Impact of non-migrating tides on the low latitude ionosphere during a sudden stratospheric warming event in January 2010

McDonald, S. E.; Sassi, Fabrizio; Tate, J.; McCormack, J. P.; Kuhl, David D.; Drob, D. P.; Metzler, C.; Mannucci, A. J.

doi:10.1016/j.jastp.2017.09.012

Cited by 26 publications

(35 citation statements)

References 60 publications

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“…NAVGEM-HA replaces the earlier Navy Operational Global Atmospheric Prediction System-Advanced Level Physics High Altitude forecast model (NOGAPS-ALPHA; Eckermann et al, 2009). NAVGEM-HA combines a semi-implicit semi-Lagrangian global forecast model (Hogan et al, 2014) with a hybrid four-dimensional variational (4DVAR) DA system based on the Naval Research Laboratory Atmospheric Variational Data Assimilation System-Accelerated Representer (NAVDAS-AR, Kuhl et al, 2013, and references therein) and has been used to constrain the tropospheric, stratospheric, and mesospheric variability in whole atmosphere models (e.g., McDonald et al, 2018). Unlike the earlier NOGAPS-ALPHA system, which used a three-dimensional variational (3DVAR) DA algorithm that consolidates observations within a 6-hr window and used static model covariance estimates, the hybrid 4DVAR NAVDAS-AR in NAVGEM-HA accounts for time-varying observations within the 6-hr window through a linear combination of climatological covariances and ensemble-based model covariances to obtain more realistic estimates of forecast model uncertainties within the DA algorithm.…”

Section: Navgem-hamentioning

confidence: 99%

Evaluating Different Techniques for Constraining Lower Atmospheric Variability in an Upper Atmosphere General Circulation Model: A Case Study During the 2010 Sudden Stratospheric Warming

Jones

Drob

Siskind

et al. 2018

J Adv Model Earth Syst

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We analyze the effects specified dynamics (SD) and 4D Tendency nudging have on accurately reproducing the middle and upper atmospheric variability induced by the 2010 sudden stratospheric warming (SSW) event in the National Center for Atmospheric Research thermosphere‐ionosphere‐mesosphere‐electrodynamics general circulation model (TIME‐GCM). TIME‐GCM numerical experiments were performed using constrained middle atmospheric winds and temperatures from a high‐altitude version of the Navy Global Environmental Model to compare the previously implemented SD scheme, with the newly implemented 4D Tendency scheme. Model comparisons focused on zonal mean winds, composition, planetary waves, and tides in the thermosphere‐ionosphere system. Through 4D Tendency nudging we reveal that coupling coefficients of the one‐way SD coupling approach between the TIME‐GCM and observed SSW conditions were too strong. Prior implementations produced unusually strong vertical shears in the zonal mean winds in the mesosphere and lower thermosphere (MLT), where the model is free running. Differences in zonal mean MLT winds between SD and 4D Tendency nudging simulations resulted in migrating diurnal (DW1) and semidiurnal (SW2) tidal amplitude differences at lower thermospheric altitudes. The consequences of simulating different MLT dynamics using SD and 4D Tendency nudging in the overlaying ionosphere are reported and validated using electron density data from the Constellation Observing System for Meteorology, Ionosphere, and Climate satellites. Although we demonstrate that SD and 4D Tendency nudging techniques are approximately equivalent, results presented herein establish that 4D Tendency nudging has the added potential to identify physical model parameters that contribute to data‐model differences during the 2010 SSW.

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Section: Navgem-hamentioning

confidence: 99%

Evaluating Different Techniques for Constraining Lower Atmospheric Variability in an Upper Atmosphere General Circulation Model: A Case Study During the 2010 Sudden Stratospheric Warming

Jones

Drob

Siskind

et al. 2018

J Adv Model Earth Syst

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“…The seminal paper by Immel et al (2006) indicated connections between tidal patterns in the lower thermosphere and the F region ionosphere and noted that the tidal structure was linked to patterns of convection in the equatorial troposphere. Furthermore, numerous papers (e.g., Goncharenko, Chau, et al, 2010, Goncharenko, Coster, et al, 2010Liu & Roble, 2002;McDonald et al, 2018;Pedatella et al, 2012) have shown how planetary wave forcing, specifically via stratospheric sudden warmings (SSWs), can affect lower thermospheric tides and thus the ionosphere.…”

