Observations and Simulations of Eddy Diffusion and TidalEffects on the Semiannual Oscillation in the IonosphereQian Wu1,2 , W. S. Schreiner2, S.-P. Ho2, H.-L. Liu1 , and Liying Qian1

1High Altitude Observatory, National Center for Atmospheric Research, Boulder, CO, USA, 2COSMIC Program Office,University Corporation for Atmospheric Research, Boulder, CO, USA

Abstract We use the National Center for Atmospheric Research TIEGCM (Thermosphere IonosphereElectrodynamics General Circulation Model) model to investigate the eddy diffusion and tidal effects onthe ionosphere SAO (semiannual oscillation). We also use the COSMIC (Constellation Observing System forMeteorology, Ionosphere, and Climate) satellite GPS radio occultation observations to validate the simulationresults. The TIEGCM is driven at the 97 km lower boundary by tidal and gravity wave (eddy diffusioncoefficient) inputs. The eddy diffusion input can be constant or with a SAO modulation, and the tidal inputhas on and off options. The TIEGCM simulation with a SAO modulated eddy diffusion (with tidal input)agrees better with the COSMIC observation than that without the SAO. Turning off the tides at the lowerboundary makes the TIEGCM-simulated ionospheric density much higher than the COSMIC observation. Thesimulations showed two results: (1) the need to add the SAO modulation to the eddy diffusion and (2) howtides reduce the ionospheric density and SAO. As to how much of the SAO should be added to the eddydiffusion is dependent on the amplitudes of the tides since both can have effects on the ionospheric density.The TIEGCM results also demonstrate that the ionospheric density diurnal signal is mostly in situ excited,while the semidiurnal signal comes from lower atmosphere.

1. Introduction

A study by Qian et al. (2009) (Q09) showed that the eddy diffusion has a strong impact on thermospheric den-sity seasonal variations. In order to make the National Center for Atmospheric Research ThermosphereIonosphere Electrodynamics General Circulation Model (NCAR TIEGCM) model produce similar amplitudesof the annual/semiannual oscillations (AOs/SAOs) in the thermosphere, Q09 imposed a seasonal varying eddycoefficient Kzz (hereafter SAO Kzz) at the TIEGCM lower boundary that was able to reproduce similar ampli-tudes of AO/SAO. The eddy diffusion coefficient Kzz is in the unit of m2/s (e.g., Vlasov & Kelley, 2015). A factorof 2 increase of the eddy diffusion coefficient reduces the thermospheric density at 400 km by 20% (Q09).Q09 performed a fitting to satellite drag data and obtained the SAO Kzz shown in Q09 Figure 6. The Kzz variesfrom ~50 m2/s during equinoxes to ~250 m2/s during the June solstice and is an antimodulation of thethermospheric density. The decrease in Kzz during equinoxes increases the thermospheric density and theincrease of the Kzz during June solstice suppresses the density leading to an increase of the SAO in the ther-mospheric density. Eddy diffusion reduces both O/N2 and temperature, thus the density (Q09). According toQian et al. (2013), eddy diffusion brings the O downward and O can be lost due to the lower boundarycondition that is set to have the vertical gradient of O be zero. Downward motion of the O also leads tomore three body recombination, which also destroys O. As Qian et al. (2013) pointed out, SAO Kzz is anad hoc measure to simulate the gravity wave effect on the thermosphere and ionosphere. We should alsopoint out that Q09 used an effective Kzz, which may contain more than the gravity wave effect. Qian et al.(2013) used the TIEGCM model to examine the eddy diffusion effect on the AO/SAO variation of the iono-sphere and showed some discrepancies in the F2 peak electron densities between the model and observa-tions. For example, the model showed a midlatitude ionosphere winter anomaly for solar minimum years,whereas the Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC) data didnot (Burns et al., 2014, 2015).

