Mesospheric and thermospheric observations of the January 2010 stratospheric warming event

Wu, Qian; Nozawa, S.

doi:10.1016/j.jastp.2014.11.006

Cited by 15 publications

(27 citation statements)

References 25 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Sridharan et al (2012) reported a quick decrease of a SDT over Tirunelveli (8.7°N, 77.8°E) before the commencement of the 2011 SSW and the SDT amplitude drops to 2 m/s at the SSW onset. Using the Resolute FPI measurements, Wu and Nozawa (2015) observed that the SDT amplitude decreased from~35 to~10 m/s from the day before the SSW occurred to the day after. Numerical simulations made by Fuller-Rowell et al (2011) and Wang et al (2011) predicted the reduction of the SDT amplitude and the enhancement of the TDT amplitude during SSWs.…”

Section: As Shown Inmentioning

confidence: 99%

A Study on the Quarterdiurnal Tide in the Thermosphere at Arecibo During the February 2016 Sudden Stratospheric Warming Event

Gong

et al. 2018

Geophysical Research Letters

View full text Add to dashboard Cite

Using data collected from the Arecibo incoherent scatter radar during 5–10 February 2016, we present a study on the quarterdiurnal tide (QDT) from 250 to 360 km. A sudden stratospheric warming (SSW) event occurred on 8 February coincided with our observation. The maximum amplitude of the QDT, at ~37 m/s, is comparable with the diurnal tide and much larger than the semidiurnal tide. The QDT is largely evanescent. Our results manifest that the F region QDT could be as important as the diurnal and semidiurnal tides. The tidal waves show large variability before and after the commencement of the SSW. Our analysis indicates that the enhancement of the QDT is most likely due to the effect of the SSW. Nonlinear interaction of the diurnal tide with the terdiurnal tide is found to play a significant role in amplifying the QDT during the SSW event.

show abstract

Section: As Shown Inmentioning

confidence: 99%

A Study on the Quarterdiurnal Tide in the Thermosphere at Arecibo During the February 2016 Sudden Stratospheric Warming Event

Gong

et al. 2018

Geophysical Research Letters

View full text Add to dashboard Cite

show abstract

“…This is demonstrated in Figure 1 ,which compares the meridional and vertical structure of monthly mean migrating semidiurnal tidal amplitudes in meridional wind for January 2010 derived from 3-hourly NAVGEM-HA output and 6-hourly NOGAPS-ALPHA output. The NAVGEM-HA results show much larger amplitudes of the migrating semidiurnal tide compared to NOGAPS-ALPHA and are in good agreement with migrating semidiurnal tidal amplitude estimates from Thermosphere Ionosphere Mesosphere Energetics and Dynamics (TIMED) Doppler Interferometer (TIDI) reported by Wu and Nozawa (2015;see Figure 7) during January 2010. This indicates that the analysis frequency of the constraining data set is important, especially in generating the pertinent features (i.e., tidal perturbations with periods less than 24 hr) responsible for much of the TI variability during SSW events (e.g., Pedatella & Liu, 2013;Pedatella, Richmond, et al, 2016, and references therein).…”

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

View full text Add to dashboard Cite

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.

show abstract

“…Observations have clearly demonstrated that SSWs significantly impact equatorial vertical plasma drifts [Chau et al, 2009;Fejer et al, 2010;Rodrigues et al, 2011;Park et al, 2012;Siddiqui et al, 2015], low-latitude electron densities [Goncharenko et al, 2010a[Goncharenko et al, , 2010bLin et al, 2012Lin et al, , 2013Jonah et al, 2014], and also the middle-to high-latitude ionosphere [Korenkov et al, 2012;Fagundes et al, 2015;Medvedeva et al, 2015;Pedatella and Maute, 2015;Polyakova et al 2014;Shpynev et al, 2015]. There is also evidence that SSWs perturb the thermosphere neutral density, temperature, and winds [Funke et al, 2010;Liu et al, 2011;Wu and Nozawa, 2015;Sassi et al, 2016]. SSWs therefore have a broad impact across the entirety of the upper atmosphere.…”

Section: Introductionmentioning

confidence: 99%

Multimodel comparison of the ionosphere variability during the 2009 sudden stratosphere warming

et al. 2016

View full text Add to dashboard Cite

A comparison of different model simulations of the ionosphere variability during the 2009 sudden stratosphere warming (SSW) is presented. The focus is on the equatorial and low‐latitude ionosphere simulated by the Ground‐to‐topside model of the Atmosphere and Ionosphere for Aeronomy (GAIA), Whole Atmosphere Model plus Global Ionosphere Plasmasphere (WAM+GIP), and Whole Atmosphere Community Climate Model eXtended version plus Thermosphere‐Ionosphere‐Mesosphere‐Electrodynamics General Circulation Model (WACCMX+TIMEGCM). The simulations are compared with observations of the equatorial vertical plasma drift in the American and Indian longitude sectors, zonal mean F region peak density (NmF2) from the Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC) satellites, and ground‐based Global Positioning System (GPS) total electron content (TEC) at 75°W. The model simulations all reproduce the observed morning enhancement and afternoon decrease in the vertical plasma drift, as well as the progression of the anomalies toward later local times over the course of several days. However, notable discrepancies among the simulations are seen in terms of the magnitude of the drift perturbations, and rate of the local time shift. Comparison of the electron densities further reveals that although many of the broad features of the ionosphere variability are captured by the simulations, there are significant differences among the different model simulations, as well as between the simulations and observations. Additional simulations are performed where the neutral atmospheres from four different whole atmosphere models (GAIA, HAMMONIA (Hamburg Model of the Neutral and Ionized Atmosphere), WAM, and WACCMX) provide the lower atmospheric forcing in the TIME‐GCM. These simulations demonstrate that different neutral atmospheres, in particular, differences in the solar migrating semidiurnal tide, are partly responsible for the differences in the simulated ionosphere variability in GAIA, WAM+GIP, and WACCMX+TIMEGCM.

show abstract

Mesospheric and thermospheric observations of the January 2010 stratospheric warming event

Cited by 15 publications

References 25 publications

A Study on the Quarterdiurnal Tide in the Thermosphere at Arecibo During the February 2016 Sudden Stratospheric Warming Event

A Study on the Quarterdiurnal Tide in the Thermosphere at Arecibo During the February 2016 Sudden Stratospheric Warming Event

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

Multimodel comparison of the ionosphere variability during the 2009 sudden stratosphere warming

Contact Info

Product

Resources

About