Section: Discussionmentioning

confidence: 99%

Space Weather Quarterly Volume 16, Issue 4, 2019

2019

Space Weather Quarterly

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“…Especially in the low‐latitude ionosphere, the vertical plasma drift velocities ( E × B drifts) that are so critical in defining the structure and variability of the EIA depend crucially on the solar tides (England et al, , ; Maute et al, ; Millward et al, ; Tarpley, , ). A variety of nonmigrating tides, especially nonmigrating diurnal eastward propagating wave number 2 and 3 (DE2 and DE3, respectively), contribute to the plasma zonal structure (Hagan et al, ; England , ; Kil et al, ; McDonald et al, ) near the equator. The DE3 tide has been linked to the wave‐4 pattern in the EIA when viewed at a constant local time (e.g., Immel et al, ), whereas DE2 is a contributor to the wave‐3 pattern that typically emerges in the boreal winter months (Forbes et al, ; Kil et al, ; Pancheva & Mukhtarov, ), although other tides (e.g., DW4, DE2, and SW5) play a role (McDonald et al, ).…”

Section: Intraseasonal Variabilitymentioning

confidence: 99%

“…A variety of nonmigrating tides, especially nonmigrating diurnal eastward propagating wave number 2 and 3 (DE2 and DE3, respectively), contribute to the plasma zonal structure (Hagan et al, ; England , ; Kil et al, ; McDonald et al, ) near the equator. The DE3 tide has been linked to the wave‐4 pattern in the EIA when viewed at a constant local time (e.g., Immel et al, ), whereas DE2 is a contributor to the wave‐3 pattern that typically emerges in the boreal winter months (Forbes et al, ; Kil et al, ; Pancheva & Mukhtarov, ), although other tides (e.g., DW4, DE2, and SW5) play a role (McDonald et al, ). Stationary PWs are also important, such as the stationary PW with zonal wave number four (sPW4) that arises from the non‐linear interaction of DE3 and DW1 in the thermosphere (Hagan et al, ).…”

Section: Intraseasonal Variabilitymentioning

confidence: 99%

“…Notwithstanding theoretical difficulties, 16‐day periodicities are not difficult to detect in modeling simulations of the thermosphere and ionosphere. Figure a is obtained from a simulation with the SAMI3 (Sami is Another Model of the Ionosphere, v. 3) model coupled with the Whole Atmosphere Community Climate Model extended version (WACCM‐X; McDonald et al, ). It shows the band‐passed amplitude of N m F 2 for zonal wavenumber 1 at westward frequencies between 0.02 and 0.10 cpd (50‐ to 10‐day periods), which shows a prominent peak in boreal winter around day 50–60 in 2016, and a minor peak around day 30.…”

Section: Intraseasonal Variabilitymentioning

confidence: 99%

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Whole Atmosphere Coupling on Intraseasonal and Interseasonal Time Scales: A Potential Source of Increased Predictive Capability

2019

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Recent advances in developing accurate, physics‐based models of the coupled ionosphere‐thermosphere (CIT) system have now made these models an integral part of next‐generation space weather prediction capabilities. These advances have produced a better understanding of how the CIT is affected by variability in the neutral lower atmosphere. However, the impacts on the CIT of lower atmospheric variability over time scales with characteristic periods longer than ~10 days have received little attention, despite clear evidence of this variability in atmospheric circulation patterns throughout the stratosphere, mesosphere, and lower thermosphere. This review synthesizes the state of knowledge on long‐term variability (>10 days) originating in the lower atmosphere and its impacts on the CIT, highlighting the following critical points and challenges: (a) planetary wave oscillations are likely to couple the lower and upper atmospheres, especially those corresponding to normal modes of the atmosphere, but it remains unclear whether they impact the ionosphere directly via wind‐dynamo coupling, or indirectly via modulation of solar and lunar tides; (b) while fast moving planetary wave oscillations are ubiquitous in the CIT especially during solstices, there is only sporadic evidence that the slowest moving modes are also present in the upper atmosphere; (c) there is abundant evidence of long‐term variations of tidal amplitudes in the CIT, but how and why such variations occur still remain; (d) interseasonal variations associated with major tropospheric and stratospheric variability have been observed, but the physical pathways are still poorly understood.

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Impact of non-migrating tides on the low latitude ionosphere during a sudden stratospheric warming event in January 2010

Cited by 26 publications

References 60 publications

Evaluating Different Techniques for Constraining Lower Atmospheric Variability in an Upper Atmosphere General Circulation Model: A Case Study During the 2010 Sudden Stratospheric Warming

Evaluating Different Techniques for Constraining Lower Atmospheric Variability in an Upper Atmosphere General Circulation Model: A Case Study During the 2010 Sudden Stratospheric Warming

Space Weather Quarterly Volume 16, Issue 4, 2019

Whole Atmosphere Coupling on Intraseasonal and Interseasonal Time Scales: A Potential Source of Increased Predictive Capability

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