Moreover, not all simulations showed the need for a consistent SAO for the eddy diffusion. For example,Siskind et al. (2014) (S14) used NOGAPS output as the lower boundary to drive the TIEGCM and experimentedwith different Kzz and tidal configurations for the TIEGCM. When S14 used a standard constant Kzz (125 m

2/s)for TIEGCM, they obtained a small SAO in the ionosphere. Then, they reduced the constant Kzz by a factor of 5

WU ET AL. INVESTIGATION OF IONOSPHERE SAO 10,502

PUBLICATIONSJournal of Geophysical Research: Space Physics

RESEARCH ARTICLE10.1002/2017JA024341

Key Points:• Imposing SAO to the eddy diffusioncoefficient in the TIEGCM increasesthe ionosphere SAO and has betteragreement with COSMIC observations

• The diurnal variation DW1 in theelectron density increase in theTIEGCM simulation is proportional tothe electron density with GSWM input

• The simulation from TIEGCM showedthe SW2 signal in the ionosphere ismostly from lower atmosphere

Correspondence to:Q. Wu,qwu@ucar.edu

Citation:Wu, Q., Schreiner, W. S., Ho, S.-P.,Liu, H.-L., & Qian, L. (2017). Observationsand simulations of eddy diffusionand tidal effects on the semiannualoscillation in the ionosphere. Journal ofGeophysical Research: Space Physics, 122,10,502–10,510. https://doi.org/10.1002/2017JA024341

Received 8 MAY 2017Accepted 9 SEP 2017Accepted article online 14 SEP 2017Published online 5 OCT 2017

©2017. American Geophysical Union.All Rights Reserved.

and obtained a larger SAO in the ionosphere, which is comparable to the standard GSWM (global scale wavemodel) run of TIEGCM with a standard constant Kzz. Salinas et al. (2016) used Kzz based on SABER CO2 obser-vation (KzzC) to drive the TIEGCM; the KzzC is smaller than that from Q09 with a smaller SAO. Their TIEGCMsimulation with KzzC produced smaller SAO in the ionosphere compared to the observations and Q09. Theelectron density, on the other hand, is larger than that based on Q09 parameters. Recently, Jones et al.(2017) (J17) using the NCAR TIMEGCMwere able to obtain similar amplitudes of the SAO in the thermospherewith a Kzz similar to the KzzC and without adding SAO to the Kzz. It is apparent from these studies that there arestill many unresolved issues associated with the Kzz effect on the SAO of the thermosphere and ionosphere.

Beyond the Kzz effect, Yamazaki and Richmond (2013) and Jones et al. (2014) have pointed out that the tidesmay have similar effect on the ionospheric density as the Kzz shown by Q09. They suggested that the tidescould change the O concentration in themesosphere due to vertical transport. Hence, it is important to inves-tigate the combined effects of the Kzz and tides on the ionosphere.

Towards that goal, we use the NCAR TIEGCM model simulations with SAO varying eddy diffusion (SAO Kzz)and that with a constant eddy diffusion (125 m2/s) for a comparison with COSMIC observations. We alsoexamine the tidal effect by turning the tides on and off in the TIEGCM. Given the tides may have effect onthe ionospheric density, we will examine not only the mean electron density but also diurnal and semidiurnaltides in the ionosphere and their responses to the eddy diffusion and tides.

The paper is organized as follows. Brief descriptions of the TIEGCMmodel and COSMIC observation are givenin the following section. Simulations and observations are then compared and discussed. Finally, we summar-ize our findings.

