and return the inferred average waveguide parameters along all paths. The target function is approximated using an artificial neural network (ANN). Synthetic training data are generated using the U.S. Navy's Long-Wavelength Propagation Capability program, which is then used to train the ANN. Performance of the ANN with real-world data is measured in two ways. First, ANN inferred average waveguide parameters are compared to a variety of previously published narrowband VLF remote sensing experiments. Second, ANN inferred average waveguide parameters are used in Long-Wavelength Propagation Capability to predict narrowband VLF amplitude and carrier phase at a receiver that was withheld when performing the average waveguide parameter inference. Results show the approximated target function performs well in capturing temporal and spatial characteristics of the D region.

show abstract

“…The empirical models, on the other hand, are less expensive computationally, and thus the data assimilation approaches that utilize empirical background models continue to be appealing. Fuller‐Rowell et al () and Araujo‐Pradere et al () have constructed the NOAA United States‐Total Electron Contents (US‐TEC) procedure based on the empirical model of International Reference Ionosphere (IRI) (Bilitza, ; Bilitza et al, , ) to reconstruct the total electron content (TEC) over the U.S. from ground‐based GPS data using the Kalman filter. Bust et al (, ) have developed a data assimilation procedure based on the 3DVAR, while Yue et al () and Yue, Schreiner, Kuo, et al () have developed a procedure to assimilate multiple types of satellite observations into an empirical background model using the state measurement update equation of Kalman filter without updating the model error covariance and performing time‐forward forecast of the model state and error covariance.…”

Section: Introductionmentioning

confidence: 99%

Data Assimilation of Ground‐Based GPS and Radio Occultation Total Electron Content for Global Ionospheric Specification

et al. 2017

View full text Add to dashboard Cite

This study presents an approach based on the Gauss‐Markov Kalman filter to assimilate the total electron content observed from ground‐based GPS receivers and space‐based radio occultation instrumentations (such as FORMOSAT‐3/COSMIC (F3/C) and FORMOSAT‐7/COSMIC‐2 (F7/C2)) into the International Reference Ionosphere. Observing System Simulation Experiments (OSSEs) show that the data assimilation procedure consisting of the forecast and the measurement update steps can better improve the accuracy of the data assimilation analysis than the assimilation procedure using the measurement update alone. Compared with F3/C, the denser F7/C2 occultation observations can improve the analysis accuracy significantly as suggested by OSSEs. The real data assimilation results are further validated with global ionosphere maps, the global ground‐based GPS measurements, and the ionospheric F2 peak height and electron density sounded by ionosondes. Both the OSSEs and validation results confirm that a number of improvements to the data assimilation procedure presented in this paper can indeed be used to reconstruct the three‐dimensional ionospheric electron density adequately.

show abstract

International Reference Ionosphere 2016: From ionospheric climate to real‐time weather predictions

Cited by 879 publications

References 49 publications

Long-term variations of the upper atmosphere parameters on Rome ionosonde observations and their interpretation

Long-term variations of the upper atmosphere parameters on Rome ionosonde observations and their interpretation

VLF Remote Sensing of the D Region Ionosphere Using Neural Networks

Data Assimilation of Ground‐Based GPS and Radio Occultation Total Electron Content for Global Ionospheric Specification

Contact Info

Product

Resources

About