2. Thermosphere-Ionosphere Electrodynamics General Circulation Model

TIEGCM is a first-principles ionosphere thermosphere general circulation model based on the continuity,momentum, and energy equations (Qian et al., 2014; Richmond, Ridley, & Roble, 1992; Roble et al., 1982,1987, 1988; Roble & Ridley, 1987, 1994). In the vertical direction, themodel covers pressure surface levels from�7 to 7 (~ 97 to ~600 km). The pressure levels are defined as z = ln(P0/P), where P0 is a reference pressure of5 × 10�4 mb (~240 km). We used 2.5° × 2.5° horizontal resolution. The model is driven at high latitudes by theWeimer ion convectionmodel (Weimer, 2005). Themodel uses the solar F10.7 index as a proxy for solar UV andEUV inputs. At the lower boundary, the model uses the GSWM, which can include both migrating and non-migrating tidal inputs (Hagan & Forbes, 2002). As mentioned earlier, Q09 added the SAO to Kzz (SAO Kzz) tothe TIEGCM lower boundary. We performed two TIEGCM annual runs for the year 2008 with the GSWM tides,one with SAO Kzz, and one with a constant Kzz (125 m2/s for all location and time). We also performed aTIEGCM annual run with the SAO Kzzwithout the GSWM tides. In our simulations, we did not include the non-migrating tides in the GSWM.

3. Constellation Observing System for Meteorology, Ionosphere, and ClimateObservations

COSMIC is a six-satellite constellation that provides GPS radio occultation (RO) data of both lower atmosphereand ionosphere (Anthes, 2011; Anthes et al., 2008). The GPS RO data were inverted to obtain ionospheric elec-tron density profiles using an Abel inversion technique (Schreiner et al., 1999, 2007). The COSMIC data havebeen used widely in ionosphere research and compared with ground-based ionosonde data by Lei et al.(2007), who mostly showed consistent results. Yue et al. (2010) estimated the error characteristics of theCOSMIC Abel retrievals, which showed relatively small magnitude errors for altitudes used in this study(above 250 km altitude). The six COSMIC satellites were launched into the same orbit in 2006 and graduallyseparated in local time. We selected the year of 2008 for this analysis, because by then the COSMIC satelliteshad been separated in local time. Another reason for selecting 2008 is the low solar activity when the loweratmospheric effect on the ionosphere is more prominent.

4. Data Processing

COSMIC electron density profile data were binned into magnetic latitude (5°) and altitude (1 km) bins. A20 day sliding window was used to select data from each bin. Then the electron density data were

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analyzed with a 2-D Lomb Scargle method in longitude and universal time to extract tidal signals of differentfrequencies and zonal wave numbers. In this study, the stationary zonal wave number 0 component is usedas the mean electron density. The same method was used by Wu et al. (2008, 2009).

The TIEGCM simulation results are also processed with this method. The results are binned in magnetic lati-tude (2.5°) and altitude (a quarter of the scale height). A 5 day sliding window is used for the model becausethe models have the coverage for all local times at all longitudes (hourly data).

5. Simulation and Observation Comparison and Discussion5.1. Mean Electron Density

Figure 1 shows the COSMIC observations (a) and TIEGCM simulations of the mean electron density at~290 km at pressure level 1.875. The TIEGCM simulations were performed with SAO Kzz (b), with a constant

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Figure 1. (a) COSMIC observation, (b) TIEGCM simulations of electron density with SAO, and (c) with constant Kzz withGSWM tidal inputs and (d) without GSWM inputs but with SAO Kzz at 1.875 pressure level (~ 290 km). The density unit is102 cm�3. The values were obtained by averaging (universal time and longitude) in different magnetic latitude (2.5°) andaltitude bins (a quarter of scale height) within a 5 day sliding window for the models and a 20 day sliding window 5°magnetic latitude and 1 km altitude bins for the COSMIC data.

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Kzz (c), and with SAO Kzz, and no GSWM tidal input (d). The two high electron density bands are the equatorialionosphere anomaly (EIA), which is a result of the equatorial fountain effect.

Because a 20 day sliding window was used for the COSMIC data, the short-period day-to-day variations weresmoothed out (Figure 1a). However, the seasonal and latitudinal variations of the equatorial ionosphere areapparent. There are two peaks at two equinoxes, and the March equinox peak is stronger than that ofSeptember. The TIEGCM simulations with SAO and constant Kzz, both showed similar peaks (Figures 1band 1c). The simulation with SAO Kzz has stronger seasonal variations as expected. The TIEGCM also showedstronger peaks in the Northern Hemisphere compared to the Southern Hemisphere, whereas the COSMICdata have larger peaks in the Southern Hemisphere. To examine the effect of the tides, we performed aTIEGCM run without the GSWM tidal input but with SAO Kzz (Figure 1d). The simulation without tidal inputhas higher ionospheric densities; in other words, the tides reduce the ion density. That is consistent withresults from Yamazaki and Richmond (2013) and Jones et al. (2014). They conclude that composition changesin the thermosphere associated with tides reduce the ionospheric density.

To further evaluate the performance of these models, the vertical profiles of mean electron density of theCOSMIC observations, the three TIEGCM (with SAO, with constant Kzz, and with SAO Kzz but no GSWM)simulations at March equinox are displayed in Figure 2. The EIA is the most prominent feature in the pro-file. The two TIEGCM simulations with GSWM tides (Figures 2b and 2c) are very similar to the COSMICobservations (Figure 2a). The TIEGCM simulation with the SAO Kzz (Figure 2b) is slightly closer to theCOSMIC observations in the Southern Hemisphere and overestimates the ionospheric density in theNorthern Hemisphere (Figure 1). As mentioned earlier, COSMIC shows slightly stronger amplitudes inthe south compared to the north, whereas TIEGCM simulations give slightly larger values in the northcompared to the south (Figure 1). The TIEGCM simulation without the GSWM (Figure 2d) overestimatesthe electron density compared to the COSMIC observations.

(a) (b)

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Figure 2. Vertical profiles of the mean ionospheric density from (a) COSMIC, (b) TIEGCM with constant and (c) SAO KzzwithGSWM and (d) with SAO Kzz without GSWM at March equinox. The density unit is electrons 102 cm�3.

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The simulation from the TIEGCM shows the need for adding the SAO to the Kzz. The ionospheric density sea-sonal variation from TIEGCM is smaller than that from the COSMIC observation with constant Kzz as shown inFigure 1c. Adding SAO to the Kzz does make the ionosphere in the Northern Hemisphere higher than thatfrom COSMIC in Figure 2c.

5.2. Diurnal Westward Zonal Wave Number One Signal (DW1)

While most of the electron day/night variation is due to solar EUV ionization (Roble, 1976), it is worthwhile toexamine the tidal effect on the diurnal variation since the GSWM tidal input has large impact on the iono-sphere. Figure 3 shows the DW1 signal from COSMIC and the three TIEGCM simulations in the same formatas Figure 1. DW1 is a migrating tide. The COSMIC data show that the DW1 amplitudes (Figure 3a) are slightlysmaller than the mean electron density. The two TIEGCM simulations with the GSWM tidal input (Figures 3band 3c) have the DW1 amplitudes about the same size as their respective mean electron densities. TheTIEGCM simulation without GSWM tidal input (Figure 3d) has DW1 amplitude smaller than the mean electrondensity from the same simulation. The DW1 from the no GSWM simulation is larger than other two TIEGCMsimulations with GSWM tides, but the increase is not comparable to that of the electron density. That sug-gests that the electron density enhancement after removing the GSWM tidal input occurs during both dayand night resulting in more increase in the mean electron density than in the DW1.

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Figure 3. Same as Figure 1 but for the DW1 signal in the electron density.

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5.3. Semidiurnal Westward Zonal Wave Number Two Signal (SW2)

Since the GSWM input also include semidiurnal tides, we examine the SW2 signal as well, which is also amigrating tide. Unlike the DW1 signal in the ionosphere, which is mostly in situ excited, the SW2 is mostlyexcited from the lower atmosphere. The SW2 signals from COSMIC and the three TIEGCM simulations areshown in Figure 4. COSMIC shows the strong SW2 amplitudes around equinoxes as in the case for the meanelectron density and DW1. That is understandable because the amplitude of SW2 is roughly proportional tothe electron density, which has a similar SAO. The mesospheric SW2 has more complex seasonal variations asshown by Wu et al. (2011). The SW2 from the two TIEGCM runs with GSWM (Figures 4b and 4c) have smallerdifference compared to the DW1 shown in Figures 3b and 3c. That may be a reflection of a stronger influencefrom the mesospheric tide to the electron density SW2 compared to the DW1, which is driven more by the insitu source. That is further demonstrated by the TIEGCM simulation without the GSWM tidal input (Figure 4d).The SW2 in ionosphere without GSWM tidal input is much smaller than the two with the GSWM tidal input,even though the mean electron density is higher. Only the SW2 amplitude at the equator near the Marchequinox increased. Perhaps, it might be more related to in situ forcing and further investigation is needed.

5.4. Comparison With Other Earlier TIEGCM and TIMEGCM Simulations

The question is how to view our new simulations in the context of those performed by S14 and J17. The stu-dies by S14 used NOGAPS output as the lower boundary for the TIEGCM. They obtained a smaller ionosphere

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Figure 4. Same as Figure 1 but for the SW2 signal in the electron density.

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SAO with this boundary condition than observations. We should notethat tides are larger from NOGAPS than from GSWM (their Figure 1).As we have shown with the TIEGCM simulations as well as byYamazaki and Richmond (2013) and Jones et al. (2014), the tides cansuppress the ionospheric density, so the larger tides from NOGAPS likelyreduced the ionospheric density in S14’s simulation. Consequently, theycould not see the same Kzz effect as in the TIEGCM simulation with theGSWM lower boundary condition and needed to reduce the Kzz constantto obtain comparable ionospheric density obtained with GSWM and astandard constant Kzz.

J17 used TIMEGCM without adding the SAO to Kzz and were able toobtain similar amplitudes of thermosphere and ionosphere SAO asshown in observations. An earlier version of TIMEGCM produced smallertidal amplitudes than the GSWM (Chang et al., 2012). J17 results alsoseem to suggest that the TIMEGCM tides at 97 kmwere smaller than thatof the GSWM used in the TIEGCM. J17 then turned off the tropospherictide further increasing the SAO in the thermosphere and ionosphere.Smaller tides in the TIMEGCMwould lead to the higher ionospheric den-sity and SAO in the TIMEGCM reducing the need for the SAO in the Kzz.

Hence, both the Kzz and tides modulate the SAO in the thermosphere and ionosphere. In the standardTIEGCM case with SAO Kzz and GSWM input, the tides may slightly reduce the ionospheric density. Addingthe SAO to the Kzz decreases the tidal effect and produces matching results with COSMIC. In the case ofthe TIEGCM driven by NOGAPS, the tides were probably too large to be corrected by the standard Kzz con-stant. If TIMEGCM tides are smaller than that in the GSWM and NOGAPS (less reduction in the ionosphere),then they may be able to produce the comparable SAO in the thermosphere and ionosphere without addingthe SAO in the Kzz. That is not to say that smaller tides are correct from the mesospheric dynamics perspec-tive. Wu et al. (2008) have shown that TIMEGCM underestimated the tide compared to observations.

5.5. O/N2 Ratio and O Density

To further investigate the eddy diffusion and tidal effect on the ionosphere, we examine the O/N2 ratio and Odensity at pressure level 1.875 (~ 290 km) for all the TIEGCM simulations (Figure 5a). The pressure levels aredefined as z = ln(P0/P), where P0 is a reference pressure of 5 × 10�4 mb (~240 km) as mentioned earlier. Thedata were averaged in the lower latitude region from �30° to 30° latitudes over all longitudes and times.Under similar conditions, the ionospheric density at pressure level 1.875, which is near the F2 peak, shouldbe roughly proportional to the O/N2 ratio due to the approximate balance between production of O+ byphotoionization and loss of O+ from fast recombination of O+ with the N2 molecules. That is the case forall the TIEGCM simulations. The simulation without GSWM tides has the largest O/N2 ratio, thus larger iono-spheric density. After turning on the GSWM tides, the O/N2 ratio drops. Switching off the Kzz SAO also reducesthe O/N2 ratio.

We also examine the O densities from these simulations (Figure 5b). The O densities were low-latitude regionaverages obtained in the same way as the O/N2 ratios. The O densities from TIEGCM simulations are similarexcept in the case of without GSWM, where the O density is higher in accordance with the O/N2 ratio. Soswitching off the GSWM tide causes an increase in the O density and O/N2 ratio. Turning on the Kzz SAO alsocauses an increase in the O density and O/N2 ratio though to a lesser extent.

It is apparent that there are still many unresolved issues regarding the gravity wave and tidal effects on theionosphere. Looking forward to possible future investigations, we see the critical need of the COSMIC obser-vations for ionosphere and upper atmosphere studies. The COSMIC observations can help further refine theinput parameters for TIEGCM including the seasonal varying eddy diffusion. The 20 day sliding windowsmoothed the COSMIC observations more than the 5 day sliding window of the TIEGCM results.Consequently, we should expect the TIEGCM simulated amplitude to be somewhat larger than that in theobservations, as our comparison shows. We hope to have more data coverage in the future to allow a shortersliding window to be used in COSMIC data analysis. In the future, the COSMIC lower atmosphere neutral

Figure 5. O/N2 ratio and O density at pressure level 1.875 (~ 290 km) fromTIEGCM simulations with GSWM and SAO Kzz (black), without GSWM andwith SAO Kzz (red), and with constant Kzz and with GSWM (green).

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observations can also be assimilated into a whole atmosphere model such as WACCM-X (Whole AtmosphereCommunity Climate Model eXtended) (Liu et al., 2010) as a lower atmosphere input to the model, and thenthe WACCM-X ionosphere simulation can be verified by the COSMIC ionosphere electron profile data. Such acombination will be a very useful tool to study the vertical coupling between the lower atmosphere and iono-sphere. The upcoming COSMIC-2 radio occultation mission will have more coverage in the low-latituderegion allowing for higher temporal resolution extraction of the variations in the ionosphere to validatemodel simulations.

6. Summary

COSMIC GPS RO observations show a SAO in the ionosphere. NCAR TIEGCM simulations were used to inves-tigate the eddy diffusion and tidal effects on the ionosphere SAO. Imposing SAO into the eddy diffusion coef-ficient in the TIEGCM increases the ionosphere SAO and has better agreement with COSMIC observations.Mesospheric and lower thermospheric tides can reduce the ionospheric density and SAO and should beconsidered with the eddy diffusion effect in the TIEGCM simulation. The diurnal variation DW1 in the electrondensity increase in the TIEGCM simulation is comparable to that of the electron density when the GSWM tidesare applied. When the GSWM tides were turned off, the DW1 also increased but not as much as electron den-sity. The simulation from TIEGCM showed the SW2 signal in the ionosphere is mostly from lower atmosphere.

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AcknowledgmentsThis research is supported by NSFgrants AGS1522830 and AGS1339918and NASA grants NNX13AF93G,NNX14AD84G, and NNX15AK75G. NCARis supported by the National ScienceFoundation. We would like to acknowl-edge high-performance computingsupport from Yellowstone (ark:/85065/d7wd3xhc) provided by NCAR’s com-putational and information systemslaboratory, sponsored by the NationalScience Foundation. The TIEGCM modelcan be downloaded at (http://www.hao.ucar.edu/modeling/tgcm/download.php). COSMIC data are available fromhttp://cdaac-www.cosmic.ucar.edu/cdaac/products.html. We acknowledgehelp in this study from Barbara Emery.

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